Application of the United Nations Framework Classification for Resources (UNFC) to Geothermal Energy Resources - Selected case studies

Full text

UNECEUNITED NATIONS
Application of the UNFC to Geothermal Energy Resources - Selected case studies
Palais des Nations
CH - 1211 Geneva 10, Switzerland
Telephone: +41(0)22 917 44 44
E-mail: info.ece@unece.org
Website: http://www.unece.org
Information Service
United Nations Economic Commission for Europe
This publication includes a set of 14 case studies on the application of the United
Nations Framework Classiÿcation for Resources (UNFC) to geothermal energy from
Australia, Germany, Hungary, Iceland, Italy, the Netherlands, New Zealand, the
Philippines and Russian Federation.
UNFC, which has been developed by the Expert Group on Resource Classiÿcation of
the United Nations Economic Commission for Europe (UNECE), applies to all energy
and mineral resources globally. This includes renewable energy resources,
anthropogenic resources and injection projects for the geological storage of carbon
dioxide.
UNFC can be applied to geothermal energy through two sets of Speciÿcations for the
application of UNFC to Renewable Energy Resources and Geothermal Energy
Resources developed in 2016.
The case studies are presented here to illustrate the application of the geothermal
energy speciÿcations for the uniform use of UNFC in di°erent contexts.
These application examples from di°erent countries provide a range of scenarios in
the classiÿcation of geothermal resources in a manner consistent with the
classiÿcation of other energy resources.
Selected case studies
Application of the United Nations
Framework Classication for Resources (UNFC)
to Geothermal Energy Resources
UNECE Energy Series
Application of the United Nations
Framework Classication for Resources (UNFC)
to Geothermal Energy Resources
Selected case studies
Layout and Printing at United Nations, Geneva – 1734615 (E) – November 2017 – 3,518 – ECE/ENERGY/110
ISBN 978 -92-1-117136-5

UNITED NATIONS ECONOMIC COMMISSION FOR EUROPE
Prepared by the UNECE Expert Group on Resource
Classification
ENERGY SERIES No. 51
UNITED NATIONS
NEW YORK AND GENEVA, 2017

NOTE
The designations employed and the presentation of the material in this publication
do not imply the expression of any opinion whatsoever on the part of the Secretariat of the
United Nations concerning the legal status of any country, territory, city or area, or of its
authorities, or concerning the delimitation of its frontiers or boundaries.
Mention of any firm, licensed process or commercial products does not imply
endorsement by the United Nations.
ECE/ENERGY/110
UNITED NATIONS PUBLICATION
Sales No. E.17.II.E.15
ISBN 978-92-1-117136-5
eISBN 978-92-1-362719-8
ISSN 1014-7225
Copyright © 2017, United Nations
All rights reserved worldwide
United Nations publication issued by
the Economic Commission for Europe (ECE)

Foreword
Over the last century, different energy and raw material sectors, as well as countries,
adopted a range of approaches to classify and manage resources. New challenges to the
production, distribution and utilization of energy and raw materials have, however,
emerged in recent years that demand innovative approaches for an integrated resource
management system. The 2030 Agenda for Sustainable Development defines a clear
pathway to address these challenges in a holistic manner.
The United Nations Framework Classification for Resources (UNFC) was developed
under the auspices of the United Nations Economic Commission for Europe by a dedicated
community of experts drawn from a range of fields, but with the common goal to develop
an internationally applicable scheme for the classification, reporting and management of
energy and mineral resources. Though initially developed for the mineral and petroleum
sectors, UNFC has recently expanded its scope to include renewable energy. Growing
awareness and interest in renewable energy resources, including geothermal resources, has
highlighted a need to standardize the way in which renewable energy potential is classified
and reported.
To facilitate improved global communication in the geothermal sector, the ECE
Expert Group on Resource Classification, under the framework of a Memorandum of
Understanding between the United Nations Economic Commission for Europe and the
International Geothermal Association (IGA), developed specifications for applying UNFC to
geothermal energy resources. The specifications were issued in September 2016.
A set of 14 case studies from Australia, Germany, Hungary, Iceland, Italy, Netherlands,
New Zealand, Philippines and Russian Federation are presented here to facilitate a better
understanding of the specifications and the uniform application of UNFC to geothermal
resources. These application examples illustrate the classification of a range of different
geothermal resource scenarios in a manner consistent with other energy resources. The
approach also provides valuable indicators to the value of UNFC as a tool to support
attainment of the Sustainable Development Goals.
Experts in geothermal energy resources, as well as those in other energy and mineral
sectors, will find this collection of case studies a useful reference document in their efforts
to apply a globally applicable integrated resource management system. I commend all
those involved in the preparation, review and verification of these case studies and thank,
in particular, the International Geothermal Association for its support.
Olga Algayerova
Executive Secretary
United Nations Economic Commission for Europe
iii

Acknowledgements
The development of these case studies was undertaken by a sub-group (Working
Group) of expert volunteers led by Gioia Falcone (Leader) with Miklos Antics, Roy Baria,
Larry Bayrante, Paolo Conti, Malcolm Grant, Robert Hogarth, Egill Juliusson, Harmen
Mijnlieff, Annamária Nádor, Greg Ussher and Kate Young as members, and Graeme
Beardsmore and Horst Rueter as observers.
The International Geothermal Association (IGA)has actively supported this work
through its IGA Resources and Reserves Committee (Chaired by Graeme Beardsmore).
UNECE and IGA have a Memorandum of Understanding to develop specifications and
guidelines for the application of UNFC to geothermal energy.
Face-to-face meetings of the Working Group by means of periodic workshops were
made possible by the support of the Energy Sector Management Assistance Program of
the World Bank (ESMAP), the United States Department of Energy (DOE) and the
Geothermal Resources Council (GRC), with the logistical organization of the IGA Service
Company. The Working Group on Renewable Energy Classification of the UNECE Expert
Group on Resource Classification, in particular its Chair, Frank Denelle, is thanked for the
support and guidance provided in developing and reviewing the case studies.
iv

Contents
Foreword................................................................................................................................................................... iii
Acknowledgements .............................................................................................................................................. iv
Contents .................................................................................................................................................................... v
Introduction ............................................................................................................................................................. 1
Case Study 1: Ngatamariki ...................................................................................... 2
Project summary.............................................................................................................................................. 2
Ngatamariki project ....................................................................................................................................... 3
Quantification ................................................................................................................................................... 3
Product type...................................................................................................................................................... 3
Reference Point................................................................................................................................................ 3
Geothermal Energy Resources ................................................................................................................... 3
UNFC-2009 classification ............................................................................................................................. 4
E category classification and subclassification.............................................................................. 4
F category classification and subclassification.............................................................................. 4
G category classification and subclassification............................................................................. 5
UNFC-2009 Geothermal Energy Resources .......................................................................................... 5
References.......................................................................................................................................................... 5
Case Study 2: Habanero........................................................................................... 6
Project Summary ............................................................................................................................................. 6
Habanero Project ............................................................................................................................................ 7
Quantification ................................................................................................................................................... 8
Geothermal Energy Product........................................................................................................................ 8
Reference Point................................................................................................................................................ 8
Geothermal Energy Resources ................................................................................................................... 8
UNFC-2009 classification ............................................................................................................................. 8
E category .................................................................................................................................................... 8
F category .................................................................................................................................................... 9
G category ................................................................................................................................................... 9
UNFC-2009 Geothermal Energy Resources.......................................................................................... 9
References.......................................................................................................................................................... 9
Figure 1 -Induced Micro-Seismicity at Habanero ............................................................................. 7
v

- vi –
Case Study 3: Insheim .............................................................................................. 10
Project Summary ............................................................................................................................................. 10
Insheim project ................................................................................................................................................ 11
Quantification ................................................................................................................................................... 12
Electricity ...................................................................................................................................................... 12
Heat ................................................................................................................................................................ 12
Product type ...................................................................................................................................................... 13
Reference Point ................................................................................................................................................ 13
Geothermal Energy Resources ................................................................................................................... 13
Electricity ...................................................................................................................................................... 13
Possible Additional Electricity for 85 L/s flow ............................................................................... 13
Heat ................................................................................................................................................................ 13
UNFC-2009 classification ............................................................................................................................. 13
E category classification and subclassification .............................................................................. 14
F category classification and subclassification .............................................................................. 14
G category classification and subclassification ............................................................................. 14
E category classification and subclassification .............................................................................. 15
F category classification and subclassification .............................................................................. 15
G category classification and subclassification ............................................................................. 16
E category classification and subclassification .............................................................................. 17
F category classification and subclassification .............................................................................. 17
G category classification and subclassification ............................................................................. 17
References .......................................................................................................................................................... 18
Case Study 4: Rotliegend-3 Geothermal Project ................................................... 19
Project summary .............................................................................................................................................. 19
Quantification ................................................................................................................................................... 19
Reference Point ................................................................................................................................................ 21
Geothermal Energy Resources ................................................................................................................... 22
UNFC-2009 classification ............................................................................................................................. 22
E category classification and subclassification .............................................................................. 22
F category classification and subclassification .............................................................................. 23
G category classification and subclassification ............................................................................. 23
UNFC-2009 classification and quantification ....................................................................................... 24
Disclaimer ........................................................................................................................................................... 24
References .......................................................................................................................................................... 24
Figure 1 - Input ofr indicative Geothermanl power calculcaion for the project .................... 20
Figure 2 - Probabilistic calculation results ............................................................................................ 21
- vii –
Case Study 5: Dutch Rotliegend Play Area – Nationwide .................................... 25
Project summary .............................................................................................................................................. 25
Geothermal resource classification of Rotliegend Geothermal projects .................................. 27
Production projects ................................................................................................................................. 27
Exploration projects ................................................................................................................................. 29
Rotliegend Play resource estimate .................................................................................................... 30
Rotliegend Play resource estimate .................................................................................................... 30
Disclaimer ........................................................................................................................................................... 31
References .......................................................................................................................................................... 31
Figure 1 - Map of data for evaluation of the Rotliegend aquifer ................................................ 26
Table 1 - Listing of resource estimates per project based on installed power and
local hour estimates. Class: E1.2; F1.1; G1, 2, 3 .................................................................................... 28
Table 2 - UNFC-2009 classification of the Rotliegend Play resource estimate ...................... 30
Table 3 - The best estimate of the geothermal resource potential of the
Dutch Rotliegend Play ................................................................................................................................... 31
Case Study 6: Hódmezővásárhely District Heating ............................................... 32
Project summary .............................................................................................................................................. 32
Quantification ................................................................................................................................................... 33
Product type ...................................................................................................................................................... 34
Reference Point ................................................................................................................................................ 34
Project lifetime ................................................................................................................................................. 34
Geothermal resources ................................................................................................................................... 34
UNFC-2009 classification ............................................................................................................................. 34
E category classification and subclassification of the present project ................................ 35
F category classification and subclassification of the present project ................................ 35
G category classification of the present project ........................................................................... 35
UNFC-2009 classification and quantification of the present project.......................................... 36
E category classification and subclassification of the potential future project(s) ........... 36
F category classification and subclassification of the future potential project(s) ........... 36
G category classification of the future potential project(s) ..................................................... 36
UNFC-2009 classification and quantification of the future potential project(s) .................... 37
References .......................................................................................................................................................... 37
Figure 1 - Distribution of uses in Hódmezővásárhely
Total annual production of the entire cascade system (2009): 1,605,407 m3 ......................... 33
Appendix 1 - Assumptions of volumetric Monte Carlo assessment ........................................... 38
Estimation of recharge areas of production wells ....................................................................... 38
Figure 1 - Hódmezővásárhely project – producing wells ................................................................ 38
Table 1 - Input values for Monte Carlo .................................................................................................. 38
vi

- vi –
Case Study 3: Insheim .............................................................................................. 10
Project Summary ............................................................................................................................................. 10
Insheim project ................................................................................................................................................ 11
Quantification ................................................................................................................................................... 12
Electricity ...................................................................................................................................................... 12
Heat ................................................................................................................................................................ 12
Product type ...................................................................................................................................................... 13
Reference Point ................................................................................................................................................ 13
Geothermal Energy Resources ................................................................................................................... 13
Electricity ...................................................................................................................................................... 13
Possible Additional Electricity for 85 L/s flow ............................................................................... 13
Heat ................................................................................................................................................................ 13
UNFC-2009 classification ............................................................................................................................. 13
E category classification and subclassification .............................................................................. 14
F category classification and subclassification .............................................................................. 14
G category classification and subclassification ............................................................................. 14
E category classification and subclassification .............................................................................. 15
F category classification and subclassification .............................................................................. 15
G category classification and subclassification ............................................................................. 16
E category classification and subclassification .............................................................................. 17
F category classification and subclassification .............................................................................. 17
G category classification and subclassification ............................................................................. 17
References .......................................................................................................................................................... 18
Case Study 4: Rotliegend-3 Geothermal Project ................................................... 19
Project summary .............................................................................................................................................. 19
Quantification ................................................................................................................................................... 19
Reference Point ................................................................................................................................................ 21
Geothermal Energy Resources ................................................................................................................... 22
UNFC-2009 classification ............................................................................................................................. 22
E category classification and subclassification .............................................................................. 22
F category classification and subclassification .............................................................................. 23
G category classification and subclassification ............................................................................. 23
UNFC-2009 classification and quantification ....................................................................................... 24
Disclaimer ........................................................................................................................................................... 24
References .......................................................................................................................................................... 24
Figure 1 - Input ofr indicative Geothermanl power calculcaion for the project .................... 20
Figure 2 - Probabilistic calculation results ............................................................................................ 21
- vii –
Case Study 5: Dutch Rotliegend Play Area – Nationwide .................................... 25
Project summary .............................................................................................................................................. 25
Geothermal resource classification of Rotliegend Geothermal projects .................................. 27
Production projects ................................................................................................................................. 27
Exploration projects ................................................................................................................................. 29
Rotliegend Play resource estimate .................................................................................................... 30
Rotliegend Play resource estimate .................................................................................................... 30
Disclaimer ........................................................................................................................................................... 31
References .......................................................................................................................................................... 31
Figure 1 - Map of data for evaluation of the Rotliegend aquifer ................................................ 26
Table 1 - Listing of resource estimates per project based on installed power and
local hour estimates. Class: E1.2; F1.1; G1, 2, 3 .................................................................................... 28
Table 2 - UNFC-2009 classification of the Rotliegend Play resource estimate ...................... 30
Table 3 - The best estimate of the geothermal resource potential of the
Dutch Rotliegend Play ................................................................................................................................... 31
Case Study 6: Hódmezővásárhely District Heating ............................................... 32
Project summary .............................................................................................................................................. 32
Quantification ................................................................................................................................................... 33
Product type ...................................................................................................................................................... 34
Reference Point ................................................................................................................................................ 34
Project lifetime ................................................................................................................................................. 34
Geothermal resources ................................................................................................................................... 34
UNFC-2009 classification ............................................................................................................................. 34
E category classification and subclassification of the present project ................................ 35
F category classification and subclassification of the present project ................................ 35
G category classification of the present project ........................................................................... 35
UNFC-2009 classification and quantification of the present project.......................................... 36
E category classification and subclassification of the potential future project(s) ........... 36
F category classification and subclassification of the future potential project(s) ........... 36
G category classification of the future potential project(s) ..................................................... 36
UNFC-2009 classification and quantification of the future potential project(s) .................... 37
References .......................................................................................................................................................... 37
Figure 1 - Distribution of uses in Hódmezővásárhely
Total annual production of the entire cascade system (2009): 1,605,407 m3 ......................... 33
Appendix 1 - Assumptions of volumetric Monte Carlo assessment ........................................... 38
Estimation of recharge areas of production wells ....................................................................... 38
Figure 1 - Hódmezővásárhely project – producing wells ................................................................ 38
Table 1 - Input values for Monte Carlo .................................................................................................. 38
vii

- viii –
Case Study 7: Alto Peak ........................................................................................... 39
Project summary .............................................................................................................................................. 39
Alto Peak project ............................................................................................................................................. 40
Quantification ................................................................................................................................................... 40
Product type ...................................................................................................................................................... 40
Reference Point ................................................................................................................................................ 40
Geothermal Energy Resources ................................................................................................................... 41
UNFC-2009 classification ............................................................................................................................. 41
E category classification ......................................................................................................................... 41
F category classification and subclassification .............................................................................. 41
G category classification ........................................................................................................................ 42
UNFC-2009 classification and quantification ....................................................................................... 43
Disclaimer ........................................................................................................................................................... 43
References .......................................................................................................................................................... 43
Case Study 8: Baslay-Dauin ..................................................................................... 44
Project summary .............................................................................................................................................. 44
Baslay-Dauin project ...................................................................................................................................... 44
Quantification ................................................................................................................................................... 45
Product type ...................................................................................................................................................... 45
Reference Point ................................................................................................................................................ 45
Geothermal Energy Resources ................................................................................................................... 45
UNFC-2009 classification ............................................................................................................................. 46
E category classification and subclassification .............................................................................. 46
F category classification and subclassification .............................................................................. 46
G category classification ........................................................................................................................ 47
UNFC-2009 classification and quantification ....................................................................................... 47
Disclaimer ........................................................................................................................................................... 47
References .......................................................................................................................................................... 48
Case Study 9: Canavese GeoDH System ................................................................. 49
Project summary .............................................................................................................................................. 49
Local and hydrogeological context .......................................................................................................... 49
Canavese plant description ......................................................................................................................... 50
Quantification ................................................................................................................................................... 50
Product type ...................................................................................................................................................... 50
Reference Point ................................................................................................................................................ 51
UNFC-2009 classification ............................................................................................................................. 53
- ix –
E category classification and subclassification .............................................................................. 53
F category classification and subclassification .............................................................................. 53
G category classification ........................................................................................................................ 53
UNFC-2009 classification and quantification ....................................................................................... 54
Reference ............................................................................................................................................................ 54
Figure 1 - Points of reference for the assessment of GSHP projects in heating mode ....... 51
Figure 2 - Simplified scheme and energy fluxes of “Canavese” plant ........................................ 52
Table 1 - Nominal capacities and efficiencies of the “Canavese” heat generation plant ... 52
Table 2 - Energy quantities over Project lifetime (20 years) and points of evaluations ...... 52
Case Study 10: Vertical Ground-Coupled Heat Pump System ............................. 55
Project summary .............................................................................................................................................. 55
Reference building and thermal load...................................................................................................... 55
Ground reservoir.............................................................................................................................................. 55
Ground-coupled heat exchangers (vertical borehole heat exchangers) ................................... 56
Heat generators: GCHP and back-up unit ............................................................................................. 56
Quantification ................................................................................................................................................... 57
Product type ...................................................................................................................................................... 57
Reference Point ................................................................................................................................................ 57
UNFC-2009 classification ............................................................................................................................. 58
E category classification and subclassification .............................................................................. 58
F category classification and subclassification .............................................................................. 58
G category classification and subclassification ............................................................................. 59
UNFC-2009 classification and quantification ....................................................................................... 59
References .......................................................................................................................................................... 60
Table 1 - Monthly heating and cooling loads for the building..................................................... 55
Table 2 - Ground thermal properties and BHEs thermal and geometrical characteristics 56
Table 3 - Nominal performances of the GCHP at rating conditions........................................... 56
Table 4 - Nominal performances of the AHP at rating conditions .............................................. 57
Table 5 - Energy quantities over Project lifetime (20 years) and corresponding
points of evaluations ..................................................................................................................................... 58
Table 6 - Main performance indexes and data of the GSHP operation (20 years) ............... 60
Figure 1(a) and 1(b) - Points of evaluation for the assessment of GSHP projects
in heating and cooling mode ..................................................................................................................... 59
Figure 1(a) - Heating mode ......................................................................................................................... 59
Figure 1(b) - Cooling mode......................................................................................................................... 60
viii

- viii –
Case Study 7: Alto Peak ........................................................................................... 39
Project summary .............................................................................................................................................. 39
Alto Peak project ............................................................................................................................................. 40
Quantification ................................................................................................................................................... 40
Product type ...................................................................................................................................................... 40
Reference Point ................................................................................................................................................ 40
Geothermal Energy Resources ................................................................................................................... 41
UNFC-2009 classification ............................................................................................................................. 41
E category classification ......................................................................................................................... 41
F category classification and subclassification .............................................................................. 41
G category classification ........................................................................................................................ 42
UNFC-2009 classification and quantification ....................................................................................... 43
Disclaimer ........................................................................................................................................................... 43
References .......................................................................................................................................................... 43
Case Study 8: Baslay-Dauin ..................................................................................... 44
Project summary .............................................................................................................................................. 44
Baslay-Dauin project ...................................................................................................................................... 44
Quantification ................................................................................................................................................... 45
Product type ...................................................................................................................................................... 45
Reference Point ................................................................................................................................................ 45
Geothermal Energy Resources ................................................................................................................... 45
UNFC-2009 classification ............................................................................................................................. 46
E category classification and subclassification .............................................................................. 46
F category classification and subclassification .............................................................................. 46
G category classification ........................................................................................................................ 47
UNFC-2009 classification and quantification ....................................................................................... 47
Disclaimer ........................................................................................................................................................... 47
References .......................................................................................................................................................... 48
Case Study 9: Canavese GeoDH System ................................................................. 49
Project summary .............................................................................................................................................. 49
Local and hydrogeological context .......................................................................................................... 49
Canavese plant description ......................................................................................................................... 50
Quantification ................................................................................................................................................... 50
Product type ...................................................................................................................................................... 50
Reference Point ................................................................................................................................................ 51
UNFC-2009 classification ............................................................................................................................. 53
- ix –
E category classification and subclassification .............................................................................. 53
F category classification and subclassification .............................................................................. 53
G category classification ........................................................................................................................ 53
UNFC-2009 classification and quantification ....................................................................................... 54
Reference ............................................................................................................................................................ 54
Figure 1 - Points of reference for the assessment of GSHP projects in heating mode ....... 51
Figure 2 - Simplified scheme and energy fluxes of “Canavese” plant ........................................ 52
Table 1 - Nominal capacities and efficiencies of the “Canavese” heat generation plant ... 52
Table 2 - Energy quantities over Project lifetime (20 years) and points of evaluations ...... 52
Case Study 10: Vertical Ground-Coupled Heat Pump System ............................. 55
Project summary .............................................................................................................................................. 55
Reference building and thermal load...................................................................................................... 55
Ground reservoir.............................................................................................................................................. 55
Ground-coupled heat exchangers (vertical borehole heat exchangers) ................................... 56
Heat generators: GCHP and back-up unit ............................................................................................. 56
Quantification ................................................................................................................................................... 57
Product type ...................................................................................................................................................... 57
Reference Point ................................................................................................................................................ 57
UNFC-2009 classification ............................................................................................................................. 58
E category classification and subclassification .............................................................................. 58
F category classification and subclassification .............................................................................. 58
G category classification and subclassification ............................................................................. 59
UNFC-2009 classification and quantification ....................................................................................... 59
References .......................................................................................................................................................... 60
Table 1 - Monthly heating and cooling loads for the building..................................................... 55
Table 2 - Ground thermal properties and BHEs thermal and geometrical characteristics 56
Table 3 - Nominal performances of the GCHP at rating conditions........................................... 56
Table 4 - Nominal performances of the AHP at rating conditions .............................................. 57
Table 5 - Energy quantities over Project lifetime (20 years) and corresponding
points of evaluations ..................................................................................................................................... 58
Table 6 - Main performance indexes and data of the GSHP operation (20 years) ............... 60
Figure 1(a) and 1(b) - Points of evaluation for the assessment of GSHP projects
in heating and cooling mode ..................................................................................................................... 59
Figure 1(a) - Heating mode ......................................................................................................................... 59
Figure 1(b) - Cooling mode......................................................................................................................... 60
ix

- x –
Case Study 11: Aggregation GSHP-Potential, North Rhine Westphalia............. 61
GSHP-Potential, North Rhine Westphalia, Germany. project summary .................................... 61
Quantification ................................................................................................................................................... 62
Product type ...................................................................................................................................................... 63
Reference Point ................................................................................................................................................ 63
UNFC-2009 classification and quantification ....................................................................................... 63
E category classification ......................................................................................................................... 64
F category classification and subclassification .............................................................................. 64
G category classification ........................................................................................................................ 64
Reference ............................................................................................................................................................ 64
Figure 1 - Points of reference for the assessment of GSHP projects in heating mode ....... 63
Case Study 12: Pauzhetsky geothermal field ........................................................ 65
Project summary .............................................................................................................................................. 65
Quantification ................................................................................................................................................... 66
Electricity ...................................................................................................................................................... 66
Heat ................................................................................................................................................................ 67
Product type ...................................................................................................................................................... 67
Reference Point ................................................................................................................................................ 67
Geothermal Energy Resources ................................................................................................................... 67
Electricity for single-flash power plant ............................................................................................. 67
Possible Electricity for binary power plant ..................................................................................... 67
Heat ................................................................................................................................................................ 67
UNFC-2009 classification ............................................................................................................................. 68
E category classification and subclassification .............................................................................. 68
F category classification and subclassification .............................................................................. 68
G category classification and subclassification ............................................................................. 69
E category classification and subclassification .............................................................................. 70
F category classification and subclassification .............................................................................. 70
G category classification and subclassification ............................................................................. 70
E category classification and subclassification .............................................................................. 71
F category classification and subclassification .............................................................................. 71
G category classification and subclassification ............................................................................. 71
References .......................................................................................................................................................... 72
- xi –
Case Study 13: Krafla Geothermal Field ................................................................. 73
Project summary .............................................................................................................................................. 73
Quantification ................................................................................................................................................... 74
Product type ...................................................................................................................................................... 75
Reference Point ................................................................................................................................................ 75
UNFC-2009 classification ............................................................................................................................. 76
E category classification and subclassification .............................................................................. 76
F category classification and subclassification .............................................................................. 76
G category classification and subclassification ............................................................................. 76
UNFC-2009 Geothermal Energy Resources .......................................................................................... 77
References .......................................................................................................................................................... 77
Case Study 14: Krafla Geothermal Field – 50 MW Power Expansion .................. 78
Project summary .............................................................................................................................................. 78
Quantification ................................................................................................................................................... 79
Product type ...................................................................................................................................................... 80
Reference Point ................................................................................................................................................ 80
UNFC-2009 classification ............................................................................................................................. 81
E category classification and subclassification .............................................................................. 81
F category classification and subclassification .............................................................................. 81
G category classification and subclassification ............................................................................. 81
UNFC-2009 Geothermal Energy Resources .......................................................................................... 82
References .......................................................................................................................................................... 82
x

- x –
Case Study 11: Aggregation GSHP-Potential, North Rhine Westphalia............. 61
GSHP-Potential, North Rhine Westphalia, Germany. project summary .................................... 61
Quantification ................................................................................................................................................... 62
Product type ...................................................................................................................................................... 63
Reference Point ................................................................................................................................................ 63
UNFC-2009 classification and quantification ....................................................................................... 63
E category classification ......................................................................................................................... 64
F category classification and subclassification .............................................................................. 64
G category classification ........................................................................................................................ 64
Reference ............................................................................................................................................................ 64
Figure 1 - Points of reference for the assessment of GSHP projects in heating mode ....... 63
Case Study 12: Pauzhetsky geothermal field ........................................................ 65
Project summary .............................................................................................................................................. 65
Quantification ................................................................................................................................................... 66
Electricity ...................................................................................................................................................... 66
Heat ................................................................................................................................................................ 67
Product type ...................................................................................................................................................... 67
Reference Point ................................................................................................................................................ 67
Geothermal Energy Resources ................................................................................................................... 67
Electricity for single-flash power plant ............................................................................................. 67
Possible Electricity for binary power plant ..................................................................................... 67
Heat ................................................................................................................................................................ 67
UNFC-2009 classification ............................................................................................................................. 68
E category classification and subclassification .............................................................................. 68
F category classification and subclassification .............................................................................. 68
G category classification and subclassification ............................................................................. 69
E category classification and subclassification .............................................................................. 70
F category classification and subclassification .............................................................................. 70
G category classification and subclassification ............................................................................. 70
E category classification and subclassification .............................................................................. 71
F category classification and subclassification .............................................................................. 71
G category classification and subclassification ............................................................................. 71
References .......................................................................................................................................................... 72
- xi –
Case Study 13: Krafla Geothermal Field ................................................................. 73
Project summary .............................................................................................................................................. 73
Quantification ................................................................................................................................................... 74
Product type ...................................................................................................................................................... 75
Reference Point ................................................................................................................................................ 75
UNFC-2009 classification ............................................................................................................................. 76
E category classification and subclassification .............................................................................. 76
F category classification and subclassification .............................................................................. 76
G category classification and subclassification ............................................................................. 76
UNFC-2009 Geothermal Energy Resources .......................................................................................... 77
References .......................................................................................................................................................... 77
Case Study 14: Krafla Geothermal Field – 50 MW Power Expansion .................. 78
Project summary .............................................................................................................................................. 78
Quantification ................................................................................................................................................... 79
Product type ...................................................................................................................................................... 80
Reference Point ................................................................................................................................................ 80
UNFC-2009 classification ............................................................................................................................. 81
E category classification and subclassification .............................................................................. 81
F category classification and subclassification .............................................................................. 81
G category classification and subclassification ............................................................................. 81
UNFC-2009 Geothermal Energy Resources .......................................................................................... 82
References .......................................................................................................................................................... 82
xi

- 1 -
Introduction
The best way to understand the applicability of UNFC-20091 to Geothermal Energy
Resources via the Specifications for the Application of the United Nations Framework
Classification for Fossil Energy and Mineral Reserves and Resources 2009 (UNFC-2009) and
the Renewables Specifications is to actually test the classification of geothermal case
studies.
To this end, simplified application examples are included in this document, with the
goal of presenting different possible situations (e.g. mature versus immature projects,
country-wide versus operator perspective, deep geothermal systems versus ground source
heat pumps, individual project classification versus aggregation) and the logic for
classification of their associated Geothermal Energy Resources according to UNFC-2009.
The application examples focus on the classification of the estimated quantities,
rather than on their quantification, to complement UNFC-2009 as a classification
framework. When applicable, a reference to external literature is made, where the reader
can find more background information on the quantities being reported.
The application examples are not examples of formal reporting or disclosure. UNFC-
2009 is a voluntary system and does not impose any rules regarding which Categories of
resources should be disclosed. Unless mandated or restricted by a government or other
regulatory body, the disclosure of resource quantities under UNFC-2009 is entirely at the
discretion of the reporter. The same remains valid with regards to the application of UNFC-
2009 to Geothermal Energy Resources, independently of the particular Categories and Sub-
Categories showed in the application example presented here.
Given that no reporting template is currently offered (or enforced) as part of UNFC-
2009, the application examples presented here follow a generic format developed solely
for the purpose of consistent presentation to the public within this document, but with no
intention of making such format a mandatory template.
The application examples are offered as guidance and do not constitute rules of
application of UNFC-2009 to Geothermal Energy Resources.
1 The United Nations Framework Classification for Resources (UNFC) changed its name in April 2017. Prior to this,
UNFC was known as the United Nations Framework Classification for Fossil Energy and Mineral Reserves and
Resources 2009 (UNFC-2009). UNFC-2009 is used throughout this publication.

Introduction
The best way to understand the applicability of UNFC-20091to Geothermal Energy
Resources via the Specifications for the Application of the United Nations Framework
Classification for Fossil Energy and Mineral Reserves and Resources 2009 (UNFC-2009) and
the Renewables Specifications is to actually test the classification of geothermal case
studies.
To this end, simplified application examples are included in this document, with the
goal of presenting different possible situations (e.g. mature versus immature projects,
country-wide versus operator perspective, deep geothermal systems versus ground source
heat pumps, individual project classification versus aggregation) and the logic for
classification of their associated Geothermal Energy Resources according to UNFC-2009.
The application examples focus on the classification of the estimated quantities,
rather than on their quantification, to complement UNFC-2009 as a classification
framework. When applicable, a reference to external literature is made, where the reader
can find more background information on the quantities being reported.
The application examples are not examples of formal reporting or disclosure. UNFC-
2009 is a voluntary system and does not impose any rules regarding which Categories of
resources should be disclosed. Unless mandated or restricted by a government or other
regulatory body, the disclosure of resource quantities under UNFC-2009 is entirely at the
discretion of the reporter. The same remains valid with regards to the application of UNFC-
2009 to Geothermal Energy Resources, independently of the particular Categories and Sub-
Categories showed in the application example presented here.
Given that no reporting template is currently offered (or enforced) as part of UNFC-
2009, the application examples presented here follow a generic format developed solely
for the purpose of consistent presentation to the public within this document, but with no
intention of making such format a mandatory template.
The application examples are offered as guidance and do not constitute rules of
application of UNFC-2009 to Geothermal Energy Resources.
1The United Nations Framework Classification for Resources (UNFC) changed its name in April 2017. Prior to this,
UNFC was known as the United Nations Framework Classification for Fossil Energy and Mineral Reserves and
Resources 2009 (UNFC-2009). UNFC-2009 is used throughout this publication.
1

Case Study 1
Case Study 1: Ngatamariki
Project Location: Ngatamariki, New Zealand
Data date: 2011
Date of evaluation: May 2015
Quantification method: Simulation
Estimate type (deterministic/probabilistic): Deterministic
Project summary
Ngatamariki in New Zealand was first explored in the 1980s, then left idle until new
geophysical and geochemical surveys were done in 2004, and exploration drilling resumed
in 2008. The field is located in the Taupo Volcanic Zone of the North Island of New Zealand.
Resource assessment and the committal to development were based upon a simulation
model using natural state data and an interference test, but no production history. The field
and its exploration are described in subsequent publications by Boseley et al (2010 a, b)
and Grant & Bixley (2011).
There is an upflow at a depth of water at around 285°C, charging a liquid reservoir
of neutral chloride water with good permeability. There is a limited upflow out of the
reservoir top in the north-central part of the field, which discharges into a highly-permeable
groundwater aquifer. A critical feature of the field that is likely to impact on reservoir
management is communication between the deep high temperature reservoir and this
shallower aquifer. Geochemistry shows that geothermal fluid rises from the high
temperature reservoir into this aquifer where it mixes with cool groundwater, and then
flows northward, feeding surface activity.
This conceptual model, with interconnected deep reservoir and shallow aquifers, was
the basis of the simulation. The simulation used a single-porosity formulation. The model
has a deep high temperature recharge, and outflows (represented in the model as wells) at
the springs. Reservoir temperatures in all wells were matched. An interference test was
conducted among the deep wells by discharging three wells for varying periods and
monitoring pressure in well NM2. The model was then used to simulate the effects of
production and injection over 50 years. The pressure-temperature field was used as input
to compute subsidence. As there is no production history to provide calibration, the model
is not fully constrained and these simulated results could be significantly in error. However,
the model has highlighted the significant physical processes that might control long-term
reservoir behaviour. It identified the possibility of significant flow of cool fluids for the
shallow cool aquifers to the deep reservoir which constrainspossible development options,
and management plans emphasize pressure maintenance as important.
Forecast runs showed that the project could support an 82 MWe(net) development.
These results were then used in an application for support resource consents (New Zealand
environmental allocation rights to the resource), and the decision by the developer to
proceed. The proposed development required the drilling of a few additional wells, some
of which were drilled at wide diameter, to take advantage of the good permeability. There
would be a central group of production wells, with injection wells to the north and south
field margins.
The assessment was made as of the time of grant of resource consents and internal
financial approval. At this time the developer had secured land access, had drilled and
tested some production wells and one injection well, all with good results. There were plans
for a steamfield layout and power plant.
This assessment is made only on the basis of the information publicly available and
reported in the four references below.
2

Case Study 1
Ngatamariki project
Ngatamariki field area has been defined by a recent resistivity (MT) survey. By the
end of 2009, the following information was available: 6 drilled wells, of which 4 were
productive. One of those four producers was designated for injection. There were
completion tests on all wells and production tests of the producers, plus an interference
test. There was a reservoir simulation using this information. It produced a match to the
initial state P&T and the interference test. There is no production history and consequently
no history match.
Quantification
The simulation was a component of the consent application and modelled a
development of 82 MWe(net), for a period of 50 years, however the defined project was
for a development of 35 years. A power density estimate gives 86 MWefor 30 years and is
used to confirm G1.
The quantification estimate derives from the reservoir simulation, plus power density.
This is a deterministic assessment, with a single development plan tested. Only one
simulation scenario was presented. The simulation provides the best estimate (G1+G2).
Power density was then used as a second estimate: 500m circles were drawn around the
productive wells NM2, NM3, NM5and NM7,but not including NM6 which is to be used for
injection. A contour around these circles covers 4.3 km2. With a reservoir temperature of
275°C and good permeability, a power density of 20 MWe/km2is achieved in analogous
fields, giving a capacity of 86 MWefor 30 years, or 82 MWe for 31.5 years.
The economic assumptions are for a power station of existing standard geothermal
design, supplying power into New Zealand’s national grid. The developer is an electricity
generator and retailer with market access.
Product type
The product produced is electricity.
Reference Point
The reference point is at the station switchyard, where power is exported to the
national grid. Internal power use has already been subtracted.
Geothermal Energy Resources
Geothermal Energy Resources:
Low estimate: 80 PJ
Best estimate: 89 PJ
3

Case Study 1
UNFC-2009 classification
E category classification and subclassification
Category UNFC-2009 definition Reasoning f or classification
E1 Extraction and sale has been
confirmed to be economically
viable
Well testing and simulation have shown
sustained discharge is possible and flow
rates are economic.
The project has resource consents and
final financial approval in 2011.
Consents were issued for 35 years, so
that the project is defined for this period.
The classification of E1.1 applies to the
energy to be produced over this period
only.
Sub-category UNFC-2009 definition
E1.1 Extraction and sale is economic
on the basis of current market
conditions and realistic
assumptions of future market
conditions
Category UNFC-2009 definition Reasoning f or classification
E3 Extraction and sale is not
expected to become
economically viable in the
foreseeable future or evaluation
is at too early a stage to
determine economic viability.
The simulation showed production could
be sustained for 50 years. However, the
proposed development is for 35 years
only. The extra 15-year period would be a
separate project and would fall here.
F category classification and subclassification
Category UNFC-2009 definition Reasoning f or classification
F1 Feasibility of extraction by a
defined development project or
mining operation has been
confirmed
Exploration, well testing, simulation and
development plans are all complete.
Sub-category UNFC-2009 definition
F1.3 Sufficiently detailed studies have
been completed to demonstrate
the feasibility of extraction by
implementing a defined
development project or mining
operation.
F2 Feasibility of extraction by a
defined development project or
mining operation is subject to
further evaluation.
There are preliminary studies (i.e. the
simulation) indicating the feasibility of
continuing production beyond 35 years,
and a project to assess this resource
would lie here.
4

Case Study 1
G category classification and subclassification
Category UNFC-2009 def inition Reasoning f or classification
G1
*
Quantities associated with a
known deposit that can be
estimated with a high level of
confidence.
The combination of the power density
method and the simulation give high
confidence on the estimate.
G2
*
Quantities associated with a
known deposit that can be
estimated with a moderate level
of confidence.
Wells have been tested and a simulation
completed based upon natural state and
interference information. There is no
production history and consequently no
match to that history. Because of the lack
of history confidence is moderate.
*
Note that the classification as G1 and G2 was based on an evaluation of public domain information only
and a final classification, including the provision of a G3 estimate, would be required to provide an indication
of the full range of uncertainty in the estimate.
UNFC-2009 Geothermal Energy Resources
Classification Energy Quantity Supplemental information
UNFC-2009
Class
Use energy units
E1.1; F1.3; G1 80PJ
*
(2 500#MWeyr) 82 MWefor 31.5 years;
E1.1; F1.3; G2 9PJ
*
(300* MWeyr) 82 MWefor 3.5 years; incremental to G1,
with G1+G2 representing the best
estimate.
*
Rounded to one significant figure.
#
Rounded to two significant figures.
References
Boseley, C., Cumming, W., Urzúa-Monsalve, L., Powell, T., & Grant, M., 2010a “A resource
conceptual model for the Ngatamariki geothermal field based on recent exploration well
drilling and 3D MT resistivity imaging”, World Geothermal Congress
Boseley, C., Grant, M. A., Burnell, J. & Ricketts, B. 2010b. Ngatamariki Project Update.
Transactions, Geothermal Resources Council, v34, pp. 177-182
Grant, M.A., & Bixley, P.F., 2011 “Geothermal Reservoir Engineering, 2nd Edition” Academic
Press, New York.
http://www.voxy.co.nz/national/ngatamariki-consents-granted-ew-and-taupo-dc/5/48346
5

Case Study 2
Case Study 2: Habanero
Project Location: Innamincka, South Australia, Australia
Data date: 30 June 2014
Date of evaluation: November 2016
Quantification method: Thermodynamic Simulation
Estimate type (deterministic/probabilistic): Deterministic scenarios
Project Summary
Habanero is an Enhanced Geothermal System (EGS) resource located in hot granite
near the town of Innamincka in northeast South Australia. The Potential Geothermal Energy
Source was first identified by a petroleum exploration well which encountered hot granite
at a depth of 3,748 m. Analysis of regional gravity data showed that the granite batholith
extends over approximately 1,000 km2. Geodynamics Limited acquired geothermal
exploration licences covering 991 km2of the gravity anomaly and these have subsequently
been converted into geothermal retention licences. The company has drilled four full-sized
geothermal wells into the granite at Habanero, 10 km south of Innamincka. Two further
full-sized exploration wells have also been drilled into the granite at Jolokia, 10 km west of
Habanero, and at Savina, 10 km southwest of Jolokia. All six of these deep wells have shown
signs of having encountered pre-existing faults within the granite.
The four wells at Habanero have all shown various indications of fracturing or faulting
within the granite. However, the vast majority of fluid flow, either into or out of the granite,
occurs over a short section of intense fracturing now known as the Habanero Fault. This
structure has been penetrated by all four Habanero wells and is interpreted to be a thrust
fault, dipping at approximately 10° to the west-southwest.
Stimulations of the Habanero Fault have been conducted on three wells (Habanero
1, 3 and 4), injecting large volumes of water under pressure to induce shearing of the fault.
After the latest stimulation of Habanero 4, the cloud of micro-seismic events, which is
believed to indicate the extent of stimulation of the fault, extends over 4 km2(Figure 1).
Two closed-loop production and injection tests have been conducted at Habanero;
the first between Habanero 1 and Habanero 3, and the second between Habanero 1 and
Habanero 4. In both cases, the circulation rate has been restricted by the poor injectivity of
Habanero 1, which was badly damaged by mud losses into the fault during drilling. Even
so, the Habanero 1 –4 closed-loop test achieved a circulation rate of 19 kg/s and a
production temperature of 215°C, with both rate and temperature still increasing steadily
when the test ended.
6

Case Study 2
Figure 1
Induced Micro-Seismicity at Habanero
*
*
Top - Plan view of hypocentre locations of seismicity from stimulation in Habanero 4. Each event is
displayed by a globe, scaled to the event magnitude. Colour coding denotes occurrence time
according to legend. Previous seismic activity is indicated by grey dots.
Bottom-Hypocentre locations in side-view looking from ESE. Events are displayed as dots with colour
coding denoting the occurrence time.
Despite the seismicity induced during stimulation, both closed-loop tests have
exhibited little or no seismicity during closed-loop operations. Tracer tests were conducted
during both closed-loop tests and these results were used to calibrate a thermodynamic
simulation model for field development planning. Stibnite scaling of the heat exchangers
has been encountered, but this has been managed by periodic flushing of the equipment
with a hot caustic soda solution. Corrosion tests were undertaken as part of the Habanero
1 –4 closed-loop and have been used to select suitable materials for the wells and surface
equipment.
Habanero Project
In light of the technical success of the Habanero 1 –4 closed-loop test, Geodynamics
has investigated the feasibility of a small-scale EGS project supplying heat to a local
consumer near Innamincka. The only potential customers currently in the region are gas
producers who require significant amounts of heat for gas processing.
A six-well geothermal project, comprising three injectors and three producers drilled
at 1,200 m spacing, has been studied in depth and a draft Field Development Plan has been
7

Case Study 2
prepared. Based upon injectivity and productivity tests done on the undamaged wells at
Habanero, it is expected that each well will be able to inject or produce between 25 and 45
kg/s of brine with acceptable pump differentials of less than 100 bar. Thermodynamic
simulation of Habanero has shown that, even with wells spaced at 1,200 m, production
temperatures will decline by about 30°C over the planned 15-year project life. Even so, the
average production temperature is expected to be around 214°C. The re-injection
temperature has been set at 80°C to avoid any silica scaling.
Quantification
The resource estimate has been prepared using a scenario-based approach linked to
outputs from the thermodynamic model. Three scenarios have been considered based
upon production and injection rates of 25, 35 and 45 kg/s with capacity factors of 94%, 96%
and 98%, respectively. The three scenarios are considered to represent low, best and high
estimates of the Geothermal Energy Resources recoverable with the six-well development
project.
Geothermal Energy Product
Heat for use in gas processing.
Reference Point
It is assumed that there is negligible heat loss between the production wellheads and
the consumer, so the Reference Point is the inlet to the consumer’s gas plant.
Geothermal Energy Resources
Geothermal Energy Resources:
•Low estimate: 19 PJth (610 MW.yr)
•Best Estimate: 28 PJth (880 MW.yr)
•High Estimate: 36 PJth (1,150 MW.yr)
UNFC-2009 classification
E category
There has been an active exploration for gas in the sediments above and around
Habanero. There is increasing gas demand from several new LNG plants, so a successful
exploration program could lead to the construction of a new plant to treat this gas. Such a
gas plant is likely to require heat to process the gas. Geodynamics has successfully drilled
six full-sized, deep geothermal wells and constructed and operated a pilot power station,
demonstrating their ability to manage construction risks, environmental impacts and
societal issues. However, it is currently considered that there are not reasonable prospects
for economic extraction and sale of heat within the foreseeable future. Consequently, the
project is categorized as E3.3.
8

Case Study 2
F category
A Field Development Plan has been prepared for Habanero and all the necessary
technology for this development already exists. However, the plan does propose that the
last 100 metres of each well should be drilled with coil tubing. Coil tubing drilling is not
new, but doing this in granite at such depths, temperatures and pressures have not been
tried before. Therefore, these geothermal energy resources should be categorized as F2
until the coil tubing drilling has been demonstrated.
Recently Geodynamics has abandoned all the Habanero wells and signalled its
intention to withdraw from the geothermal energy business. Since there are no current
plans to develop or acquire additional data at this time, the project is considered to be in
sub-category F2.3.
G category
Four wells have been drilled at Habanero, all of which have encountered the
Habanero Fault. The fault has been successfully stimulated from three wells and two closed-
loop production and injection tests have been conducted. Therefore the Habanero
geothermal energy source can be considered “known” and all Geothermal Energy
Resources should be reported in categories G1, G2 and G3.
UNFC-2009 Geothermal Energy Resources*
Classification Energy Quantity Supplemental information
E3.3; F2.3; G1 19 PJth (610 MW.yr) Low estimate of Geothermal Energy
Resources
E3.3; F2.3; G2 9 PJth (270 MW.yr) Increment between Best and Low estimates
E3.3; F2.3; G3 8 PJth (270 MW.yr) Increment between High and Best
estimates.
*
Energy Quantities are subject to rounding.
References
Geodynamics Limited, 2014; “Habanero Geothermal Project Field Development Plan”. Web
site, www.geodynamics.com.au.
Hogarth, R. & Bour, D., 2015; “Flow Performance of the Habanero EGS Closed Loop”.
Proceedings, World Geothermal Congress 2015.
McMahon, A. & Baisch, S., 2015; “Seismicity Associated with the Stimulation of the
Enhanced Geothermal System at Habanero, Australia”. Proceedings, World Geothermal
Congress 2015.
9

Case Study 3
Case Study 3: Insheim
Project Location: Insheim, Germany
Data date: 2015
Date of evaluation: January 2016
Quantification method: Extrapolation of production history
Estimate type (deterministic/probabilistic): Deterministic scenarios
Project Summary
The Insheim Geothermal Project is located on the western rim of the Upper Rhine
Valley in Germany. At the time of reporting, the plant is one of four actually producing
geothermal power plants in the Upper Rhine Valley.
Insheim stemmed from an understanding built at the European Enhanced
Geothermal Systems (EGS) research project at Soultz-sous-Forêts (France; Garnish
et al.
,
1994; Baria
et al.
, 1995) of the geomechanical behaviour of large deep natural faults. This
project exploits naturally permeable faults with the relatively little requirement for hydraulic
stimulation. There are one production well and one injection well to depths of about
3,800 metres. Subsurface fluid flow takes place through north–south striking normal faults
in the Buntsandstein formation and granitic basement rock. It is a closed loop system that
does not require makeup water and does not discharge any harmful products into the
atmosphere.
Geological information at Insheim was obtained predominantly from several
boreholes and seismic reflection surveys carried out by the oil industry in the past and
additional general geological knowledge.
During the build-up and testing phase of the development, it became clear that the
injection well was not sufficiently permeable. Hydraulic stimulation improved the situation,
but not enough. As a consequence, a sidetrack starting at 2,500 m depth was drilled from
the injection well and injection now divides along both completions. This greatly improved
the injectivity and circulation rates up to 85 L/s are now sustainable with acceptable pump
loads.
The Insheim project has been generating power continuously since 2012. The
business plan called for a gradual increase in flow rate from 65 L/s in the first year to 75 L/s
in the second year and 85 L/s from the third year onwards (Baumgartner
et al
., 2013).
However, regulatory approvals currently restrict circulation rates to 65 L/s as a precaution
against induced seismicity. There is a reasonable expectation that the limit could be raised
to the planned 85 L/s in the future. The plant is designed and built to sustain 85 L/s.
In the Insheim area, there was some public concern about acceptance of induced
seismicity and the potential for radioactive scaling material. The seismicity aspect was
addressed by the installation of a permanent seismic monitoring system and the
establishment of acceptance and reaction scheme mutually agreed by all parties concerned.
As a part of this condition, the circulation flow-rate is restricted to ~65 L/s. Regarding the
potential for scaling from radioactive material, techniques are used to reduce scaling by
keeping any radioactive material in solution by the use of inhibitors, controlling circulation
pressures and pH. Any potential radioactive substances will be handled according to
appropriate regulations.
Construction of a district heating system that makes use of the rejected heat from
the power plant is in the planning phase at the time of reporting. A heat exchanger is in
place on the power plant but a distribution system is yet to be constructed.
10

Case Study 3
Insheim project
The Insheim binary geothermal power plant has operated continuously since 2012
and has approximately 26 years of production left of its nominal 30-year design life. Insheim
has one production and one injection well, both about 3,800 m deep. The wellhead
temperature is about 165°C. The working fluid is isopentane. A line-shaft pump is used for
production. The nominal installed capacity of the binary generator power of the plant is 4.8
MWeand it has operated an average of 8,000 h/yr over the past four years. Internal
operating power (that is, parasitic load) is supplied from external mains, with gross electrical
output available for sale under Germany’s feed-in tariff laws.
At the time of reporting, regulatory requirements limit circulation rate to 65 L/s as a
precaution against induced seismicity. Before this restriction was imposed, the system
demonstrated sustainable flow rates of 85 L/s. There is a reasonable expectation that the
regulatory limit will be increased to 85 L/s at some time in the future.
Numerical modelling has provided confidence that circulation of fluid between the
injection and production wells is via a deep and hot circuit along the sub-vertical normal fault,
and that no appreciable temperature decline is expected over the remaining 26 years of the
project lifetime. Similarly, no appreciable decrease in flow rate is expected from the current
65 L/s, but there is a downside risk that the maximum 85 L/s flow might decrease over time.
At the time of reporting, a distribution system is in the planning phase to sell heat
from the power plant’s rejected fluid into a local district heating market of 600–800
households to service seasonal demand. A study of the feasibility of a district heating
system has shown it to be financially attractive (Heck
et al.
, 2009). The heat exchangers are
already installed. The system will represent a cascaded use of the Geothermal Energy
Resource, taking the geothermal fluid rejected from the power plant and reducing its
temperature further without reducing the electrical power output. An average of 31% of
the 76,500 MW.hrth of heat annually rejected by the plant (operating at its capacity of 85 L/s)
is forecast to be utilized by the district heating system (Heck
et al.
, 2009). The total annual
heat demand is forecast to be 23,700 MW.hrth. However, demand is concentrated in winter,
when peak demand could reach 96% of the maximum geothermal heating power. At the
lower 65 L/s flow rate, up to 41% of available heat could be utilized.
Relevant project parameters are as follows:
•Wellhead temperature: 165°C
•Rejection temperature from power plant: 70°C
•Maximum flow rate: 85 L/s
•Current regulated flow rate: 65 L/s
•Maximum thermal power supplied to the power plant: 34 MWth
•Current regulated thermal power supplied to the power plant: 26 MWth
•Maximum electrical power at reference point: 4.8 MWe
•Current regulated electrical power at reference point: 3.7 MWe
•Average yearly production hours for electricity 2012–2015: 8,000 hr
•Input temperature for district heating: 70°C
•Rejection temperature from district heating: 45°C
•Input flow for district heating: 65 L/s
•Expected utilization factor: 41%
•Remaining project lifetime: 26 years.
11

Case Study 3
Quantification
Electricity
This potential additional recoverable energy is calculated and classified separately.
There is uncertainty about whether 85 L/s can be sustained over the plant lifetime.
Calculations assume a possible 10% reduction in maximum flow rate as a low-side estimate.
All assumptions are summarized below:
•Power plant inlet / outlet temperature: 165°C / 70°C
•Operating hours (low / medium / high): 7,600 / 8,000 / 8,400
hours per year
•Assumed conversion efficiency heat-to-electricity: 14.2%
Remaining lifetime is 26 years. The Insheim plant is rated to 4.8 MWemaximum gross
output. Power to run the plant equipment, and particularly the line-shaft pump, is sourced
from the grid, so all the gross power from the plant is exported. The maximum gross output
is based on a flow rate of 85 L/s. Production is currently limited by regulation to 65 L/s.
There is a reasonable expectation that the regulation will be lifted to 85 L/s at some time
in the future.
Quantification of electrical energy for the remaining project life is based on
extrapolation of observed generation history over the first four years of operation. The
mean expectation is that production will continue at 65 L/s and an average of 8,000 hours
per year (91% availability) for the remainder of the project. There is a downside risk that
plant availability will drop over time for operational reasons, resulting in declining output.
The low side estimate is based on an average reduction to 87% availability (7,600 hours per
year) from the historical average case over the remaining plant life. There is upside potential
to increase the average availability of the plant over time as the plant management
becomes more efficient. The upside potential is based on achieving 96% availability (8,400
hours per year).
There is a reasonable expectation that regulations will be amended in the foreseeable
future to allow production rate to increase to 85 L/s for the remainder of the project, with
all other parameters:
•Flow rate: 65 L/s
•Possible future flow rates (low / medium / high): 76.5 / 85 / 85 L/s.
Heat
Quantification of recoverable heat is based on modelled heat demand for the district
heating system. The demand is expected to average 23,700 MW.hrth per year (Heck
et al.
,
2009). Upside and downside estimates are based on ±10% uncertainty in the expected
mean.
•Heating system inlet / outlet temperature: 70°C / 45°C
•Annual heat demand (low / medium / high): 21,300 /23,700 /26,100 MW.hrth
•Remaining lifetime: 26 years.
12

Case Study 3
Product type
There are two Energy Products: electricity and heat.
Reference Point
The reference point for electricity is the station switchyard, where gross power is
exported into the national grid. Internal power requirements are purchased from the grid.
The reference point for heat is the metering point for the heat distribution system.
Geothermal Energy Resources
Electricity
Electricity:
•Low estimate: 2.63 PJe(3.7 MWex 7,600 hrs x 26 years)
•Best estimate: 2.77 PJe(3.7 MWex 8,000 hrs x 26 years)
•High estimate 2.91 PJe(3.7 MWex 8,400 hrs x 26 years)
Possible Additional Electricity for 85 L/s flow
Possible Additional Electricity for 85 L/s flow:
•Low estimate: 0.43 PJe(0.6 MWex 7,600 hrs x 26 years)
•Best estimate: 0.82 PJe(1.1 MWex 8,000 hrs x 26 years)
•High estimate 0.86 PJe(1.1 MWex 8,400 hrs x 26 years)
Heat
Heat:
•Low estimate: 1.99 PJth (21,300 MW.hrth x 26 yrs)
•Best estimate: 2.22 PJth (23,700 MW.hrth x 26 yrs)
•High estimate: 2.44 PJth (26,100 MW.hrth x 26 yrs)
UNFC-2009 classification
Classification Energy Quantity Supplemental information
UNFC-2009
Class
Commodity:
Electricity
The Insheim plant has generated electricity continuously
since 2012. Expected remaining lifetime: 26 years.
E1.1;F1.1; G1 2.63 PJeConservative estimate based on 5% reduction in
availability.
E1.1;F1.1; G2 0.14 PJeIncremental energy based on continued output at current
rates and availability for the remaining project life.
E1.1;F1.1; G3 0.14 PJeIncremental energy based on 5% increase in availability.
13

Case Study 3
E category classification and subclassification
Category UNFC-2009 definition Reasoning f or classification
E1 Extraction and sale is economic on the basis
of current market conditions and realistic
assumptions of future market conditions.
Plant is commercially producing
now through a market-wide
German feed-in tariff scheme
guaranteed for the life of the plant.
Sub-category UNFC-2009 definition
E1.1 Extraction and sale is economic on the basis
of current market conditions and realistic
assumptions of future market conditions.
F category classification and subclassification
Category UNFC-2009 definition Reasoning f or classification
F1 Feasibility of extraction by a defined
development project or mining operation
has been confirmed.
Energy is being successfully
extracted and converted to
electricity at the required
commercial rate.
Sub-category UNFC-2009 definition
F1.1 Extraction is currently taking place.
G category classification and subclassification
Category UNFC-2009 definition Reasoning for classification
G1 Quantities associated with a
known deposit that can be
estimated with a high level of
confidence.
Two wells have been drilled at Insheim. The
injection well has been stimulated.
Production and injection tests have been
conducted. The system is currently
producing. Thus, the Insheim Geothermal
Energy Source can be considered “known”
and all resources are classified as G1, G2
and G3.
While modelling has given a high level of
confidence that temperature and flow will
be sustained over the life of the plant, there
is uncertainty in the availability of the plant.
It may decrease due to greater than
expected maintenance requirements, or
increase due to achieved efficiencies.
G2 Quantities associated with a
known deposit that can be
estimated with a moderate level
of confidence.
G3 Quantities associated with a
known deposit that can be
estimated with a low level of
confidence.
14

Case Study 3
Classification Energy Quantity Supplemental information
UNFC-2009
Class
Commodity:
Electricity
The Insheim plant could generate additional electricity if
Regulators allow flow rate to increase to 85 L/s.
E2;F1.3; G1 0.43 PJeConservative estimate based on 5% reduction in availability
and 10% reduction in flow.
E2;F1.3; G2 0.39 PJeIncremental energy based on continued output at current
rates and availability for the remaining project life.
E2;F1.3; G3 0.04 PJeIncremental energy based on 5% increase in availability.
E category classification and subclassification
Category UNFC-2009 definition Reasoning for classification
E2 Extraction and sale is expected
to become economically viable
in the foreseeable future.
There is a reasonable likelihood that
Regulators will raise the 65 L/s flow limit to
85 L/s in the foreseeable future.
F category classification and subclassification
Category UNFC-2009 definition Reasoning for classification
F1 Feasibility of extraction by a
defined development project or
mining operation has been
confirmed
The plant has been designed to
accommodate 85 L/s flow. The extra energy
can be recovered and converted using the
existing plant.
Sub-category UNFC-2009 definition
F1.3 Sufficiently detailed studies have
been completed to demonstrate
the feasibility of extraction by
implementing a defined
development project or mining
operation.
15

Case Study 3
G category classification and subclassification
Category UNFC-2009 definition Reasoning for classification
G1 Quantities associated with a
known deposit that can be
estimated with a high level of
confidence.
Two wells have been drilled at Insheim. The
injection well has been stimulated.
Production and injection tests have been
conducted. The system is currently
producing. Thus, the Insheim Geothermal
Energy Source can be considered “known”
and all resources are classified as G1, G2
and G3.
While modelling has given a high level of
confidence that temperature will be
sustained over the life of the plant,
maximum flow might decrease by as much
as 10% from 85 L/s. There is also
uncertainty in the availability of the plant. It
may decrease due to greater than expected
maintenance requirements, or increase due
to achieved efficiencies.
G2 Quantities associated with a
known deposit that can be
estimated with a moderate level
of confidence.
G3 Quantities associated with a
known deposit that can be
estimated with a low level of
confidence.
Classification Energy Quantity Supplemental information
UNFC-2009
Class
Commodity:
Heat
The construction of a district heating network in Insheim is
currently in the planning phase. A heat exchanger is already
in place, with work proceeding on a distribution network to
supply approximately 600 to 800 households.
E1.1;F1.3; G1 1.99 PJth Conservative estimate based on heat demand 10% lower
than predicted over the 26 year project life.
E1.1;F1.3; G2 0.23 PJth Incremental energy based on predicted demand for 26 year
project life.
E1.1;F1.3; G3 0.22 PJth Incremental energy based on heat demand 10% higher than
predicted over the 26 year project life.
16

Case Study 3
E category classification and subclassification
Category UNFC-2009 definition Reasoning f or classification
E1 Extraction and sale is economic on
the basis of current market
conditions and realistic assumptions
of future market conditions. There
are reasonable expectations that all
approvals/contracts will be obtained
within a reasonable timeframe.
The local market for heat is well
understood and provides a firm
commercial basis for developing the
district heating system. There are
reasonable expectations that all
approvals/contracts will be obtained
within a reasonable timeframe.
Sub-category UNFC-2009 definition
E1.1 Extraction and sale is economic on
the basis of current market
conditions and realistic
assumptions of future market
conditions.
F category classification and subclassification
Category UNFC-2009 definition Reasoning f or classification
F1 Feasibility of extraction by a
defined development project has
been confirmed.
A district heating network at Insheim is
currently in the planning phase. The
technology has already been
demonstrated at analogous projects
within the Rhine Graben.
Sub-category UNFC-2009 definition
F1.3 Sufficiently detailed studies have
been completed to demonstrate
the feasibility of extraction by
implementing a defined
development project.
G category classification and subclassification
Category UNFC-2009 definition Reasoning f or classification
G1 Quantities associated with a
known deposit that can be
estimated with a high level of
confidence.
The power plant at Insheim is currently
rejects sufficient heat to meet the heating
demand of Insheim. An increase in flow
to 85 L/s would provide even more
surplus heat. Uncertainty relates to the
predicted demand.
G2 Quantities associated with a
known deposit that can be
estimated with a moderate level
of confidence.
G3 Quantities associated with a
known deposit that can be
estimated with a low level of
confidence.
17

Case Study 3
References
Garnish, J., Baria, R., Baumgärtner, J., Gérard, A., (1994). The European Hot Dry Rock
Programme 1994-1995,
GRC Trans
.
Baria R, Garnish J, Baumgartner J, Gerard A, Jung R, (1995). Recent development in the
European HDR research programme at Soultz-Sous-Foret (France). Proceeding of the World
Geothermal Congress, Florence, Italy, International Geothermal Association, Vol. 4, 2631-
2637, ISBN 0-473-03123-X.
Baumgärtner, J., Teza, D. and Wahl, G. (2013). Gewinnung geothermischer Energie durch
Entwicklung und Zirkulation eines Störungssystems im Kristallin und deren mikroseismische
Überwachung am Beispiel des Geothermieprojektes Insheim (Extraction of geothermal
energy through the development and circulation of controlled systems in the crystalline
basement and their microseismic monitoring, using the example of the geothermal project
Insheim). Final report to Bestec GmbH. Accessed online 4 Feb 2016: http://edok01.tib.uni-
hannover.de/edoks/e01fb14/777426781.pdf .
Baumgärtner, J. and Lerch, C. (2013): Geothermal 2.0: The Insheim Geothermal Power Plant.
The second generation of geothermal power plants in the Upper Rhine Graben. Third
European Geothermal Review. Geothermal Energy for Power Production. June 24-26, 2013,
Mainz, Germany.
Baumgärtner, J., Hettkamp, T., Teza, D., Kölbel, T., Mergner, H., Schlagermann, P. and Lerch,
C. (2013): Betriebserfahrungen mit den Geothermiekraftwerken Landau, Insheim und
Bruchsal. bbr Fachmagazin für Brunnen-und Leitungsbau.
Gérard, A., Baumgärtner, J., Baria, R., 1997. An attempt towards a conceptual model derived
from 1993-1996 hydraulic operations at Soultz. In:
Proceedings of NEDO International
Geothermal Symposium
, Sendai, 2, pp. 329-341.
Heck, P., Anton, T., Oßwald, D., Müller, J. and Speicher, M. (2009). Entwicklung der
Gemeinden Insheim und Rohrbach zu „Geowärmedörfern“(Development of Local Insheim
and Rohrbach to "Geothermal Energy villages"). Institute for Applied Material Flow
Management Research Report. Accessed online 4 Feb 2016: 00ea http://www.wald-
rlp.de/index.php?eID=tx_nawsecuredl&u=0&g=0&t=1454652674&hash=bed002693004c
f203761dfc53e7679858a461768&file=fileadmin/website/fawfseiten/projekte/downloads/I
nsheim.pdf
Weblink: http://www.geothermie-insheim.de
18

Case Study 4
Case Study 4: Rotliegend-3 Geothermal Project
Project Location: the Netherlands
Data date: 2010
Date of evaluation: May 2015
Quantification method: Stochastic calculation based on uncertainty
of reservoir parameters and a standard doublet/duplex configuration
Estimate type (deterministic/probabilistic): Probabilistic
Project summary
The Rotliegend-3 geothermal exploration project was started up in 2010. The project
is aiming to provide the heat base load to greenhouses to replace a significant heat input
from gas fired heat and power systems. Based on the regional geothermal potential
mapping [2] this area was chosen for further evaluation. The latter evaluation comprised a
detailed subsurface evaluation of a selected subset of the Dutch public subsurface dataset.
This data set comprised five offset wells, a 3D-seismic dataset and a 2D seismic dataset.
Based on an anticipated fit for purpose well configuration and pressure difference
over the production and injection intervals an indicative geothermal power estimate (MW)
in terms of P90, P50 and P10 were calculated using DoubletCalc [1]. In the Netherlands, the
default production licence period is 35 years. The anticipated load hours of the doublet are
7000 hours a year. Preliminary calculations suggest that after 55 years thermal
breakthrough will result in uneconomic performance and there is reasonable confidence
that the production licence will be extended to meet the technical lifetime of the system
At the status date of this evaluation, the exploration licence was in place, there was
a high degree of confidence that all licences for drilling the exploration well would be in
place in the foreseeable future and that if successful the production licence would be
granted. Financial close awaits the granting the feed-in tariff [3] grant and the guarantee
fund grant [4].
Quantification
The quantification estimate is derived from a standardized indicative geothermal
power calculation using the software program DoubletCalc which is a prerequisite for
entering government financial support schemes. This is a stochastic assessment based on
the uncertainty of the geologic parameters: gross thickness, net to gross, permeability,
depth and salinity of the formation waters (Figure 1). Technical and installation design and
operational parameters refer to standard practices in the Netherlands.
19

Case Study 4
Figure 1
Input for indicative Geothermal power calculation for the project
20

Case Study 4
Figure 2
Probabilistic calculation results
*
* The economic assumptions are for heating greenhouses. Delivery of heat is secured because the operator
of the project is the user of the delivered heat.
The product/commodity produced is heat.
Reference Point
The reference point is at “sweet side” or secondary loop of the heat exchanger where
the heat produced is measured according to specifications detailed in the feed-in tariff
documents. Internal power use has already been subtracted.
21

Case Study 4
Geothermal Energy Resources
Geothermal Energy Resources:
•Low estimate (P90): 8.3 PJth (330 MW yr); 6 MWth for 55 years, with 7,000
load hrs/yr
•Best Estimate (P50): 11.1 PJth (440 MW yr); 8 MWth for 55 years, with 7,000
load hrs/yr
•High Estimate (P10): 15.2 PJth (605 MW yr); 11 MWth for 55 years, with
7,000 load hrs/yr
UNFC-2009 classification
E category classification and subclassification
Category UNFC-2009 definition Reasoning f or classification
E2 Extraction and sale is
expected to become
economically viable in the
foreseeable future.
Economy
Economic evaluation of the indicative
geothermal power estimates proved the P90
geothermal power estimate to be economic.
Financing
Application of the government schemes
“feed-in tariff” and “guarantee fund” have
been submitted and are expected to be
granted. Bank loans are in place under the
condition of positive response on the
government financial support schemes.
Loans by the province are granted.
Licensing
The required exploration licence is in place.
Technical evaluation of the drilling activity
has yet to be audited by the mining
authority. If the exploration well testing
provides confidence in economic
development granting of a production
licence is regarded as certain.
Societal issues
No adverse activity from the general public
stalling or terminating the granting of the
necessary licences is foreseen as geothermal
energy for heating greenhouses is regarded
as environmentally friendly and the
preferred option to transfer to green energy
in heating greenhouses and operational
safe by the public.
Sub-category UNFC-2009 definition
Not applicable
22

Case Study 4
F category classification and subclassification
Category UNFC-2009 def inition Reasoning for classification
F3 Feasibility of extraction by a
defined development project
or mining operation cannot
be evaluated due to limited
technical data.
Geo-science studies
Detailed subsurface studies using
appropriate well data and 2D& 3D seismic
surveys were used to adequately assess the
geothermal potential. The reports resulted
in an assessment of the geothermal
potential and are the basis for the well-
design and drilling plan. Drilling plan report
has been filed at the relevant authority.
Technical studies
Preliminary well design is reported.
Preliminary surface installation design is
reported as well. These reports were input
for the economic assessment. All identified
technical issues are anticipated to be
solvable with standard industry practices.
Sub-category UNFC-2009 definition
F3.1 Where site-specific geological
studies and exploration
activities have identified the
potential for an individual
deposit with sufficient
confidence to warrant drilling
or testing that is designed to
confirm the existence of that
deposit in such form, quality
and quantity that the
feasibility of extraction can be
evaluated.
G category classification and subclassification
Category UNFC-2009 def inition Reasoning for classification
G4 Estimated quantities
associated with a potential
deposit, based primarily on
indirect evidence.
The Geothermal project is regarded as an
exploration project because:
No wells have been drilled in the
exploration licence.
The nearest off-set well is some 20 km
away. This well gives appreciable confidence
on the presence of the aquifer, but not on
its deliverability, as the “correlation length”
of the relevant reservoir properties is
significant lower.
Sub-category UNFC-2009 definition
G4.1 Low estimate of the
quantities;
G4.2 Incremental amount to G4.1
such that
G4.1+G4.2
equates
to a best estimate of the
quantities;
G4.3 Incremental amount to
G4.1+G4.2 such that
G4.1+G4.2+G4.3
equates to a
high estimate of the
quantities.
23

Case Study 4
UNFC-2009 classification and quantification
Classification Energy Quantity Supplemental information
UNFC-2009
Class
Energy units used: Petajoules
(PJ) = (x1015J)
E2; F3.1; G4.1 8.3 PJ It is the P90 estimate.
E2; F3.1; G4.2 2.8 PJ Increment between Best and Low
estimates. The P50-P90 estimate (11.1-
8.3PJ). As such the G4.2 is incremental to
G4.1.
E2; F3.1; G4.3 4.2 PJ Increment between High and Best
estimates. The P10-P50 estimate (15.2-
11.1PJ).
Disclaimer
The case study presented with facts and figures is loosely based on the
Koekoekspolder project in the Netherlands. Data and information is available in the public
domain through the RVO website2.[5]
References
[1] DoubletCalc, http://nlog.nl/nl/geothermalEnergy/tools.html
[2] ThermoGis, www.thermoGis.nl
[3] Application documents Guarantee fund: www.RVO.nl
[4] Feed in Tariff information, www.rvo.nl/
[5] S. Henares, M. R. Bloemsma, M. E. Donselaar, H. F. Mijnlieff, A.E. Redjosentono, H. G.
Veldkamp, G. J. Weltje. 2014, The role of detrital anhydrite in diagenesis of Aeolian
sandstones (Upper Rotliegend, The Netherlands), Implications for reservoir-quality.
2http://www.rvo.nl/subsidies-regelingen/projecten/eerste-aardwarmtecluster-koekoekspolder
24

Case Study 5
Case Study 5: Dutch Rotliegend Play Area –
Nationwide
Project Location: the Netherlands, Dutch Rotliegend reservoir
Data date: 2014
Date of evaluation: May 2015
Quantification method: Stochastic calculation based on the uncertainty of reservoir
parameters and a standard doublet/duplex configuration
Estimate type (deterministic/probabilistic): Probabilistic
Project summary
The Permian Rotliegendes is a well-known and prolific gas reservoir in the
Netherlands. For gas E&P the Rotliegend reservoir has been drilled over a thousand times.
The extent and quality of the aquifer/reservoir are relatively well known. In the last decade,
especially Dutch greenhouse owners showed interest to convert to geothermal instead of
heating their greenhouses with natural gas. The Rotliegend geothermal play area has been
mapped using the public domain well and seismic data (van Wees et al. 2012, ThermoGIS).
Figure 1 indicates the availability of data for the reservoir evaluation. Within the Rotliegend
geothermal play area, several geothermal projects are realized and planned (Figure 1).
At present, just under seventy geothermal licences are in force (MEA 2015). Within
three of these licences, the Rotliegend reservoir was drilled successfully resulting in four
producing geothermal doublets. Some six of these seventy licences are still in the
exploration phase targeting the Rotliegend. Eleven exploration licences targeting the
Rotliegend were expired or withdrawn.
For all the exploration licences applied and granted, the Government of the
Netherlands has one or more indicative power estimates of the proposed project to be
executed in the licence. For the geothermal systems in the production phase, the Dutch
government receives production data. The geothermal operator also has to file their
production plan including the (future) production profile and/or installed power estimate
plus the anticipated full load hours per year over the project lifetime. Production licences
are in general granted for 35 years unless modelling shows that the cold waterfront passes
beyond the licence boundary earlier. When operations proceed satisfactorily from an
operational and HSE point of view, it is assumed there will be no obstructions for licence
term extension.
The various defined projects can be classified according to UNFC-2009 and the
indicative power estimates recalculated to energy produced within the project life.
25

Case Study 5
Figure 1
Map of data for evaluation of the Rotliegend aquifer*
*
Coloured areas give the outline of the presence of the Rotliegend aquifer. When the color is blue
there is public 3D-seismic available, light blue 3D-seismic still confidential, darkish green high density
2d-seismic, light green low density (generally vintage) 2D-seismic lines. Black dots well which proved
the presence of the Rotliegend aquifer, Red dots well which proved the absence of the Rotliegend
aquifer (reason not disclosed: not deposited, faulted out, eroded). Green dots well which proved the
presence of the Rotliegend strata but aquifer not encountered. The Orange triangles denote the
location of the Rotliegend targeted doublets. With a black outline the realized / operational, no
outline the doublets with advanced plans.
26

Case Study 5
Geothermal resource classification of Rotliegend
Geothermal projects
Production projects
Currently, four geothermal systems are producing from the Rotliegend aquifer. All
systems are in the operational phase which means all licences to produce or for prolonged
testing are in place and the chance of acquiring the official production licence is believed
to be 100%. This corresponds to the E1 definition and supporting explanation “
Extraction
and sale is economic on the basis of current market conditions and realistic assumptions of
future market conditions. All necessary approvals/ contracts have been confirmed or there
are reasonable expectations that all such approvals/contracts will be obtained within a
reasonable timeframe. Economic viability is not affected by short-term adverse market
conditions provided that longer-term forecasts remain positive.
”
Additionally, the E1.1 category definition emphasizes the current and future market
conditions (
Extraction and sale is economic on the basis of current market conditions and
realistic assumptions of future market conditions
) as opposed to E1.2 where the economy
of the project is relying on (dedicated) governmental subsidies and / or other
considerations (
Extraction and sale is not economic on the basis of current market
conditions and realistic assumptions of future market conditions, but is made viable
through government subsidies and/or other considerations
.).
In Section I.2. Treatment of Policy Support of the document Specifications of UNFC-
2009 to geothermal energy resources it is recognized that:
•A variety of policy support mechanisms, regulatory instruments and financial
incentives (e.g., feed-in tariffs, premiums, grants, tax credits etc.) exist
worldwide to reflect the value that offtakers or the state place on renewable
energy (or geothermal energy specifically);
•Some energy subsidies may be available on a project-by-project basis, while
others may be available to all such renewable/geothermal energy projects in
the market;
•Energy subsidies are typically phased out over time, or once the qualifying
renewable energy sources reach a certain share of overall energy production.
The project economics of the producing projects under consideration are enhanced
by the support of the Dutch Sustainable Energy Scheme (SDE+) which is a general feed-in
tariff scheme for the development of sustainable energy projects. Although the scheme can
be regarded to realize a level playing field for all energy carriers equalizing the effect of
different supportive (tax/policy/environment protection costs evasive) measures for non
sustainable energy carriers and thus maybe regarded as part of the market conditions
leading to an E1.1 classification. However, the definition given in section I2 must be
interpreted sensu stricto. Therefore the project is classified as E1.2 on the E-axis; “Extraction
is currently taking place”, thus the projects are classified as F1.1 on the F-axis.
27

Case Study 5
Table 1
Listing of resource estimates per project based on installed power and load hour
estimates. Class: E1.2; F1.1; G1, 2, 3
Project
Power estimate (MW) Load hours /yr estimate Project
lifetime
(yr)
Energy estimate over
project lifetime (PJ )
Low Best High Low Best High P90 P50 P10
I3 5 7 7 800 8160 8700 35 4 5 6
II 810 14 7200 7800 8640 35 910 12
III 7 9 11 6600 7200 7920 35 7 8 9
IV 7 9 10 7800 8160 8640 35 7 8 9
Total Stochastic sum of future energy production
of the four projects 30 32 35
The UNFC-2009 classified resource estimatesfor the ‘aggregated’ producing
geothermal systems are as follows:
UNFC-2009 class Confidence level Resource estimate (PJ)
E1.2; F1.1; G1 High confidence 30
E1.2; F1.1; G2 Medium confidence 2
E1.2; F1.1; G3 Low confidence 3
The currently operational geothermal systems (Table 1) have a longer operational
lifetime than the given production licence period. Resources that are seen to be technically
recoverable after the expiry date of the licence which is beyond the “foreseeable future”
timeframe which is stated to be five years (section I.1, document Specifications of UNFC-
2009 to geothermal energy resources) should (sensu stricto) be classified as E3 on the E-
axis. However, studies have indicated that it is highly likely that from a technical point of
view the production can commence beyond the present licence expiration and with respect
to the longstanding policy of efficient end sustainable resource exploitation in the
Netherlands licence extension is highly certain as well one may deviate from the strict five
years period definition and regard foreseeable future as long as the technical life end of
the projects. Therefore, sensu largo, an E2 classification would be more adequate also with
reference to the E3.2 of the presently immature exploration projects described later in the
application example study. The present evaluator prefers the E2 classification
Production is currently taking place, therefore the F1.1 classification can be assigned
to this category as well.
Power estimate (MW) Load hours /yr estimate Project
lifetime
(yr)
Energy estimate over
project lifetime (PJ )
Low Best High Low Best High P90 P50 P10
I3 5 7 7 800 8160 8700 10 1.2 1.5 1.8
II 810 14 7200 7800 8640 20 567
III 7 9 11 6600 7200 7920 15 3.1 3.5 4
IV 7 9 10 7800 8160 8640 5 1.0 1.2 1.3
Total Stochastic sum of future energy production
of the four projects 11 12 13
28

Case Study 5
The UNFC-2009 classified resource estimates for the ‘aggregated’ producing
geothermal systems are as follows:
UNFC-2009 class Confidence level Resource estimate (PJ )
E2; F1.1; G1 High confidence 11
E2; F1.1; G2 Medium confidence 1
E2; F1.1; G3 Low confidence 1
Exploration projects
There are six exploration licences with relatively advanced site specific evaluations
on the resource estimates. Therefore, these projects are classified as F3.1: ‘
where site-
specific geological studies and exploration activities have identified the potential for an
individual deposit with sufficient confidence to warrant drilling or testing that is designed
to confirm the existence of that deposit in such form, quality and quantity that the feasibility
of extraction can be evaluated’
.
Licences and grants have been secured classifying the projects as E2, ‘
Extraction and
sale is expected to become economically viable in the foreseeable future’
. Most projects
await final fine tuning of the subsurface work, risk evaluation and some definitive financial
close decisions to drill the first exploratory well. The resource estimates per project are
stochastically calculated from the power estimate range from the site specific evaluations
and the yearly load hours estimate range. Subsequently, the resources estimates of these
six exploration projects are stochastically added as well as these projects are operating
independent of each other resulting in the aggregated resource estimate of this class.
Project
Power estimate (MW) Load hours /yr estimate Project
lif etime
(yr)
Energy Estimate over
project lifetime (PJ )
Low Best High Low Best High P90 P50 P10
V15 21 28 7500 8400 8700 35 18 22 26
VI 6 8 10 7500 8400 8700 40 8 9 10
VII 612 17 7500 8400 8700 45 12 16 20
VIII 13 20 30 7500 8400 8700 35 17 22 27
IX 713 28 7500 8400 8700 50 16 23 34
X10 15 29 7500 8400 8700 45 18 23 32
Total Stochastic sum of future energy production
of the four projects
104 116 129
The UNFC-2009 classified resource estimates for the ‘aggregated’ producing
geothermal systems are as follows:
UNFC-2009 class Confidence level Resource estimate (PJ )
E2; F3.1; G4.1 High confidence 104
E2; F3.1; G4.2 Medium confidence 12
E2; F3.1; G4.3 Low confidence 13
29

Case Study 5
Rotliegend Play resource estimate
Play wise resource estimates have been performed using Rotliegend geothermal
potential estimate of Kramer et al. 2012. They estimate a Heat In Place for the Rotliegend
reservoir of 409,000 PJ. Potential Recoverable Heat estimate is in the order of 111,000 PJ.
Defining notional projects and applying general economic and flow constraints to the
Potential Recoverable Heat map results in a Recoverable Heat estimate of some 27,000 PJ.
Development of the notional projects is not envisaged in the foreseeable future, so
an E3 classification applies. The general economic evaluation of the Recoverable Heat
estimate leads to an E3.2 classification as the ‘
economic viability of extraction cannot be
determined due to insufficient information
’. The Recoverable Heat figures are part of the
Potential Recoverable Heat estimate. Therefore, the remainder of the Potential Recoverable
Heat can be regarded as “not economic yet” and classified as E3.3.
The above resource figures of Kramer et al. 2012 all pertain to notional geothermal
doublet exploration projects based on regional mapping of the Rotliegend reservoir
(ThermoGis). Such notional projects classify as F3 on the F-axis (“
maturities of studies and
commitments
”). The amount of data underlying the reservoir maps bears the character of
local geological study and thus the classification can be more specifically classified as F3.2
“
where local geological studies and exploration activities indicate the potential for one or
more deposits in a specific part of a geological province, but requires more data acquisition
and/or evaluation in order to have sufficient confidence to warrant drilling or testing that
is designed to confirm the existence of a deposit in such form, quality and quantity that the
feasibility of extraction can be evaluated;”.
The estimates are regarded as best estimates of future notional exploration projects.
UNFC-2009 states "Category G4, when used alone, shall reflect the best estimate and is
equal to G4.1+G4.2". Table 2 shows the UNFC-2009 classification of the above mentioned
resource estimates.
Table 2
UNFC-2009 classification of the Rotliegend Play resource estimate
Classification Estimate (PJ)
E3.2; F3.2; G4 (G4.1+G4.2) 27 000
E3.3; F3.2; G4 (G4.1+G4.2) 84 000
Rotliegend Play resource estimate
For portfolio or national reporting purposes there, generally, is a wish for a single
best estimate of the resource. The figures of the producing geothermal systems may be
added under the condition that the different categories are mentioned (UNFC-2009 Part II
section IV). For adding the resource estimates of exploration projects, the figures should be
appropriately risked. For the Exploration projects (E2; F3.1; G4) the risk of not resulting in
an economical viable project is regarded as low. A Possibility Of Discovery (POD) of 80% is
deemed realistic. The POD of the Play based Recoverable Heat estimate (E3.2; F3.2; G4) is
thought to be significantly lower. A hint is given by the relatively high number of
exploration licences with Rotliegend as target reservoir, which expired or were withdrawn.
The POD is estimated to be 50% for this resource class. The remaining Potential Recoverable
Heat (E3.3; F3.2; G4) has a very low chance of discovery. A POD of 10% is thought to be
realistic. Table 3 gives the result of the aggregation of the above described geothermal
resources.
30

Case Study 5
Table 3
The best estimate of the geothermal resource potential of the Dutch Rotliegend Play
UNFC-2009 class Resource estimate (PJ) POD (%) Risked resource estimate (PJ)
E1.1; F1.1; G1+G2 32 -32
E2; F1.1; G1+G2 12 -12
E2; F3.1; G4
(G4.1+G4.2) 116 80 93
E3.2; F3.2; G4
(G4.1+G4.2) 27 000 50 13 500
E3.3; F3.2; G4
(G4.1+G4.2) 84 000 10 8400
Total risked resources 22 037
Disclaimer
All figures presented are not the operator figures because they reside in the
confidential domain. Figures given are rough estimates based on production data and
regional geological data and average operational figures. The POD and thus the risked
volumes are only a rough guess. These values should not be used for reporting as they are
only given as an illustration of a portfolio or national resource reporting as described in
UNFC-2009 Part II section IV, National resource reporting.
References
ThermoGis: http://www.thermogis.nl/thermogis_en.html
Kramers, L., van Wees, J.-D., Pluymaekers, M.P.D., Kronimus, A. & Boxem, T., 2012, Direct
heat resource assessment and subsurface information systems for geothermal aquifers; the
Dutch perspective. Netherlands Journal of Geosciences — Geologie en Mijnbouw , 91 – 4,
pp 637 –649.
UNFC-2009, United Nations Framework Classification for Fossil Energy and Mineral
Reserves and Resources 2009. (UNFC-2009)
http://www.unece.org/energy/se/unfc_2009.html
MEA 2015, NATURAL RESOURCES AND GEOTHERMAL ENERGY IN THE NETHERLANDS.
2014 Annual review. An overview of exploration, production and underground storage.
(http://www.nlog.nl/resources/Jaarverslag2014/ENGLISH%20Natural%20Resources%2020
14%20final_v1.pdf )
van Wees J.-D., Kronimus A., van Putten M., Pluymaekers M.P.D., Mijnlieff H., van Hooff P.,
Obdam A. & Kramers L., 2012, Geothermal aquifer performance assessment for direct heat
production –Methodology and application to Rotliegend aquifers. Netherlands Journal of
Geosciences — Geologie en Mijnbouw. 91 –4, 651 –665.
31

Case Study 6
Case Study 6: Hódmezővásárhely District Heating
Project Location: Hódmezővásárhely, Hungary
Data date: 2012
Date of evaluation: January 2016
Quantification method: Volumetric heat assessment
Estimate type: Probabilistic
Project summary
Hódmezővásárhely is a mid-size town with 47,668 inhabitants situated in the south-
eastern part of the Pannonian Basin, Hungary, Central Europe. The geothermal potential of
the Pannonian basin is outstanding in Europe, as it lies on a characteristic positive
geothermal anomaly, with heat flow density ranging from 50 to 130 mW/m2with a mean
value of 90-100 mW/m2and geothermal gradient of about 45°C/km (Dövényi and Horváth,
1988). This increased heat flux is related to the Early-Middle Miocene formation of the basin
when the lithosphere stretched and thinned (thus the crust is “only” 22-26 km thick) and
the hot asthenosphere got closer to the surface (Horváth and Royden, 1981).
During the thermal subsidence of the basin, a large depression formed, occupied by
a huge lake (Lake Pannon), which was gradually filled up by sediments transported by rivers,
originating in the surrounding uplifting Alpine and Carpathian mountain belts (Bérczi and
Phillips, 1985; Magyar et al., 1999).
These several thousand metre thick multi-layered porous sediments (Upper
Miocene-Pliocene “Pannonian” sequence”) have low heat conductivity and are composed
of successively clayey and sandy deposits. Within this basin-fill sequence the main thermal-
water bearing sandy aquifers are found in a depth interval of ca. 800-2,000 m in the interior
parts of the basin where the temperature ranges from 60 to 90°C. This regionally extended
geothermal aquifer is widely used for direct heat purposes as well as for balneology on
many parts of the Pannonian Basin, especially in its south-eastern part in Hungary, where
Hódmezővásárhely is also situated.
In Hódmezővásárhely a Municipality owned company has operated a cascade system
of 10 wells (8 production and 2 reinjection) for over 20 years (Ádok, 2012). The first well
was drilled in 1954 for medical and district heating purposes. The wells are multi-purpose
and supply water for district heating, domestic hot water supply and are also used for
balneological purposes (Figure 1). Due to the chemical composition of the water, 3 wells
qualify as medicinal water. The current system consists of two separate geothermal loops.
The high temperature (80–90°C) thermal water is first directed to heat exchangers of the
district heating plants. Than the cooled (ca. 50°C) outlet water is partly directed to the
second loop, which is the pipeline of domestic hot water supply, partly reinjected (at a
temperature of 35°C). Part of the water used for domestic hot water supply is also used for
balneological purposes (mixed with cold water). The system provides heating of 2,725 flats
and 130 public consumers, such as the town hall, hospitals, museums, schools, shopping
centres, etc. It was developed in several stages (1967, 1984, 1994-1998, 2007), partly co-
financed by the Energy and Environment Operative Program of the European Regional
Development Fund, but mostly developed from the resources of the Municipality.
32

Case Study 6
The outflow temperature of 6 production wells used for district-heating and
domestic hot water supply ranges between 65–90°C, with the wells’ depth ranging between
1800 and 2400 m on average. The wells tap aquifers with high hydraulic conductivity (1.15-
5.8 x 10-5 m/s) and effective porosity (0.13-0.16) (Szanyi and Kovács, 2010), therefore they
may yield thermal water up to 30 L/s. However, during use, the max. production rate is
20 L/s. (The other 2 production wells –technically also part of the cascade system –are
used for domestic water supply and balneological purposes. These 2 wells tap shallower
aquifers with lower temperatures and are not considered in this study).
The intensive use of the wells completed in the Upper Pannonian sandy aquifers in
the 1970s and 1980s decreased the hydraulic heads continuously, which was the reason for
initiating reinjection. The 2 reinjection wells were drilled in 1998 and 2007. However, only
about 50% of the total amount of produced water for heating purposes is reinjected (Ádok,
2012). The injectivity degrades mainly due to the clogging of the pore-throats. Well
maintenance using compression cleaning is needed every 2 years since the injected water
is filtered using a microfiber filter system. The average reinjection temperature is 35°C which
underpins a good thermal efficiency (compared to 80–90°C of production temperature). So
far no detectable temperature decrease occurred in the aquifer at a 300 m distance from
the injection well, because of the high heat capacity of the rock matrix (Szanyi and Kovács,
2010).
Figure 1
Distribution of uses in Hódmezővásárhely
Total annual production of the entire cascade system (2009): 1,605,407 m3
Since the expansion of the geothermal system (1993), the gas consumption of the
heating centres dramatically dropped (from 4.6 million m3to 0.5 million m3). In 2011 the
share of geothermal in the total heating was about 86%, while the gas accounted for 14%.
The increasing use of geothermal has a very positive effect on air quality, an annual
saving of 4.5 million m3of gas is calculated, which is equivalent of 4,680 t CO2 emission.
Quantification
There are two types of quantification methods presented (see more details under the
UNFC-2009 classification section): a simple production forecast for the currently operating
project and a volumetric method using Monte Carlo simulation to estimate the entire (future,
still untapped) potential of the reservoir, on the basis of a conceptual or notional project.
The quantification of the resource estimate was done by applying the volumetric
method using Monte Carlo simulation for the reservoir parameters (area, thickness,
temperature, porosity) as well as recovery factor. Assumptions about the volume of the
reservoir are based on well data and cumulative recharge areas of single wells deriving from
hydrodynamic modelling. Temperature data refer to produced depths, calculated from
outflow temperatures. The quantities associated with high-, medium-and low-level of
33

Case Study 6
confidence are based on 90, 50 and 10 percentile of the resulting cumulative probability
distribution respectively. For details see Appendix 1.
Product type
Heat (energy for heating).
Reference Point
The reference point is where fluid enters the heat exchanger. Due to the close
distance between the wells and the plant and modern insulation techniques, there is
negligible heat loss between the well-head and the heat exchanger (measured temperature
drop is 0.1°C/km along the pipes).
Project lifetime
The current Hódmezővásárhely project has been operating for around 20 years (with
an increasing number of wells) and its foreseen operation lifetime is another 25 years at the
Effective Date of evaluation. The same lifetime is assumed here for the notional project.
Geothermal resources
Geothermal resource potential of the current Hódmezővásárhely project:
•Best Estimate: 5 PJ
Geothermal resource potential of the larger Hódmezővásárhely reservoir (notional
project):
•Low estimate: 93 PJ
•Best Estimate: 210 PJ
•High Estimate:366 PJ
UNFC-2009 classification
The production history of the currently operating Hódmezővásárhely district heating
project shows that since 1994 approximately 0.2 PJ is produced annually, as reported by
the Operator (depending on heat demand). On the other hand, the forecasted amount of
available resources estimated for the entire reservoir volume of the site (93PJ –P90, 210 PJ
–P50, 366 PJ –P10) is some orders of magnitude higher, which is due to the excellent
reservoir properties and especially to the high recharge rates. Therefore, it is obvious that
the present district heating project recovers only a small fraction of the potentially
extractable heat that might be utilized in the future by another project(s) either parallel or
in series with the present project. Therefore there are two ways to represent the UNFC-2009
classification of this area: (a) classify the current mature and operating project, forecasting
its production history (that recovers only a small proportion of the available heat; and (b)
classify the potential future project(s) that may utilize the available resources. Both
scenarios are presented below:
34

Case Study 6
E category classification and subclassification of the present project
Category UNFC-2009 definition Reasoning for classification
E1 Extraction and sale has been
confirmed to be
economically viable
E1.1 Extraction and sale is
economic on the basis of
current market conditions
and realistic assumptions of
future market conditions.
•The project has been operating for 20
years and based on all experiences it is
foreseen to run at least another 25 years.
Total price of geothermal heat (4.0
Hungarian Forint (HUF)/MJ) is about 2/3
of the price of the imported gas (5.58
HUF/MJ) (2012 data, 300 HUF = 1 Euro),
therefore the project is economic under
the current market conditions and is
supplying a substantial and existing heat
market
•It has very positive and quantified effects
on the reduction of gas consumption
and decreased CO2emission.
F category classification and subclassification of the present project
Category UNFC-2009 definition Reasoning for classification
F1 Feasibility of extraction by a
defined development
project or mining operation
has been confirmed.
F1.1 Extraction is currently taking
place.
The gradually expanding project has been
operating since 1954. All production licences
available and secured in the long-term.
G category classification of the present project
Category UNFC-2009 definition Reasoning for classification
G1 Quantities associated with a
known deposit that can be
estimated with a high level
of confidence.
Based on a production forecast a 5PJ heat
energy to be extracted can be foreseen with a
moderate level of confidence for the next 25
years (25 x 0.2 PJ).
G2 Quantities associated with a
known deposit that can be
estimated with a moderate
level of confidence.
G3 Quantities associated with a
known deposit that can be
estimated with a low level of
confidence.
35

Case Study 6
UNFC-2009 classification and quantification of the present
project
Classification Energy Quantity Supplemental information
E1.1; F1.1; G1+G2 5 PJ Forecast of the production history
E category classification and subclassification of the potential
future project(s)
Category UNFC-2009 definition Reasoning for classification
E3 Extraction and sale is not
expected to become
economically viable in the
foreseeable future
*
or
evaluation is at too early a
stage to determine
economic viability.
Based on the current project experiences and
market conditions a similar project(s) is expected
to become economically viable in the next 5–10
years to exploit the still available resources.
*
Note that, as the “foreseeable future” has been defined as within a maximum of five years in the geothermal
context, the expectation that the notional project will become economically viable in the next 5–10 year
prompts the use of the E3 category.
F category classification and subclassification of the future
potential project(s)
Category UNFC-2009 definition Reasoning for classification
F2 Feasibility of extraction by a
defined development project
or mining operation is
subject to further evaluation.
At the moment no concrete development plans
are available and future project(s) need new
capital investments as well as licences, which are
currently not initiated.
G category classification of the future potential project(s)
Category UNFC-2009 definition Reasoning f or classification
G1 Quantities associated with a
known deposit that can be
estimated with a high level
of confidence.
A volumetric Monte Carlo assessment has
indicated a 90% probability of 93 PJ (low estimate)
of recoverable geothermal energy. Therefore G1 is
93-5 PJ = 88 PJ (the 5 PJ is assigned to the
currently operating project see above)
G2 Quantities associated with a
known deposit that can be
estimated with a moderate
level of confidence.
A volumetric Monte Carlo assessment has
indicated a 50% probability of 210 PJ (best
estimate) of recoverable geothermal energy.
Therefore G2 is 210-5-88=117 PJ
G3 Quantities associated with a
known deposit that can be
estimated with a low level of
confidence.
A volumetric Monte Carlo assessment has
indicated a 10% probability of 366 PJ (high
estimate) of recoverable geothermal energy.
Therefore G3 is 366-5-88-117=156 PJ
36

Case Study 6
UNFC-2009 classification and quantification of the future
potential project(s)
Classification:
UNFC-2009
Class
Energy
Quantity Supplemental information
E3; F2; G1 88 PJ 90% probability of 93PJ (low estimate) of recoverable
geothermal energy minus the foreseen total production
(5PJ) of the current project
E3; F2; G2 117 PJ A 50% probability of 210 PJ (best estimate) of recoverable
geothermal energy, minus the foreseen total production of
the current project, therefore G2 is 210-5-88=117 PJ
E3; F2; G3 156 PJ A 10% probability of 366 PJ (high estimate) of recoverable
geothermal energy minus the foreseen total production of
the current project, therefore G3 is 366-5-88-117=156 PJ
References
Ádok, J. (2012): Geotermikus fűtési rendszerek-egy működőrendszer tapasztalatai –
presentation at the national workshop of the Geo-DH (Promote Geothermal District
Heating Systems in Europe) project, December 3, 2012, Budapest.
Bérczi, I., Phillips, R.L.(1985): Processes and depositional environments within deltaic-lacustrine
sediments, Pannonian Basin, Southeast Hungary –
Geophysical Transactions,
31, 55-74.
Dövényi, P., Horváth, F. (1988): A review of temperature, thermal conductivity and heat flow
data from the Pannonian Basin, in: Royden, L.H., Horváth, F. (Eds): The Pannonian Basin a
Study in Basin Evolution. –
American Association of Petroleum Geologist memoirs
, Tulsa,
Oklahoma, 45, 195-233.
Horváth, F., Royden, L.H.(1981): Mechanism for formation of the intra-Carpathian basins: A
review. –
Earth Evolutionary Sciences
, 1, 307-316.
Magyar, I., Geary, D.H., Müller, P.(1999): Paleogeographic evolution of the Late Miocene
Lake Pannon in Central Europe. –
Palaeogeography, Palaeoclimatology, Palaeoecology,
147,
151-167.
Szanyi, J., Kovács, B. (2010): Utilization of geothermal systems in South-East Hungary –
Geothermics
39, 357-364.
Zilahi-Sebess L., Merényi, L., Paszera, Gy., Tóth, Gy., Boda, E., Budai, T.: Nyersanyag készletek, A
hazai ásványi nyersanyag-potenciál, 5. Geotermikus energia, (Háttértanulmány), Nemzeti
Energiastratégia, Készletgazdálkodási és hasznosítási cselekvési terv, Manuscript, (2012), 84 p.
37

Case Study 6
Appendix 1 -Assumptions of volumetric Monte Carlo
assessment
Estimation of recharge areas of production wells
The produced aquifer (Upper Miocene sandstone reservoir) is regionally extended in
the entire basin, which is produced by many other users. Therefore it was necessary to
determine the “impact area” of the project, i.e. the recharge area of the production wells
belonging to the Hódmezővásárhely project. Production wells are closely spaced (few
hundred metres from each other) (Figure 1). Results of previous hydrodynamic modelling
in similar geological conditions at a nearby site showed that the recharge area of a well can
be determined as follows: R = 0.8 x Q (Eq1) (Zilahi-Sebess et al. 2012); where R is the radius
of the recharge area around a given well and Q is the yield of the well. In the present study,
the 4 major production wells with high temperature (80-90°C) and yield (750 to 1,500 L/min)
were considered (the other wells with either lower temperature or little yield within the
impact area of the major producing wells were excluded).
Figure 1 shows the recharge areas of the single wells (black lines) (radius range from
600 to 1,200 m depending on the yield). The red line shows the cumulative area of the 4
individual areas which is 14.2 km2in total.
Figure 1
Hódmezővásárhely project –producing wells
Table 1
Input values for Monte Carlo
Reservoir area
(km2)
Reservoir
thickness (m)
Reservoir
temperature (°C) Porosity ( %) Recovery
factor
min max min max min max min max min max
12.5 15.5 600 900 58 108 618 0.10 0.20
38

Case Study 7
Case Study 7: Alto Peak
Project Location: Leyte, Philippines
Data date: December 2014
Date of evaluation: September 2015
Quantification method: Volumetric Stored Heat Assessment
Estimate type: Probabilistic
Project summary
The Alto Peak Geothermal Project in Leyte, Philippines, located on the south-eastern
side of the Greater Tongonan Geothermal Field. The project area is within the Geothermal
Renewable Service Contract (GRESC) 2009-10-001, a concession block (total area 504 km2)
awarded in 2009 by the Philippine Department of Energy to Energy Development
Corporation (EDC), a fully privatized geothermal company. Alto Peak is part of what was
known in the 1990s as Leyte-A geothermal project which aimed to generate an additional
640 MWeof electric power utilizing the geothermal resources in Leyte.
The encouraging results of the earlier surface explorations studies led to the decision
to finance a 3-well deep exploration program. From 1991 to 1992, three wells, AP-1D, AP-
2D and AP-3D were drilled to test the exploration model, characterize and quantify the size
of the geothermal resource.
Subsurface data from wells AP-1D and AP-2D indicated high resource temperature
(>350oC) and high permeability, with an associated resource area of approximately 2 km2.
Petrological and fluid inclusion studies indicated that the Alto Peak geothermal system is
old, waning but is rejuvenated by injection of heat and fluids from recent magmatic
intrusions (Reyes et al., 1993). Discharge fluid chemistry also indicated a liquid-dominated
reservoir with a temperature of approximately 350-400oC.
A 4-well delineation drilling programme was then recommended to define the extent
of the productive temperatures, confirm additional resources outside the proven resource,
further explore and test the candidate injection area northwest of the project. Further
scientific studies, including detailed geological studies and surface resistivity
measurements, were done to support the drilling of additional, deep, delineation
production wells.
The feasibility study of the project in 1993 based on the last five wells drilled showed
that the proposed 80 MWeelectric power development in the Alto-Peak is both technically
and economically feasible. Thus, development drilling commenced in 1994 and was
completed in 1995.
In 1997, the Alto Peak project was reviewed to determine the appropriateness of the
resource for power development. The review indicated that that the system is non-
commercial utilizing the existing technologies to address the acidic fluids and mineral
scaling characteristics encountered during the discharge tests (PNOC-EDC, 1997). The
review also pointed out that the boundaries of the resource has not been fully delineated
and although Monte Carlo analysis using stored heat calculation method of reserve
estimation indicated about 80 MWeof reserve there is a high degree of uncertainty about
the development potential of the project which is believed to be immature to allow
commercial development and exploitation. As a result, the Alto Peak project was shelved in
1997 and only regular physical monitoring and blockage surveys of the wells were
performed.
39

Case Study 7
Alto Peak project
In 2014, EDC reviewed the Alto Peak project as part of the overall assessment of the
potential growth project areas southeast of Tongonan, Leyte which included Janagdan, Mt.
Lobi-Anonang, Mahagnao and Bato-Lunas project areas. The Alto Peak review was based
on the result of the field geological and geochemical surveys undertaken from June to
September of 2014. The geological studies included lithological mapping, structural
mapping and tectonic interpretations. The geochemical surveys comprised of re-sampling
of the thermal manifestations, review and re-interpretation of fluid and gas discharge data
and stable isotopes. Review of the subsurface physical data was also made as part of the
review. To date, nine production (two cement were plugged) and one injection wells were
drilled within the project area. A Geothermal Energy Resource estimate based on the 1993
and 1997 and the 2014 data was also done to re-assess the area as a growth project.
Quantification
The quantification of energy for the project is based on the Volumetric Method using
Monte Carlo simulation. The assumptions used about the volume of the reservoir were
based on the resource assessment done in 1993 and 1997 with modifications as deemed
appropriate based on the well baseline data.
The confidence level in the estimates is based on a Monte Carlo simulation of a
Volumetric Heat assessment. The quantities associated with the high, medium and low level
of confidence area based on 90, 50 and 10 percentile of the resulting cumulative probability
distribution, respectively. Input variables are shown in the following table.
Input Variables Units
Most
Likely Min Max Mean SD
Probability
Distribution
Area km20.3287 3.553 triangular
Thickness m 1 700 1300 1950 triangular
Temperature °C 260 220 345 triangular
Recovery
factor
0.06 0.02 =f (porosity)
Load Factor 0.92 0.8 1.0 triangular
Rejection
Temp
°C 180 Single value
Product type
The product type is electricity.
Reference Point
The reference point is at the station switchyard, where power is exported into the
national grid in the Philippines. Internal power use or parasitic load has already been
subtracted.
40

Case Study 7
Geothermal Energy Resources
Geothermal Energy Resources:
•Low estimate (P90): 5 PJ (150 MWeyr); 6 MWefor 25 years
•Best Estimate (P50): 15 PJ (475 MWeyr); 19 MWefor 25 years
•High Estimate (P10): 34 PJ (1,075 MWeyr); 43 MWefor 25 years
UNFC-2009 classification
E category classification
Category
UNFC-2009
definition Supporting explanation Reasoning f or classification
E2 Extraction and sale
is expected to
become
economically
viable in the
foreseeable future.
Extraction and sale has
not yet been confirmed
to be economic but, on
the basis of realistic
assumptions of future
market conditions, there
are reasonable
prospects for economic
extraction and sale in
the foreseeable future.
Heat available for
exploitation and conversion
to electricity not yet
confirmed to be
commercially viable, on the
basis of realistic assumptions
of future local market
conditions. Project is
however, expected to
become commercially viable
in the foreseeable future due
to introduction of regulatory
incentives (e.g. FIT for
emerging technologies).
Fcategory classification and subclassification
Category
UNFC-2009
definition Supporting explanation Reasoning f or classification
F2 Feasibility of
extraction by a
defined
development
project or mining
operation is
subject to further
evaluation.
Preliminary studies
demonstrate the
existence of a deposit in
such form, quality and
quantity that the
feasibility of extraction
by a defined (at least in
broad terms)
development project or
mining operation can be
evaluated. Further data
acquisition and/or
studies may be required
to confirm the feasibility
of extraction.
The existence of a
geothermal resource has
been confirmed by the result
and assessment of 9
production wells and 1
injection well. Additional
surveys (e.g. MT and gravity)
are however, needed to
refine the boundary of the
resource. Current research is
on-going on corrosion
resistant alloys (CRA), scale
inhibitors and improvement
in well sustainability to
demonstrate the commercial
application of needed
materials/resources.
41

Case Study 7
Sub-
category
UNFC-2009
definition
F2.2 Project activities
are on hold
and/or where
justification as a
commercial
development may
be subject to
significant delay.
Project activities are on-
hold for reasons not
related to the energy
resource potential of the
project or knowledge on
the physical and
geochemical potential of
the resource;
construction of a pilot
electrical power
generation facilities may
be subject to significant
delays.
The proposed development
is on-hold due to concern on
utilization of high
temperature acidic fluids
which is expected to affect
commercial viability of the
project. Material testing of
wellhead, casings and
related material is needed to
demonstrate metallurgical
viability and sustainability of
operations
G category classification
Category UNFC-2009 def inition Reasoning for classification
G1 Quantities associated with a
known deposit that can be
estimated with a high level of
confidence.
A volumetric Monte Carlo simulation has
indicated that there is a 90% probability
that 6 MWecan be produced for 25 years
(5PJ).
G2 Quantities associated with a
known deposit that can be
estimated with a moderate
level of confidence.
A volumetric Monte Carlo simulation has
indicated that there is a 50% probability
that 19 MWecan be produced for 25 years
(15 PJ). This equates to the best estimate,
i.e. G1+G2, with G2 being incremental to
G1. Thus, G2 is equal to 15-5=10 PJ.
G3 Quantities associated with a
known deposit that can be
estimated with a low level of
confidence.
A volumetric Monte Carlo simulation has
indicated that there is a 10% probability
that 43 MWecan be produced for 25 years
(34 PJ). This equates to the high estimate,
i.e. G1+G2+G3, with G3 being incremental
to G1+G2. Thus, G3 is equal to 34-15=19 PJ.
42

Case Study 7
UNFC-2009 classification and quantification
Classification Energy Quantity Supplemental information
UNFC-2009
Class
Energy units used: Peta-Joules
(PJ)= (x1015 J)
E2; F2.2; G1 5 PJ
*
Low estimate of the geothermal energy
resource; it is the P90 estimate.
E2; F2.2; G2 10 PJ
*
Incremental between Best and Low
estimates; the P50-P90 estimate (15-5 PJ),
with G2 being incremental to G1.
E2; F2.2; G3 19 PJ
*
Incremental between High and Best
estimates; the P10-P50 estimate
(34-15 PJ), with G3 being incremental to
G1+G2.
*
Energy quantities are subject to rounding
Disclaimer
Application examples are made only for the purpose of illustrating the applicability
of UNFC-2009 to “real” geothermal energy projects. This application example, with facts
and figures, is based on the Alto Peak project in the Philippines. Data and information is
available in the public domain and in the referenced articles. Resource figures are loosely
based on such available information.
References
Bustamante, C.C., 1993. Reservoir simulation of the Alto Peak geothermal field, Leyte,
Philippines. UNU Report No. 5, UNU Geothermal Training Programme, Iceland, 29 p.
Philippine National Oil Company –Energy Development Corporation (PNOC-EDC), 1997.
Alto Peak Geothermal Field Resource Assessment Review Report (final), prepared by
Mesquite Group, Inc., Harding Lawson Associates, and Dames and Moore.
Reyes, A.G., W.G. Giggenbach, J.R.M. Salera, N.D. Salonga and M.C. Vergara, 1993. Petrology
and geochemistry of Alto Peak, a vapor-cored hydrothermal system, Leyte Province,
Philippines.
Geothermics
, Vol. 22, Issues 5-6, Special Issue, Geothermal Systems of the
Philippines, 379-519.
43

Case Study 8
Case Study 8: Baslay-Dauin
Project Location: Baslay-Dauin, Negros Oriental, Visayas, Philippines
Data date: August 2014
Date of evaluation: August 2015
Quantification method: Volumetric Heat Assessment
Estimate type: Probabilistic
Project summary
Baslay-Dauin geothermal project is located at the southern tip of Negros Island,
Philippines and covers an area of 46 km2of the Southern Negros Geothermal Field.
Surface geothermal exploration activities were undertaken within the Baslay-Dauin
Geothermal Project from 1973 to 1979 to investigate its geothermal potential. Drilling of
two exploration wells, DN-1 and DN-2 were completed in 1982 and 1983, respectively.
DN-1 encountered a temperature of 240 oC and near-neutral fluids with a maximum
chloride content of 3,300 mg/kg but discharged large amount of elemental sulphur
suggesting possible acid resource beneath the area drilled by DN-1. As a result of the first
drilling, the second well DN-2 was drilled 4 km southwest of DN-1 to test the presence of
an exploitable resource within the Nagpantaw low-resistivity anomaly (Harper and Arevalo,
1982).
The two exploration wells, DN-1 and DN-2 confirmed the presence of a geothermal
energy source within the project area. Well data from DN-1 and DN-2 suggest that DN-1
was drilled closer to the heat source and interpreted upflow area while DN-2 lies within the
periphery of the outflow area. The development of the project area was however, relegated
to lower priority by the Energy Development Corporation (EDC) and development was
instead focused on other high potential geothermal projects in the country (Bayrante et al.,
1982).
Baslay-Dauin project
Between August 2013 and April 2014, EDC conducted geological, geochemical and
geophysical survey (3G) campaigns within Baslay-Dauin project to re-evaluate the
development potential of Baslay-Dauin as a candidate brown field growth area and to
establish its hydrological relationship with the adjacent Southern Negros Geothermal Field
(SNGPF). The project was included by the Department of Energy (DOE) of the Philippines in
the geothermal sector road map which envisions an addition of 1,495 MWecapacity to the
grid over a planning period 2011-2030 (DOE, 2011). The result of the project resource
assessment in 2014 infers a resource separate from SNGPF.
The power potential of the Baslay-Dauin geothermal resource was estimated based
on the size of the resource defined by the Magneto-Telluric (MT) survey complemented by
updated geological assessment and the result of the two exploration wells drilled in the
project.
44

Case Study 8
Quantification
The quantification of energy for the project is based on the Volumetric Method using
Monte Carlo simulation. The assumptions used about the volume of the reservoir are based
on the result of the MT surveys done in 2013 and additional surface data from geology and
geochemistry interpretations. Assumptions about the reservoir temperature are based on
the well DN-1.
The confidence level in the estimates is based on a Monte Carlo simulation of a
Volumetric Heat assessment. The quantities associated with a high, medium and low level
of confidence are based on 90, 50 and 10 percentile of the resulting cumulative probability
distribution, respectively. Input variables are shown in the following table.
Input Variables Units
Most
Likely Min Max Mean SD
Probability
Distribution
Area km24.43 3.58 7.63 triangular
Thickness m 1 800 1400 2400 triangular
Temperature °C 250 220 270 triangular
Recovery factor 0.06 0.02 =f (porosity)
Load Factor 0.92 0.8 1.0 triangular
Rejection Temp °C 180 Single value
Product type
The product type is electricity.
Reference Point
The reference point is at the station switchyard, where power is exported into the
national grid in the Philippines. Internal power use or parasitic load has already been
subtracted.
Geothermal Energy Resources
Geothermal Energy Resources:
•Low Estimate (P90): 16 PJ (500 MWeyr); 20 MWefor 25 years
•Best Estimate (P50): 28 PJ (875 MWeyr); 35 MWefor 25 years
•High Estimate (P10): 43 PJ (1,400 MWeyr); 55 MWefor 25 years
45

Case Study 8
UNFC-2009 classification
E category classification and subclassification
Category UNFC-2009 definition Reasoning for classification
E3 Extraction and sale is
not expected to
become economically
viable in the
foreseeable future or
evaluation is at too
early a stage to
determine economic
viability.
The evaluation of the economic viability of the
project shall depend on the result of a surface
geoscientific study and modelling which will
serve as basis for the formulation of the
exploration and delineation drilling program.
Sub-category UNFC-2009 definition
E3.2 Economic viability of
extraction cannot yet
be determined due to
insufficient information
(e.g. during the
exploration phase).
Additional geophysical study and modelling (MT
additional stations) to possible improve the
quality of data. The MT data will be used to
come up with a refine geophysical model which
will serve as input in the stored heat estimates
and revised volumetric stored heat estimates.
F category classification and subclassification
Category UNFC-2009 definition Reasoning for classification
F2 Feasibility of extraction
by a defined
development project or
mining operation is
subject to further
evaluation.
The existence of a geothermal resource has
been confirmed by the result of the deep
exploration wells, existing resource assessment
and stored heat calculation indicated the
presence of a commercially productive
resource. Additional MT surveys are however,
needed to refine the model and the boundary
of the resource. Additional exploration drilling
and testing is needed to further evaluate the
well discharge and resource characteristics.
Sub-category UNFC-2009 definition
F2.2 Project activities are on
hold and/or where
justification as a
commercial
development may be
subject to significant
delay.
The proposed development is on-hold pending
results of further MT surveys, resource
assessment and stored heat estimation. Further
exploration and delineation drilling results also
needed to justify commercial development. The
project is included in the Philippine Energy
Programme which is expected to be reviewed
by the new administration in 2016.
46

Case Study 8
G category classification
Category UNFC-2009 definition Reasoning f or classification
G1 Quantities associated with
a known deposit that can
be estimated with a high
level of confidence.
A volumetric Monte Carlo simulation has indicated
that there is a 90% probability that 20 MWewill be
produced in the area for 25 years (16 PJ).
G2 Quantities associated with
a known deposit that can
be estimated with a
moderate level of
confidence.
A volumetric Monte Carlo simulation has indicated
that there is a 50% probability that that 35 MWewill
be produced for 25 years (28 PJ). This equates to the
best estimate, i.e. G1+G2, with G2 being incremental
to G1. Thus, G2 is equal to 28-16=12 PJ.
G3 Quantities associated with
a known deposit that can
be estimated with a low
level of confidence.
Avolumetric Monte Carlo simulation has indicated
that there is a 10% probability that 55 MWewill be
produced for 25 years (43 PJ). This equates to the
high estimate, i.e. G1+G2+G3, with G3 being
incremental to G1+G2. Thus, G3 is equal to 43-
28=15 PJ.
UNFC-2009 classification and quantification
Classification Energy Quantity Supplemental information
UNFC-2009
Class
Energy units used:
Peta-Joules (PJ)
=(x1015J)
E3; F2.2; G1 16 PJ
*
Low estimate of the geothermal energy resource; it
is the P90 estimate.
E3; F2.2; G2 12 PJ
*
Incremental between Best and Low estimates; the
P50-P90 estimate (28-16 PJ), with G2 being
incremental to G1.
E3; F2.2; G3 15 PJ
*
Incremental between High and Best estimates; the
P10-P50 estimate (43-28 PJ), with G3 being
incremental to G1+G2.
*
Energy quantities are subject to rounding.
Disclaimer
Application examples are made only for the purpose of illustrating the applicability
of the UNFC-2009 classification framework to a “real” geothermal energy projects. This
application example, with facts and figures, is based on the Baslay Dauin project in the
Philippines. Data and information are available in the public domain and in the referenced
articles. Resource figures are loosely based on such available information.
47

Case Study 8
References
Bayrante
et al
., 1997.A review of the origin of sulphur in DN-1 discharge and its implication
for future development, Dauin geothermal prospect, Central Philippines.
GRC Trans
. Vol. 21,
p. 603-608.
Bayrante
et al
., 1997. Development potential of the Dauin geothermal prospect, Negros
Oriental, Philippines.
GRC Trans
. Vol. 21, p. 609-615.
Department of Energy, Philippines, 2011. Renewable Energy Plans and Programs (2011-
2030), 67 p.
Harper, R. T. and E. M. Arevalo, 1982. A geoscientific evaluation of the Baslay-Dauin
prospect, Negros Oriental, Philippines.
Proc
. Pacific Geothermal Conference and New
Zealand Geothermal Congress.
48

Case Study 9
Case Study 9: Canavese GeoDH System
Project Location: Milan, Italy
Data date: 2010
Date of evaluation: December 2015
Quantification method: Simulation
Estimate type (deterministic/probabilistic): Deterministic scenario
Project summary
The Project concerns the integration of a groundwater heat pump unit (GWHP)
within the district heating system of “Canavese” (Milan, Italy). In light of its expertise in
cogeneration, district heating (DH) networks, and heat pump applications, A2A S.p.A (ex
AEM) has decided to exploit the significant groundwater availability in the Milan area for
energy purposes. The company started a development plan for integrating GWHPs within
part of the already existing DH generation plants, one of them being “Canavese”.
This document illustrates the project according to the geothermal specifications of
UNFC-2009.
Local and hydrogeological context
Milan is the second most populated Italian city (1.3 million residents): it is
characterized by a polycentric metropolitan area, known as “Greater Milan”, of more than
5 million people in 2,945 km2(1,651 people/km2). Milan is the main industrial, commercial,
and financial centre of Italy; the total primary energy demand for the heating of buildings
is approximately 106toe per year [1].
The city is located in northern Italy, at the centre of the largest alluvial plain of the
country (
Po valley
) in a very favourable area for groundwater exploitation. The hydrological
context is characterized by numerous rivers, together with a relevant network of artificial
channels and natural springs. Geologically, the shallow aquifer layer (up to a depth of 30 –
50 m) is composed of gravel and coarse sand that constitutes a first unconfined aquifer.
Then, a thin clay layer and a second stratum of coarse /medium sand, gravel and clay
constitute a second semi-confined aquifer up to a depth of 100-150 m. Groundwater moves
from the North and North-West (recharge area) to the South, towards the Po river. The
aquifer recharge is mainly provided by local and Alpine precipitations (880 –1,300 and
1,000 –2,200 mm/yr, respectively), together with infiltration of surface water from rivers
and channels.
Historically, the Milan area is characterized by significant groundwater pumping for
residential and industrial uses. During the seventies, several thousands of wells operated in
the area, with a maximum water production of over one billion cubic meter per year. Since
the eighties, groundwater extraction has significantly reduced, due to the transfer of
industrial activity outside the urban area. Consequently, the water level has risen, resulting
in frequent flooding of basement levels. Today, hundreds of wells operate to lower the
water table around buildings, discharging the fluid in surface channels without any
utilization. However, the water level remains at few meters deep in many parts of the city,
with associated flooding risk.
The energetic use of groundwater is continually increasing in the Milan area, also
thanks to a promoting action by the local public administration. Despite some outstanding
issues with installation authorization and operative regulation, many GWHPs have been
installed in the urban area, demonstrating the favourability and the viability of this
technology in the local context.
49

Case Study 9
Canavese plant description
The heat generation plant of Canavese represents the first Italian experience of a
groundwater heat pump coupled to a large district heating systems. The previously existing
apparatus consists of a cogeneration plant composed of three natural gas engines with a
total of 15.1 MWel installed. The total thermal power recovered by exhaust gases and
intercooling is about 13.2 MWth. A total capacity of 45.0 MWth of boilers is installed with
peaking/back-up purposes.
A 15 MWth heat pump is going to be installed in the above-described generation
system in order to exploit the abundant availability of groundwater in the area (see previous
section) with relevant benefits in terms of primary energy savings, and reduction of fossil
fuel consumption and gas emissions.
Groundwater represents the cold thermal source: it is extracted from the shallowest
aquifer by means of six wells (at a depth of 25-30 meters) at a temperature of 15°C. Nominal
flow rate and temperature drop at the evaporator are approximately 1100 m3/h and 7°C,
respectively. The disposal system comprises three injection wells together with surface
discharge in the nearby Lambro River. The pumping energy required by the ground-
coupled loop is about 15% of the energy input to the HP compressor. Nominal supply
temperature to the DH network is equal to 90°C with a temperature drop of almost 25°C in
the condenser. Thermal energy produced by the HP, heat recovery from gas engines and
back-up boilers can be directly delivered to the district heating network or it can be
accumulated in storage tanks (3,000 m3).
HP technology is based on specific expertise gained with DHs in Sweden. Under the
above-described thermal sources conditions, the HP unit is able to deliver 15 MWth with a
nominal Coefficient of Performance (COP) of 3. The conceptual scheme and the nominal
data of Canavese DH plants layout are summarized in Figure 2 and Table 1, respectively.
Quantification
Both the equipment design and the quantification of energy fluxes during the
expected operational lifetime (20 years) have been performed through a Mixed Integer
Linear Programming (MILP) optimization algorithm aimed at assessing the best design of
the system and related management. The employed objective function is the net present
value at the end of system lifetime. It results from the cumulative difference between
incomes from sales of electrical and thermal energy and installation expenditure, operating
and maintenance costs. More details on the optimization procedure can be found in [1].
The accuracy of the simulation model is related to three main factors: (a) the
prediction of the thermal load evolution during the Project lifetime (20 years); (b) the actual
deviation between nominal and operative efficiency of the heat generators (HP included);
and, (c) the actual “equivalent full load hours” of the heat generators (HP included). More
details on the simulation assumptions can be found in [1].
Product type
This Project produces two energy products: the electricity output from the CHP
engines and the heat delivered to the DH network. However, in this case, the electricity
generation is not derived from a Geothermal Energy Source. Therefore, the electrical output
does not qualify as Geothermal Energy Product, though it has an impact on the Project’s
economic evaluation.
50

Case Study 9
In this Project, there is a
hybrid
Geothermal Energy Product corresponding to the
heat
delivered to the DH network (point D in Figures 1 and 2). It is given by the combination
of the thermal energy delivered by the gas engines and back-up boilers, together with the
thermal output of the GSHP unit (point B in Figures 1 and 2).
The cumulative energy exchanged in the HP evaporator (point A in Figures 1 and 2),
corresponds to the energy extracted from the actual Geothermal Energy Source.
Reference Point
According to the definition given in Section A of the geothermal specifications,
Geothermal Energy Resources are the cumulative quantities of Geothermal Energy Products
that will be extracted from the Geothermal Energy Source. Thus, in order to exclude the
electricity generation component (which is not derived from a Geothermal Energy Source
in this case), point A should be selected as the Reference Point for reporting the true
Geothermal Energy Product and Geothermal Energy Resources.
On the other hand, it is recognized that point B may be more meaningful in terms of
what is actually delivered by the overall GSHP system, although both the product and the
resource at that location would have to be viewed as “hybrid” (i.e. only partially geothermal).
According to Figures 1 and 2, the assessment of the overall energy balance of the
Project is based on four points of evaluation in order to distinguish the energy exchanged
with the ground source (point A), the thermal output of the heat pump unit (point B), the
driven energy (point C), and the total heat delivered to the DH network (point D). Other
significant energy quantities and corresponding points of evaluations are shown in Figure
2. Points B and D refer to hybrid energy quantities given by the combination of different
forms of energy, of which only one is geothermal.
In this assessment, point A is chosen as Reference Point to report and classify the
Geothermal Energy Resources according to UNFC-2009. For clarity, all the main energy
quantities are summarized in Figure 2 and Table 2.
Figure 1
Points of reference for the assessment of GSHP projects in heating mode
51

Case Study 9
Figure 2
Simplified scheme and energy fluxes of
“Canavese”
plant
*
*
..Quantities shown are based upon a reference year of operation. The letters A, B, C and D indicate the four
points of evaluation for GSHP analysis illustrated in Figure 1. The Reference Point for the evaluation of the
Geothermal Energy Resources is highlighted in red (point A).
Table 1
Nominal capacities and efficiencies of the “Canavese” heat generation plant
Heat generator
Electrical
capacity
Electrical
efficiency Thermal capacity
Thermal
efficiency / COP
Gas engines 15.1 MWel 0.44 13.2 MWth 0.36
Heat pump
*
15.0 MWth 3
Boilers 45.0 MWth 0.9
Total 15.1 MWel 73.2 MWth
*
Delivery temperature of the DH network: 90°C.
Table 2
Energy quantities over Project lifetime (20 years) and points of evaluations
Estimate Point A* Point B* Point C* Point D*
Low estimate - - - -
Best estimate 3.5 PJ 5.3 PJ 1.8 PJ 11 PJ
High estimate - - - -
*
For location of the reference point see Figure 1 & 2.
52

Case Study 9
UNFC-2009 classification
E category classification and subclassification
Category UNFC-2009 definition Reasoning for classification
E1 Extraction and sale has been
confirmed to be economically
viable
Well testing, previous experience and
simulation results have shown the
feasibility and the viability of the Project,
also considering the regulatory framework
and the social acceptability in the Milan
area. All necessary approvals have been
confirmed by the competent authorities.
Sub-category UNFC-2009 definition
E1.1 Extraction and sale is economic
on the basis of current market
conditions and realistic
assumptions of future market
conditions
F category classification and subclassification
Category UNFC-2009 definition Reasoning f or classification
F1 Feasibility of extraction by a
defined development project or
mining operation has been
confirmed
The Project concerns the installation of a
groundwater heat pump in an already-
operative heat generation plant of a DH
network.
A2A expertise in DH design and
management, simulation results, the use
of established technologies, and the
favourable conditions of the ground
source lead to the confirmation of the
Project feasibility.
Sub-category UNFC-2009 Definition
F1.3 Sufficiently detailed studies
have been completed to
demonstrate the feasibility of
extraction by implementing a
defined development project or
mining operation.
G category classification
Category UNFC-2009 definition Reasoning for classification
G1
*
Quantities associated with a
known deposit that can be
estimated with a high level of
confidence.
The level of uncertainty of reported energy
quantities is not related to the ground
source characterization as the
hydrogeological conditions of the area have
been already assessed through the operation
of neighbouring wells for decades.
Simulation accuracy is related to the
assumptions on heat generators efficiency,
thermal load prediction, and energy prices
evolution over system lifetime.
G2
*
Quantities associated with a
known deposit that can be
estimated with a moderate
level of confidence.
Note that the classification as G1+G2 was based on the results published in [1], obtained from the
application of an optimization algorithm with project’s NPV as the objective function, and assuming only
one load scenario. A final classification, including the provision of a G1 and a G3 estimate, would be required
to provide an indication of the full range of uncertainty in the estimate.
53

Case Study 9
UNFC-2009 classification and quantification
Classification Energy Quantity Supplemental information
UNFC-2009 Class Energy quantities refer to the groundwater
HP unit only. Other significant energy
fluxes are shown in Fig. 2.
E1.1; F1.3; G1+G2 Reference Point A
*
: 3.5 PJ Nominal heating capacity of the HP unit:
15 MWth.
Nominal COP: 3.
Assumed Project lifetime: 20 years.
Ground-coupled apparatus deliver almost
50% of the total heating output of the
overall generation plant.
*
For explanations on points of reference, the reader can refer to Figures 1 and 2.
Reference
[1] Sparacino M, Camussi M, Colombo M, Carella R, Sommaruga C, “The world’s largest
geothermal district heating using groundwater under construction in Milan (ITALY): AEM
unified heat pump project”, Proceedings of EGC 2007, Unterhaching, Germany, 30 May –1
June 2007.
54

Case Study 10
Case Study 10: Vertical Ground-Coupled Heat Pump
System
Project Location: Italy
Data date: 2013
Date of evaluation: May 2015
Quantification method: Simulation
Estimate type (deterministic/probabilistic): Deterministic
Project summary
The Project concerns the installation of a Vertical Ground-Coupled Heat Pump
system (V-GCHP) in an office building located in Pisa, Italy. Both heating and cooling
services are provided. The overall Ground Source Heat Pump (GSHP) system consists of 10
vertical boreholes (BHEs), a GCHP unit, and an air-coupled heat pump (AHP) as
peaking/back-up generator. Fan coil units are used as the heat terminal unit.
This document illustrates classification of the project according to the UNFC-2009
geothermal specifications.
Reference building and thermal load
End-user thermal load shows the typical profile of office buildings located in a
Mediterranean climate, with both heating and cooling demands. The load profile was
evaluated over a typical meteorological year (TMY) [1] through a commercial dynamic
building energy simulator. The main data on the building’s thermal load are shown in
Table 1.
Table 1
Monthly heating and cooling loads for the building
Parameter Value
Annual heating demand
a
–MWh 68 (245 MJ)
Annual cooling demand
b
–MWh 80 (288 MJ)
Peak heating load –kW 40
Peak cooling load –kW 60
a
Delivery temperature of the building end-user loop: 45°C.
b
Delivery temperature of the building end-user loop: 7°C.
Ground reservoir
The ground source was investigated through a thermal response test (TRT), following
the procedure described in current technical standards [2]. The ground volumetric capacity
was assumed to equal 2.25x106 J/(m3K). Groundwater effects are negligible. The effective
thermal conductivity and diffusivity resulting from TRT are shown in Table 2.
55

Case Study 10
Ground-coupled heat exchangers (vertical borehole heat
exchangers)
BHE field is made of 10 boreholes (closed-loop) with a typical 3x3-plus-1 matrix
arrangement and double “U-tube” configuration. The borehole thermal resistance [3],
Rb
,
was evaluated using a 2D-FEM simulation. The geometrical and thermal characteristics of
the boreholes are summarized in Table 2.
Table 2
Ground thermal properties and BHEs thermal and geometrical characteristics
Parameter Value
Ground source
Ground thermal conductivity -W/(m∙K) 1.8
Ground thermal diffusivity -mm2/s 0.8
Ground-coupled heat ex changers
BHE depth – m 100
BHE diameter –cm 15
BHE configuration Double U
BHEs number 10
Spacing between boreholes [m] 10
BHE pipe diameter (outer –inner) [cm] 4 – 3.4
U shank spacing [cm] 9.5
BHE thermal resistance [m∙K/W] 0.06
Heat generators: GCHP and back-up unit
In this Project, an electrically-driven water-to-water HP with variable capacity control
units is considered as main heating and cooling generator. Nominal performance data are
shown in Table 3. The Coefficient of Performance (COP) and the Energy Efficiency Ratio
(EER) are the useful thermal power divided by power input in heating and cooling mode,
respectively.
Table 3
Nominal performances of the GCHP at rating conditions [4]
Ground-coupled unit
Heating capacity Cooling capacity COP EER
39.2 kW 58.2 kW 3.9 4
The heating and cooling back-up/peaking unit consists of an electrically-driven
air/water reversible heat pump unit with variable capacity control. Nominal performance
data are shown in Table 4.
56

Case Study 10
Table 4
Nominal performances of the AHP at rating conditions [4]
Air -coupled unit
Heating capacity Cooling capacity COP EER
11.8 kW 17.5 kW 2.6 2.7
The air unit is supposed to operate during mild months when the capacity ratio of
the GHP would be lower than the minimum allowable compressor speed (i.e. out of control
range). Consequently, the air-source HP unit operates during those months in which
outdoor temperature is sufficiently high to avoid freezing issues.
Quantification
Both the equipment design and the quantification of energy fluxes during the
operative lifetime (20 years) have been performed by an in-house model based on current
technical standards and scientific literature. More details on the simulation procedure can
be found in [3].
The accuracy of the simulation model is mainly related to the thermal load prediction
over the Project lifetime (20 years). Moreover, no ageing effects were considered in the
evaluation of equipment performance.
Product type
In this Project, there is a
hybrid
Geothermal Energy Product corresponding to the
heat delivered to the end-user system (point D in Figure 1(a)). Besides, the heat removed
during the cooling season (point D in Figure 1(b)) must also be considered, as it has a
relevant impact on the heat transfer process with the ground source (point A in Figures 1(a)
and 1(b)) and, consequently, on the Project’s technical and economic evaluations.
The contribution of the GSHP unit to the final energy product should be evaluated
at point B, both in heating and cooling mode. However, both the product and the resource
at that location would have to be regarded as “hybrid” (i.e. only partially geothermal).
Finally, the energy exchange with the Geothermal Energy Source corresponds to the heat
transfer at the ground-coupled heat exchanger (point A in Figures 1(a) and 1(b)).
Reference Point
According to Figures 1a and 1b, the assessment of the overall energy balance of the
Project is based on four points of evaluation in order to distinguish the energy exchanged
with the ground source (point A), the thermal output of the heat pump unit (point B), the
driven energy (point C), and the total heat delivered to the end-user system (point D). Points
B and D refer to
hybrid
energy quantities given by the combination of different forms of
energy, of which only one is geothermal.
Despite the advantageous effect of the summer operation in terms of Project viability
and sustainability, the actual energy extracted from the Geothermal Energy Source
corresponds only to the cumulative energy exchanged in the HP evaporator during the
heating period (point A in Figure 1(a)).
In this assessment, point A is chosen as the
Reference Point
to report and classify the
Geothermal Energy Resources according to UNFC-2009. For clarity, all the main energy
quantities are summarized in Figures 1(a) and 1(b), Table 5, and Table 6.
57

Case Study 10
Table 5
Energy quantities over Project lifetime (20 years) and corresponding points of
evaluations
Estimate Point A* Point B* Point C* Point D*
Low estimate - - - -
Best estimate
heating mode
cooling mode
3.2 TJ
5.3 TJ
4.0 TJ
4.5 TJ
0.8 TJ
0.8 TJ
4.9 TJ
5.8 TJ
High estimate - - - -
*
For location of the reference point see Figures 1(a) and 1(b).
UNFC-2009 classification
E category classification and subclassification
Category UNFC-2009 definition Reasoning for classification
E1 Extraction and sale has been
confirmed to be economically viable.
The Project is waiting for the start
of implementation. Funding has
been confirmed and there are
reasonable expectations that all
necessary approvals will be
obtained within a reasonable
timeframe.
Sub-category UNFC-2009 definition
E1.1 Extraction and sale is economic on
the basis of current market
conditions and realistic assumptions
of future market conditions.
F category classification and subclassification
Category UNFC-2009 definition Reasoning for classification
F1 Feasibility of extraction by a defined
development project or mining
operation has been confirmed
The Project relies on proven
technologies. The presence of
similar projects nearby supports the
feasibility of the Project.
Sub-category UNFC-2009 definition
F1.3 Sufficiently detailed studies have
been completed to demonstrate the
feasibility of extraction by
implementing a defined
development project or mining
operation.
58

Case Study 10
G category classification and subclassification
Category UNFC-2009 definition Reasoning for classification
G1
*
Quantities associated with
a known deposit that can
be estimated with a high
level of confidence.
The level of uncertainty of reported energy
quantities is not related to the ground source
characterization as geological conditions of
the area have already been assessed by
previous investigations and TRT. Simulation
accuracy is related to the thermal load
prediction, equipment performance
evaluation, and energy prices evolution over
system lifetime.
G2
*
Quantities associated with
a known deposit that can
be estimated with a
moderate level of
confidence.
*
Note that the classification as G1+G2 was obtained from the application of only one load scenario based
on local TMY [1] and standard gains profiles (e.g. people, electric devices etc) of office buildings. A final
classification, including the provision of a G1 and a G3 estimate, would be required to provide an indication
of the full range of uncertainty in the estimate.)
UNFC-2009 classification and quantification
Classification Energy Quantity Supplemental information
UNFC-2009
Class
Energy quantities refer to the ground-
coupled HP unit. Figures 1(a) and 1(b) show a
simplified scheme of significant energy
fluxes.
E1.1; F1.3; G1+G2 Reference Point A
*
: 3.2 TJ
(Heating mode)
Assumed Project lifetime: 20 years.
Ground-coupled apparatus delivers almost 83%
and 77% of the total heating and cooling load,
respectively.
Average COP of the ground-coupled HP unit :4;
Average EER of the ground-coupled HP unit: 5;
*
Points of reference are shown in Figures 1(a) and 1(b).
Figures 1(a) and 1(b)
Points of evaluation for the assessment of GSHP projects in heating and cooling
mode
(Figure 1(a) -Heating mode)
59

Case Study 10
(Figure 1(b) -Cooling mode)
Table 6
Main performance indexes and data of the GSHP operation (20 years)
Parameter Value
Overall primary energy consumption 7.2 TJ (2 000 MWh)
Energy delivered by GSHP in heating mode
(Point B) 4.0 TJ (1 115 MWh)
Energy removed by GSHP in cooling mode
(Point B) 4.5 TJ (1 240 MWh)
Fraction of the heating load delivered by GSHP system 0.83
Fraction of the cooling load delivered by GSHP system 0.77
<COP> of GSHP system (aux. included)* 4.26
<EER> of GSHP system (aux. included)* 3.62
<COP> of ASHP system 2.71
<EER> of ASHP system 3.16
Energy extracted from ground-source in heating mode
(Point A) 3.2 TJ (896 MWh)
Energy delivered to the ground-source in cooling mode
(Point A) 5.3 TJ (1 485 MWh)
* Overall <COP> and <EER> also include the pumping energy required in the ground-coupled loop.
References
[1] CTI. Typical Meteorological Year. Milan (IT): Italian Committee of Thermotechnics (CTI);
2012
[2] ASHRAE. Geothermal energy, in ASHRAE Handbook -HVAC Applications. Atlanta (GA):
American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE); 2011.
–34.4.
[3] Grassi W, Conti P, Schito E, Testi D. On sustainable and efficient design of ground-source
heat pump systems. Journal of Physics: Conference Series 655 (1), 012003; 2015.
[4] UNI. UNI EN 14511-2. Air conditioners, liquid chilling packages and heat pumps with
electrically driven compressors for space heating and cooling. part 2: test conditions. Milan,
2013.
60

Case Study 11
Case Study 11: Aggregation GSHP-Potential,
North Rhine Westphalia
Location state: North Rhine Westphalia (NRW), Germany
Data date: 2015
Date of evaluation: January 2016
Quantification method: Official potential study by LANUV, NRW, Germany
Estimate type (deterministic/probabilistic): Deterministic incremental
GSHP-Potential, North Rhine Westphalia, Germany, project
summary3
In 2015, the State Agency for Nature, Environment and Consumer Protection of
North Rhine Westphalia (NRW) presented an aggregated potential study for the usage of
Ground Source Heat Pump (GSHP) systems. The study assesses the potential of the GSHP
system with a maximum drill depth of 100m.
Aside from the geological potential, actual demand influences the technical limits of
using such potential. The study aggregates the potential of 3.6 million parcels of land and
compares the extractable heat and the individual demand of an existing building on that
piece of land. The evaluation is carried out in 3 steps:
(i) Calculating the geothermal energy potential of the parcel of land, which is
extractable by an optimal GSHP arrangement. The electrical power to run the
heat pump is then added to the calculated potential, using an average
Coefficient of Performance (COP)of 3.8.
(ii) Calculating the heat demand of the building(s) on this parcel (the heat sink),
depending on size, the number of floors, type of use of the building, etc.
(iii) Defining as ‘potential’ of this parcel of land which is the smaller of the two
above values. For parcels without a building, the potential is zero, as there is
no market.
To calculate the extractable heat, the area (m2), the subsurface characteristics, the
local climatic conditions and possible legal or regulatory restrictions are considered in the
study. For extraction calculations, a standardized borehole layout is assumed, which is
adapted to the size of the parcel of land under consideration, where the parcel is replaced
by an equivalent square with the same area (in m2). The area covered by a building or
buildings is excluded from the calculation.
As the first step of the aggregation, all parcels of land in NRW were researched to
decide if a GSHP system would be feasible on that parcel, and only those parcels containing
a heat sink (e.g. a building) were taken into account. Parcels of land used for traffic-
infrastructure, pieces with non-heated buildings (such as storage houses) and those in areas
with regulatory restrictions, such as water supply areas, were excluded.
In a second step, the theoretical geothermal potential for the remaining "net-owned
units" was determined, taking into account restrictions on critical hydrogeological areas
and other restricted areas, such as those with near-surface mining.
3Potenzialstudie Erneuerbare Energien NRW
Teil 4 - Geothermie
LANUV-Fachbericht 40
Landesamt für Natur, Umwelt und Verbraucherschutz Nordrhein-Westfalen.
61

Case Study 11
The theoretical usable potential was calculated on the basis of subsurface temperature
and conductivity maps available from the Geological Survey of NRW. Standard values for
double-U-tube borehole heat exchanger, diameters, filling material and working fluids were
used, with a drilling depth of 100m (40m in some restricted areas).
Finally, the heat demand (i.e. the available heat market) was quantified for each piece
of property using local climatic conditions and benchmark building characteristics. The
following categories of the building were used in the study:
•building without heating (zero heat demand)
•building for housing (standard heat demand)
•heat demand 150 kWh/m2a + hot water 15 kWh/m2a, usage hours:
2100 h/a.
•commercial buildings with higher-than-average heat demand
•heat demand 300 kWh/m2a
•commercial buildings with lower-than-average heat demand
•heat demand 75 kWh/m2a.
More details on the heat demand estimation are provided in [1].
This assessment is made only on the basis of the information publicly available and
reported in the reference below.
Quantification
The results for the 3.6 million parcels of land were aggregated at three levels, giving
quantifications at city, region and state level, respectively. The additional heat demand
potential of future new building was estimated based on the development scenarios
delivered from the cities. For simplicity, it is assumed here that the estimates associated with
old and new buildings fall all under the same E-F-G classification, therefore permitting their
aggregation (see section K, “Aggregation of quantities”, in UNFC-2009).
The aggregation results read:
•Total heat demand of existing buildings: 975 PJ /yr (271.1 TWh/y).
•Fraction of the total heat load deliverable by means of GSHPs: 533 PJ/yr (153.7
TWh/y) –this means that GSHP can satisfy 56.7% of the entire heating demand
in NRW.
•Additional heat demand for new buildings estimated to be built within the
lifetime of the project: 1.5 PJ/yr (426 GWh/y).
The values 153.7 TWh/y and 426 GWh/y are used in the commodity quantification.
The statistical lifetime of heating systems in NRW is 35 years, which is also assumed
in this study (where it is also assumed that
there are reasonable prospects for economic
extraction and sale in the foreseeable future
from old and new buildings installations). Thus,
the final energy commodity deliverable by GSHPs is 19.4 EJ, based on existing buildings
only. If the heat demand of new buildings (53.7 PJ) is additionally taken into account, then
the total deliverable heat is estimated to be almost 19.5 EJ. These values are taken as best
estimates for classification purposes.
62

Case Study 11
Product type
In this Project, the Geothermal Energy Product corresponds to the heat delivered to
the buildings (point D in Fig. 1). Both the product and the resource at that location would
have to be regarded as “hybrid” as they are given by the combination of different forms of
energy, of which only one is geothermal (point A in Fig. 1). All the reported quantities result
from the aggregation of the energy exchanged in each single Project.
Reference Point
According to Figure 1, the assessment of the overall energy balance of a GSHP system
should be based on four points of evaluation in order to distinguish the energy exchanged with
the ground source (point A), the thermal output of the heat pump unit (point B), the driven
energy (point C), and the total heat delivered to the end-user system (point D). Points B and D
refer to
hybrid
energy quantities given by the combination of the energy excreted by the
ground source (point A), the energy input at the compressor (electrically driven heat pumps are
considered), and the contribution of peaking/back-up generators.
In this assessment, point D is chosen as
Reference Point
to report and classify the
Geothermal Energy Resources according to UNFC-2009.
Figure 1
Points of reference for the assessment of GSHP projects in heating mode
UNFC-2009 classification and quantification
Classification Energy Quantity Supplemental information
UNFC-2009 Class Commodity:
Heat
E2; F1.3; G1
*
+G2
*
19.4 EJ +
53.7 PJ
End-user thermal load that can be satisfied from
GSHPs based on capacity of the individual parcels
and existing buildings. It includes electrical power
to run the heat pumps. Average COP: 3.8. The
incremental heat demand of new buildings is also
included in the estimate. The sum of the quantities
associated with existing and new buildings is
taken as best estimate.
*
Note that the classification as G1+G2 is based on a simplified evaluation of public domain information; a
final classification, including the provision of separate G1 and G3 estimates, would be required to provide an
indication of the full range of uncertainty in the estimate.
63

Case Study 11
E category classification
Category UNFC-2009 definition Reasoning for classification
E2
*
Extraction and sale is expected to
become economically viable in the
foreseeable future
The LANUV study is based on real
data gained from thousands of
drilled holes and other
information, such as data from the
official NRW cadaster. Thousands
of new wells are drilled every year.
Therefore, there are reasonable
prospects for successful
implementation in the foreseeable
future.
*
Note that a more thorough evaluation should assess the likelihood of all the buildings being built in the
foreseeable future, i.e. within 5 years from the date of the evaluation. If there are no reasonable prospects
that this will be the case, then all or part of the estimated quantities should be classified as E3 instead of E2.
F category classification and subclassification
Category UNFC-2009 definition Reasoning for classification
F1 Feasibility of extraction by a defined
development project or mining
operation has been confirmed
The NRW potential study is
regarded as a sufficiently detailed
study. Over 40 000 shallow
installations have been realized in
NRW already, with a detailed
understanding of the near surface
potential. Also, the extraction
technology is well established.
Sub-category UNFC-2009 definition
F1.3 Sufficiently detailed studies have been
completed to demonstrate the
feasibility of extraction by
implementing a defined development
project or mining operation.
G category classification
Category UNFC-2009 definition Reasoning for classification
G1 Quantities associated with a known
deposit that can be estimated with a
high level of confidence
Thousands of wells have already
been drilled in NRW and therefore
the Geothermal Energy Source
can be considered “known”. The
results of the studies are regarded
as best estimates and therefore
classified as G1+G2.
G2 Quantities associated with a known
deposit that can be estimated with a
moderate level of confidence
Reference
[1] http://www.lanuv.nrw.de/uploads/tx_commercedownloads/30040d.pdf
64

Case Study 12
Case Study 12: Pauzhetsky geothermal field
Location: Pauzhetka, Kamchatka, Russian Federation
Data date: 2016
Date of evaluation: March 2016
Quantification method: Extrapolation of production history, iTOUGH2-modelling
Estimate type (deterministic/probabilistic): Deterministic scenarios
Project summary
The development of the Pauzhetsky geothermal field located in the Kamchatka
Peninsula of Far East Russia started in 1960. In 1966, a 5 MWepower plant was put into
operation, which was replaced in 2006 by a new 6 MWeunit. The first reservoir engineering
studies of the field (Piip,1965; Sugrobov, 1970) revealed a liquid-dominated reservoir in
layered tuffs at temperatures of 170–190 oC, with hot springs discharges at 31 kg/s. The
first 10 years of exploitation at a total mass rate of 160–190 kg/s showed a gradual
temperature decline and chloride dilution in the fluids produced by wells located near the
natural discharge area. Consequently, new exploration and development wells were drilled,
and exploitation gradually shifted away from the natural discharge area until fluid
temperatures of 200–220 oC were reached. Production wells were drilled into a central
upflow zone located 1.5–2.0 km southeast of the old production field. The drop in
temperatures and enthalpies continued, while the total mass flow rate reached
220–260 kg/s between 1975 and 2006. iTOUGH2 inverse modelling (2008) help verify the
conceptual hydrogeological model of the system, to identify key parameters, and to obtain
more reliable parameter estimates and subsequent predictions. The TOUGH2 forward and
iTOUGH2 inverse modelling codes were used to calibrate a model of the Pauzhetsky
geothermal field based on natural-state and 1960–2006 exploitation data. We identified
and estimated key model parameters, i.e. geothermal reservoir fracture porosity, initial
natural upflow, base-layer porosity and the permeabilities of the hydraulic windows in the
upper layer of the model (Kiryukhin et. al., 2008).
The computed heat and mass balances helped to identify the sources for the
geothermal reserves in the field. The largest contribution comes from fluids stored in the
reservoir, followed by meteoric water recharge, base-layer upflow, and injection waters.
Model predictions for the period 2007–2032 show the possibility of maintaining steam
production at an average rate on the order of 30 kg/s (total flow rate about 290 kg/s),
provided that five additional make-up wells are put into operation, and that the steam
transmission lines from wells 122 and 131 are improved to allow a reduction in wellhead
pressures. This rate of steam production would be sufficient to support an average
electricity generation of 7MWeat the Pauzhetsky power plant (Kiryukhin et al, 2008, 2014).
In view of the above, the distribution of development steam reserves (at separation
pressure 2.9 bars) for the Pauzhetka geothermal field was approved by Protocol of the
Federal Subsoil Resources Management Agency of the Russian Federation (ROSNEDRA)
number 1606, 6 May 2008 (A+B+C1 category 25.4 kg/s, including A+B category 14.1 kg/s
(56%), C1 category 11.3 kg/s (44%).
The calibrated model used for estimating overall reservoir behaviour under future
production scenarios (Kiryukhin et al, 2014). The inflow of meteoric water is characteristic
for the Pauzhetka field; this water makes up 30% of the total extracted fluid, which is
observed not only in former areas of thermal discharge but primarily (75%) in the area of
abandoned wells in the P. Pauzhetka river, where no naturally occurring discharge was
observed prior to the beginning of extraction. From this it follows that some (poorly
cemented) abandoned wells can conduct meteoric waters into the reservoir, cooling the
productive zone and exerting a negative effect on the extraction parameters. Modelling the
65

Case Study 12
operation of this field showed that the total steam productivity could be enhanced by 23.2%
by isolating such artificial infiltration zones, so that the available power output of the station
would require fewer extra wells.
With the turbines used at the Pauzhetka power plant consuming 4.03 kg/s steam per
1 MW of electrical energy as approved at the GKZ for the Central area of the Pauzhetka
geothermal field, the development reserves are sufficient to produce 6.3 MW of electrical
energy. We note that it is possible to use more effective technologies of heat carrier
utilization, e.g., those for the East Mesa power plant (37 MW of electrical energy). Here a
double boiling cycle is used with 1070 kg/s heat carrier and an enthalpy of 689 kJ/kg (the
data are for the East Mesa power plant in 2006); the carrier is utilized to derive 59.8 kg/s
steam first at a separation pressure of 3.14 bars for the first cycle, the separated water
(1010.2 kg/s) is then used to get 56.89 kg/s more steam at a pressure of 1.15 bars for the
second cycle. It follows that the specific steam consumption per 1 MW of electrical energy
is equal to 1.62 kg/s at a pressure of 3.14 bars plus 1.54 kg/s at a pressure of 1.15 bars (a
Modular 25 Mitsubishi turbine). With this technology, the Pauzhetka geothermal field
would be capable of producing 11.2 MW from the operating producing wells.
Relevant project parameters are as follows:
•Extraction two-phase flow rate: 288 kg/s
•Steam rate at average separation pressure 2.9 bars (sustainable production
for next 17 years has been confirmed by simulation results): 25.4 kg/s
•Conversion rate for current turbines: 4.03 kg/s steam per 1 MWe
•Annual existing single-flash power plant ouput: 4.2 MWe(2 x 6 MWeinstalled
capacity)
•Potential conversion for binary power plant at 1.15 bars separation pressure
: 11.2 MWe
•Potential steam production enhancement by 23.2% by isolating such artificial
infiltration zones
•Rejected water from existing power plant: 252.6 kg/s at 132 oC (2008)
•Remaining project lifetime: 17 years
•Total available energy amount: 2.25 PJ (4.2 MWex 17 years).
Quantification
Electricity
Quantification of recoverable steam for the existing 6 MWepower plant capacity
during the next 17 years was based on existing production wells (56%) and projected
additional five productions wells (44%). Minimization of the cold water inflow into
production reservoir may yield 23% more electricity production.
In the case of a switch from single-flash to binary technology, an 87% increase in
electricity production is possible.
66

Case Study 12
Heat
Quantification of recoverable heat is based on the minimum value of two: (1) Potential
heat demand for the district heating system Ozernovsky settlement, that is 15.0 MWth (or 0.27
PJ) annually (with heating system inlet/outlet temperature: 110°C/45°C). The value above was
estimated using the Paratunsky settlement operating district geothermal heating system as
analog; (2) Rejected water after electricity power plant, that is defined by the mass rate of
252.6 kg/s at 132 oC (2008).
The remaining lifetime is 17 years.
Product type
There are two Energy Products: electricity and heat.
Reference Point
The reference point for electricity is the station switchyard, where gross power is
exported to Ozeranaya settlement and fishery plant.
The reference point for potential heat export is the metering point for the heat
distribution system in Ozernaya settlement.
Geothermal Energy Resources
Electricity for single-flash power plant
Electricity for single-flash power plant:
•Low estimate: 1.82 PJe(3.4 MWex 17 years)
•Best estimate: 3.21 PJe(6.0 MWex 17 years)
•High Estimate: 3.94 PJe(7.4 MWex 17 years)
Possible Electricity for binary power plant
Possible Electricity for binary power plant:
•Low estimate: 3.40 PJe(6.3 MWex 17 years)
•Best estimate: 5.99 PJe(11.2 MWex 17 years)
•High estimate: 7.37 PJe(13.8 MWex 17 years)
Heat
Heat:
•Low estimate: 20.7 PJth (38.6 MWth x 17 years)
•Best estimate: 36.9 PJth (68.7 MWth x 17 years)
•High estimate: 45.4 PJth (84.8 MWth x 17 years)
67

Case Study 12
UNFC-2009 classification
Classification Energy Quantity Supplemental information
UNFC-2009
Class
Commodity:
Electricity
The Pauzhetsky plant has generated electricity
continuously since 1966. Expected remaining lifetime: 17
years.
E1.1;F1.1; G1 1.82 PJeConservative estimate based on 44% reduction in
availability due to production wells decline.
E1.1;F1.1; G2 1.39 PJeIncremental energy based on continued output from
existing production wells and in case of five additional
make-up wells will be drilled.
E1.1;F1.1; G3 0.73 PJeIncremental energy based on continued output from
existing production wells, in case of five additional
make-up wells will be drilled and in case of isolating
artificial infiltration cold water zone.
E category classification and subclassification
Category UNFC-2009 definition Reasoning for classification
E1 Extraction and sale is
economic on the basis of
current market conditions and
realistic assumptions of future
market conditions.
Plant is now commercially producing for
the Ozernaya settlement and fishery
processing plant through a market
scheme guaranteed for the life of the
plant.
Sub-category UNFC-2009 definition
E1.1 Extraction and sale is
economic on the basis of
current market conditions and
realistic assumptions of future
market conditions.
F category classification and subclassification
Category UNFC-2009 definition Reasoning for classification
F1 Feasibility of extraction by a
defined development project
or mining operation has been
confirmed.
Energy is being successfully extracted and
converted to electricity at the required
commercial rate.
Sub-category UNFC-2009 definition
F1.1 Extraction is currently taking
place.
68

Case Study 12
G category classification and subclassification
Category UNFC-2009 def inition Reasoning for classification
G1 Quantities associated with a
known deposit that can be
estimated with a high level
of confidence.
The system is currently producing. Production
wells maintain total mass flow rate 220–260
kg/s since 1975. The TOUGH2 forward and
iTOUGH2 inverse modelling codes were used
to calibrate a model of the Pauzhetsky
geothermal field based on natural-state and
1960–2006 exploitation data.
Thus, the Pauzhetsky Geothermal Energy
Source can be considered “known” and all
resources are classified as G1, G2 and G3.
While modelling has given a high level of
confidence that 56% of the steam production
rate will be sustained from existing production
wells over the life of the plant (G1), there is
uncertainty in the availability of the rest 44%
steam production, which requires additional
five make-up wells drilling (G2).
The inflow of meteoric water from some
(poorly cemented) abandoned wells can
conduct meteoric waters into the reservoir,
cooling the productive zone and exerting a
negative effect on the extraction parameters.
Modelling the operation of this field showed
that the total steam productivity could be
enhanced by 23.2% by isolating such artificial
infiltration zones (G3).
G2 Quantities associated with a
known deposit that can be
estimated with a moderate
level of confidence.
G3 Quantities associated with a
known deposit that can be
estimated with a low level of
confidence.
Classification Energy Quantity Supplemental information
UNFC-2009
Class
Commodity:
Electricity
The Pauzhetsky plant could generate
additional electricity if the switch from single-
flash to binary technology would be
implemented.
E2;F1.3; G1 3.40 PJeConservative estimate based on 44%
reduction in availability due to existing
production wells decline.
E2;F1.3; G2 2.59 PJeIncremental energy based on continued
output from existing production wells and in
case of five additional make-up wells will be
drilled.
E2;F1.3; G3 1.38 PJeIncremental energy based on continued
output from existing production wells, in case
of five additional make-up wells will be drilled
and in case of isolating artificial infiltration
cold water zone.
69

Case Study 12
E category classification and subclassification
Category UNFC-2009 definition Reasoning for classification
E2 Extraction and sale is expected
to become economically viable
in the foreseeable future.
There is a reasonable likelihood that switch
from single-flash to binary technology will be
implemented in the foreseeable future.
F category classification and subclassification
Category UNFC-2009 definition Reasoning for classification
F1 Feasibility of extraction by a
defined development project
or mining operation has
been confirmed
With binary technology, the Pauzhetka
geothermal field would be capable of
producing 11.2 MW from the operating
producing wells and additional make-up wells
during the next 17 years operational life time.
Sub-category UNFC-2009 definition
F1.3 Sufficiently detailed studies
have been completed to
demonstrate the feasibility of
extraction by implementing a
defined development project
or mining operation.
G category classification and subclassification
Category UNFC-2009 definition Reasoning for classification
G1 Quantities associated with a
known deposit that can be
estimated with a high level of
confidence.
The system is currently producing. Production wells
maintain total mass flow rate 220–260 kg/s since
1975. The TOUGH2 forward and iTOUGH2 inverse
modelling codes were used to calibrate a model of
the Pauzhetsky geothermal field based on natural-
state and 1960–2006 exploitation data.
Thus, the Pauzhetsky Geothermal Energy Source can
be considered “known” and all resources are
classified as G1, G2 and G3.
While modelling has given a high level of confidence
that 56% of the steam production rate will be
sustained from existing production wells over the life
of the plant (G1), there is uncertainty in the
availability of the rest 44% steam production, which
requires additional five make-up wells drilling (G2).
The inflow of meteoric water from some (poorly
cemented) abandoned wells can conduct meteoric
waters into the reservoir, cooling the productive
zone and exerting a negative effect on the extraction
parameters. Modelling the operation of this field
showed that the total steam productivity could be
enhanced by 23.2% by isolating such artificial
infiltration zones (G3).
G2 Quantities associated with a
known deposit that can be
estimated with a moderate
level of confidence.
G3 Quantities associated with a
known deposit that can be
estimated with a low level of
confidence.
70

Case Study 12
Classification Energy Quantity Supplemental information
UNFC-2009
Class
Commodity:
Heat
The construction of a district heating network in the
Ozernovsky settlement (2,000 people) and Fishery
plant is currently in the planning phase.
E2;F1.3; G1 8.03 PJht Minimum rejected water mass rate after electricity PP,
that is defined during the rest of the project lifetime
(17 years) is 136.4 kg/s at 132 oC (G1) is more than
the heat demand from the district heating network,
that is 15 MWht annually.
E category classification and subclassification
Category UNFC-2009 definition Reasoning for classification
E2 Extraction and sale is expected
to become economically viable
in the foreseeable future.
There is a reasonable likelihood that
construction of a district heating network in
Ozernaya settlement (2,000 people) and
Fishery plant will be implemented in the
foreseeable future.
F category classification and subclassification
Category UNFC-2009 definition Reasoning for classification
F1 Feasibility of extraction by a
defined development project
has been confirmed.
A district heating network at Ozernovsky
settlement is currently in the planning phase.
The technology has already been
demonstrated at analogous projects within
the Paratunsky Graben.
Sub-category UNFC-2009 definition
F1.3 Sufficiently detailed studies
have been completed to
demonstrate the feasibility of
extraction by implementing a
defined development project.
G category classification and subclassification
Category UNFC-2009 definition Reasoning for classification
G1 Quantities associated with a known
deposit that can be estimated with a
high level of confidence.
Minimum rejected water mass rate
after electricity PP, that is defined
during the rest of the project lifetime
(17 years) is 136.4 kg/s at 132 oC(G1)
G2 Quantities associated with a known
deposit that can be estimated with a
moderate level of confidence.
G3 Quantities associated with a known
deposit that can be estimated with a
low level of confidence.
71

Case Study 12
References
Kiryukhin A.V., Asaulova N.P., Finsterle S. Inverse modelling and forecasing for the
exploitation of the Pauzhetsky geothermal field, Kamchatka, Russia, Geothermics, V. 37, p.
540-562, 2008.
А.В.Кирюхин, Н.П. Асаулова, Ю.Ф. Манухин, Т.В. Рычкова, В.М. Сугробов ИСПОЛЬЗОВАНИЕ
ЧИСЛЕННОГО МОДЕЛИРОВАНИЯ ДЛЯ ОЦЕНКИ ЭКСПЛУАТАЦИОННЫХ ЗАПАСОВ
МЕСТОРОЖДЕНИЙ ПАРОГИДРОТЕРМ (на примере Паужетского геотермального
месторождения) // Вулканология исейсмология, №1, 2010, с.56-76.
A.V. Kiryukhin, N.P. Asaulova, Yu.F. Manukhin, T.V. Rychkova, V.M. Sugrobov, Using
Numerical Modelling for Assessing the Recoverable Reserves of a Geothermal Steam Field:
The Pauzhetka Geothermal Field. 2010, published in Vulkanologiya i Seismologiya, 2010,
Vol. 4, No. 1, pp. 56–71.
А.В. Кирюхин, Н.П. Асаулова, О.Б. Вереина, А.Ю. Поляков ОЦЕНКА ВЛИЯНИЯ ИНФИЛЬТРАЦИИ
ПРИ ЭКСПЛУАТАЦИИ ВЫСОКОТЕМПЕРАТУРНЫХ ГЕОТЕРМАЛЬНЫХ МЕСТОРОЖДЕНИЙ
(ПАУЖЕТСКОГО ИМУТНОВСКОГО МЕСТОРОЖДЕНИЙ, КАМЧАТКА, РОССИЯ) // «Вулканология
исейсмология», 2014, №3, с.24-36.
A.V. Kiryukhin, N.P. Asaulova, O.B. Vereina, A.Yu. Polyakov Estimating the Influence of
Filtering during the Operation of the Pauzhetka and Mutnovskii High_Temperature
Geothermal Fields, Kamchatka, Russia// Journal of Volcanology and Seismology, 2014, Vol.
8, No. 3, pp. 156–167.
72

Case Study 13
Case Study 13: Krafla Geothermal Field
Project Location: Krafla, Iceland
Data date: 2016
Date of evaluation: September 2016
Quantification method: Simulation
Estimate type (deterministic/probabilistic): Deterministic
Project summary
The Krafla region in north-east Iceland, located in the North Atlantic Rift Zone, has long
been known for its volcanic and geothermal activity. The first geothermal research study of
the area was conducted in 1969. Aeromagnetic maps were produced and the geothermal
system was estimated to be at 200–300°C. During 1971 and 1972, resistivity surveying was
conducted and the first two exploration wells were subsequently drilled in 1974. The decision
to build a 60 MW power plant was made that same year and construction started in 1975.
Concurrently the 1975–1984 Krafla volcanic episode (Krafla Fires) started.
Ongoing exploration of the Krafla reservoir revealed an unusually complex system.
The conceptual model for the reservoir is divided into several compartments that differ
greatly e.g. in terms of temperature, enthalpy, fluid chemistry and permeability. This
complexity, along with the Krafla Fires and market-related issues, caused considerable delay
in project completion. The power plant started production of 7 MW in 1978, climbing to 30
MW in 1984. Finally, the second turbine started operation in 1999, bringing the total
production capacity to 60 MW (Weisenberger et. al., 2015).
Historical overview of the Krafla geothermal power plant in the Krafla geothermal system (Weisenberger
et. al., 2015).
73

Case Study 13
Today (2016) the Krafla power plant is run by Landsvirkjun (National Power Company
of Iceland) and at a capacity of 60 MWe(net) with steam maintenance from workovers and
occasional drilling of make-up wells. The project reported here is based on an assumption
of continued operation for the next 30 years, with continued steam supply coming from
make-up wells. A total of 42 wells have been drilled in the field at this time, although the
plant is run on only half of those wells. Some of the wells that are not utilized have been
abandoned, while others have revealed unexploited and potentially favourable parts of the
resource and could be utilized for the current power plant.
No permitting or regulatory issues are expected to constrain continued operation in
the area. Thus, for the purpose of this example, the simplification is made that the project
lifetime is determined by the estimated depreciation time of the power plant. Landsvirkjun
has investigated some options for expanding the power plant, adding topping stations and
bottoming cycles, but none of those are being considered in the project reported here.
A TOUGH2 reservoir simulation model has been set up to investigate plausible 30
year production scenarios and predict at what point declining reservoir productivity might
halt further steam maintenance operations. This reservoir model was based on the revised
conceptual model of Weisenberger et. al. (2015) along with the production history recorded
over the past four decades. The model was created with relatively low gridblock resolution,
as it was meant as a preliminary model for estimating the production capacity of the
peripheral zones of the currently utilized area.
In an effort to quantify the uncertainty in predictions based on the simulation model,
some experimentation was carried out to produce optimistic and pessimistic versions of
the model without much compromise in the fit to available data (Berhet et al., 2016a). Each
of the three versions of the model (pessimistic, base case and optimistic) were then used
to simulate production from the reservoir throughout the project lifetime. In these
simulation scenarios, an automated test was carried out before adding each make-up well
to investigate whether the investment would provide sufficient payback to justify drilling
the well. If this test revealed that the make-up well should not be drilled, then all make-up
well drilling was abandoned and the production of the power plant was allowed to decline
until the end of the project lifetime.4
This assessment was made largely with publicly available information, but with
assumptions regarding economic factors that were not readily available at the time of this
study.
Quantification
Forecast runs (Þorvaldsson et al., 2016) showed that for the current utilization at
Krafla (60 MWe(net) power plant, max production capacity 63 MWe(net)) make-up wells
would continue to be drilled for:
•10 years for the pessimistic case,
•19 years for the base case,
•18 years for the optimistic case.
4In this simple example (created specifically for the UNFC project), it was assumed that each well cost
7.5 m$ (includes associated cost e.g. for failed wells and steam gathering), the energy price was fixed
at 43 $/MWh and a discount rate of 10% per annum was used. Technically, the decision to drill a
make-up well would also be influenced by other items such as O&M cost, opportunity cost of not
fully utilizing the investment in well and the power plant capacity, possible variability in energy price,
well productivity etc. These items were not considered, however, in this example case study.
74

Case Study 13
The cumulative energy produced over the project lifetime for each of these scenarios
amounts to:
•55.1 PJ for the pessimistic case,
•56.5 PJ for the base case,
•57.5 PJ for the optimistic case.
Future production scenarios for utilization of the Krafla geothermal field (Þorvaldsson et. al., 2016).
The quantification estimate derives from a reservoir simulation model as described
in the Project Summary. This is a deterministic assessment, with three separate
development plans tested, each corresponding to given assumptions about uncertain key
parameters in the model. The simulation method takes into account the interplay between
uncertain properties of the reservoir and economic constraints on drilling of make-up wells.
This is what leads to the variability in total energy production over the project lifetime,
which in this case is relatively low (within 2.5% of the base case estimate).5
The economic assumptions in the model are for the operation of a dual-flash
geothermal power station supplying power onto Iceland’s national grid. The developer is
an electricity generator and wholesaler with market access via the grid.
Product type
The product produced is electricity.
Reference Point
The reference point is at the station switchyard, where power is exported into the
national grid. Internal power use has already been subtracted.
5Note that the uncertainty in the reservoir parameters also leads to considerable variability in the
future profitability of the project. This variability, however, is not reported as part of the UNFC.
75

Case Study 13
UNFC-2009 classification
E category classification and subclassification
Category UNFC-2009 definition Reasoning f or classification
E1 Extraction and sale has been
confirmed to be economically
viable
The project has been operating since
1978, and has produced at the current
60 MW capacity since 1999.
No barriers to continued extraction are
foreseeable at the time of this
assessment.
Sub-category UNFC-2009 definition
E1.1 Extraction and sale is economic
on the basis of current market
conditions and realistic
assumptions of future market
conditions
F category classification and subclassification
Category UNFC-2009 definition Reasoning f or classification
F1 Feasibility of extraction by a
defined development project or
mining operation has been
confirmed
The project is already operating and
selling energy to the Icelandic national
grid.
Sub-category UNFC-2009 definition
F1.1 Extraction is currently taking
place.
G category classification and subclassification
Category UNFC-2009 def inition Reasoning f or classification
G1 Quantities associated with a
known deposit that can be
estimated with a high level of
confidence.
Quantification was based on a TOUGH2
reservoir simulation model that was
populated with parameters that fit the
available data, but lead to low recoverability
estimates where data is lacking.
G2 Quantities associated with a
known deposit that can be
estimated with a moderate level
of confidence.
Quantification was based on a TOUGH2
reservoir simulation model that was
populated with parameters that fit the
available data, but lead to moderate
recoverability estimates where data is lacking.
G3 Quantities associated with a
known deposit that can be
estimated with a low level of
confidence.
Quantification was based on a TOUGH2
reservoir simulation model that was
populated with parameters that fit the
available data, but lead to high recoverability
estimates where data is lacking.
76

Case Study 13
UNFC-2009 Geothermal Energy Resources
Classification:
UNFC-2009
Class Energy Quantity Supplemental information
E1.1; F1.1; G1 55.1 PJ Pessimistic reservoir model –60 MWeuntil
make-up well drilling is halted in year 10
E1.1; F1.1; G2 1.4 PJ Base case reservoir model –60 MWeuntil
make-up well drilling is halted in year 19
E1.1; F1.1; G3 1.0 PJ Optimistic reservoir model –60 MWeuntil
make-up well drilling is halted in year 18
References
Jean-Claude Berthet, Valdís Guðmundsdóttir, Gunnar Þorgilsson, Andri Arnaldsson, 2016a,
“Simulation of the Krafla geothermal system -Resource assessment of shallow peripheral
zones”, Vatnaskil 16.02, ISOR-2016/011. Available at
http://gogn.lv.is/files/2016/simulation_of_krafla_geothermal_system.pdf
Lárus Þorvaldsson, Jean-Claude Berthet, Andri Arnaldsson, 2016b, “Energy extraction in 60
MWeand 110 MWeKrafla scenarios”, Vatnaskil Memo No. 16.14. Available at
http://gogn.lv.is/files/2016/krafla_UNFC_memo.pdf
Tobias Björn Weisenberger, Guðni Axelsson, Andri Arnaldsson, Anett Blischke, Finnbogi
Óskarsson, Halldór Ármannsson, Hanna Blanck, Helga Margrét Helgadóttir, Jean-Claude C.
Berthet, Knútur Árnason, Kristján Ágústsson, Sigríður Sif Gylfadóttir and Valdís
Guðmundsdóttir, 2015, “Revision of the Conceptual Model of the Krafla Geothermal
System”, ÍSOR-2015/012, Vatnaskil 15.03, LV-2015-040. Available at
http://www.landsvirkjun.is/Media/2015-040.pdf.
77

Case Study 14
Case Study 14: Krafla Geothermal Field –
50 MW Power Expansion
Project Location: Krafla, Iceland
Data date: 2016
Date of evaluation: September 2016
Quantification method: Simulation
Estimate type (deterministic/probabilistic): Deterministic
Project summary
The Krafla region in north-east Iceland, located on the North Atlantic Rift Zone, has
long been known for its volcanic and geothermal activity. The first geothermal research study
of the area was conducted in 1969. Aeromagnetic maps were produced and the geothermal
system was estimated to be at 200–300°C. During 1971 and 1972, resistivity surveying was
conducted and the first two exploration wells were subsequently drilled in 1974. The decision
to build a 60 MW power plant was made that same year and construction started in 1975.
Concurrently the 1975–1984 Krafla volcanic episode (Krafla Fires) started.
Ongoing exploration of the Krafla reservoir revealed an unusually complex system.
The conceptual model for the reservoir is divided into several compartments that differ
greatly e.g. in terms of temperature, enthalpy, fluid chemistry and permeability. This
complexity, along with the Krafla Fires and market-related issues, caused considerable delay
in project completion. The power plant started production of 7 MW in 1978, climbing to 30
MW in 1984. Finally, the second turbine started operation in 1999, bringing the total
production capacity to 60 MW (Weisenberger et. al., 2015).
Historical overview of the Krafla geothermal power plant in the Krafla geothermal system
(Weisenberger et. al., 2015).
78

Case Study 14
Today (2016), the Krafla power plant is run by Landsvirkjun (National Power Company
of Iceland) and at a capacity of 60 MWe(net) with steam maintenance from workovers and
occasional drilling of make-up wells. The project reported here is based on plans for
expanded electrical power generation capacity of 50 MW. It is assumed that the new power
station would run alongside the current 60 MW power station for the next 30 years, with
continued steam supply coming from make-up wells. A total of 42 wells have been drilled
for the current station, although the plant is run on only half of those wells. Some of the
wells that are not utilized have been abandoned, while others have revealed unexploited
and potentially favourable parts of the resource.
Some permitting issues for the expansion are yet to be addressed, but these are not
expected to impact the viability of the project heavily. Market prices and demand for
electricity in Iceland are favourable for the proposed expansion, although there is some
uncertainty about whether the national power grid will need to be upgraded to bring the
power to market. Thus, for the purpose of this example, the simplification was made that
the project lifetime was determined by the estimated depreciation time of the new power
station. The power station being considered for the project reported here is a single-flash
power cycle with evaporative cooling.
A TOUGH2 reservoir simulation model has been set up to investigate plausible
30-year production scenarios and predict at what point declining reservoir productivity
might halt further steam maintenance operations. This reservoir model was based on the
revised conceptual model of Weisenberger et. al. (2015) along with the production history
recorded over the past four decades. The model was created with relatively low gridblock
resolution, as it was meant as a preliminary model for estimating the production capacity
of the peripheral zones of the currently utilized area.
In an effort to quantify uncertainty in the predictions some experimentation was carried
out to produce optimistic and pessimistic versions of the model without much compromise in
the fit to available data (Berhet et al., 2016a). Each of the three versions of the model (pessimistic,
base case and optimistic) were then used to simulate production from the reservoir throughout
the project lifetime. In these simulation scenarios, an automated test was carried out before
adding each make-up well to investigate whether the investment would provide sufficient
payback to justify drilling the well. If this test revealed that the make-up well should not be
drilled, then all make-up well drilling was abandoned and the production of the power plant
was allowed to decline throughout the project lifetime.6
This assessment was made largely with publicly available information, but with
assumptions regarding economic factors that were not readily available at the time of this study.
Quantification
Forecast runs (Þorvaldsson et al., 2016) showed that for the expanded utilization at
Krafla (110 MWe(net) total power generation, max production capacity 115,5 MWe(net))
make-up wells would continue to be drilled for:
•14 years for the pessimistic case,
•23 years for the base case,
•23 years for the optimistic case.
6In this simple example (created specifically for the UNFC project), it was assumed that each well cost
7.5 m$ (includes associated cost e.g. for failed wells and steam gathering), the energy price was fixed
at 43 $/MWh and a discount rate of 10% per annum was used. Technically, the decision to drill a
make-up well would also be influenced by other items such as O&M cost, opportunity cost of not
fully utilizing the investment in well and the power plant capacity, possible variability in energy price,
well productivity etc. These items were not considered, however, in this example case study.
79

Case Study 14
The cumulative energy produced from the 50 MW expansion is computed by
subtracting the estimated production of the current 60 MW plant (as reported in Case Study
13) from the total energy produced over the project lifetime. This leads to:
•44.9 (100.0-55.1) PJ for the pessimistic case,
•46.9 (103.4-56.5) PJ for the base case,
•47.5 (105.0-57.5) PJ for the optimistic case.
Future production scenarios for expanded utilization of the Krafla geothermal field (Þorvaldsson
et. al., 2016).
The quantification estimate derives from a reservoir simulation model as described
in the Project Summary. This is a deterministic assessment, with three separate
development plans tested, each corresponding to given assumptions about uncertain key
parameters in the model. The simulation method takes into account the interplay between
uncertain properties of the reservoir and economic constraints on drilling of make-up wells.
This is what leads to the variability in total energy production over the project lifetime,
which in this case is within 4.5% of the base case estimate.7
The economic assumptions in the model are for the operation of a new 50 MW
single-flash geothermal power plant. Electricity will be supplied into Iceland’s national grid.
The developer is an electricity generator and wholesaler with market access via the grid.
Product type
The product produced is electricity.
Reference Point
The reference point is at the station switchyard, where power is exported into the
national grid. Internal power use has already been subtracted.
7Note that the uncertainty in the reservoir parameters also leads to considerable variability in the
future profitability of the project. This variability, however, is not reported as part of the UNFC.
80

Case Study 14
UNFC-2009 classification
E category classification and subclassification
Category UNFC-2009 definition Reasoning for classification
E2 Extraction and sale is
expected to become
economically viable in the
foreseeable future.
Extraction has been ongoing in the Krafla
area since 1978. Continued exploration and
maintenance of the field has indicated that
the resource would be sufficiently large to
support expanded production capacity.
There is still some uncertainty regarding
permitting issues, market access and
electricity price. At the moment, however, it
is realistic to assume that these matters will
be resolved such that economic extraction
can take place.
F category classification and subclassification
Category UNFC-2009 definition Reasoning for classification
F2 Feasibility of extraction by a
defined development project
or mining operation is subject
to further evaluation.
The data gathered from the current
utilization of the field underpins a model for
the reservoir that indicates a favorable
resource.
More detailed economic studies are
required, however, to determine whether the
power station should be constructed with
the assumed project configuration. Such
studies are underway at this time.
Sub-category UNFC-2009 definition
F2.1 Project activities are ongoing
to justify development in the
foreseeable future.
G category classification and subclassification
Category UNFC-2009 def inition Reasoning for classification
G1 Quantities associated with a
known deposit that can be
estimated with a high level of
confidence.
Quantification was based on a TOUGH2
reservoir simulation model that was
populated with parameters that fit the
available data, but lead to low recoverability
estimates where data is lacking.
G2 Quantities associated with a
known deposit that can be
estimated with a moderate
level of confidence.
Quantification was based on a TOUGH2
reservoir simulation model that was
populated with parameters that fit the
available data, but lead to moderate
recoverability estimates where data is lacking.
G3 Quantities associated with a
known deposit that can be
estimated with a low level of
confidence.
Quantification was based on a TOUGH2
reservoir simulation model that was
populated with parameters that fit the
available data, but lead to high recoverability
estimates where data is lacking.
81

Case Study 14
UNFC-2009 Geothermal Energy Resources
Classification:
UNFC-2009
Class Energy Quantity Supplemental information
E2; F2.1; G1 44.9 PJ Pessimistic reservoir model –50 MWe
expansion until make-up well drilling is
halted in year 14
E2; F2.1; G2 2.0 PJ Base case reservoir model –50 MWeuntil
make-up well drilling is halted in year 23
E2; F2.1; G3 0.6 PJ Optimistic reservoir model –60 MWeuntil
make-up well drilling is halted in year 23
References
Jean-Claude Berthet, Valdís Guðmundsdóttir, Gunnar Þorgilsson, Andri Arnaldsson, 2016,
“Simulation of the Krafla geothermal system -Resource assessment of shallow peripheral
zones”, Vatnaskil 16.02, ISOR-2016/011. Available at
http://gogn.lv.is/files/2016/simulation_of_krafla_geothermal_system.pdf
Lárus Þorvaldsson, Jean-Claude Berthet, Andri Arnaldsson, 2016, “Energy extraction in 60
MWeand 110 MWeKrafla scenarios”, Vatnaskil Memo No. 16.14. Available at
http://gogn.lv.is/files/2016/krafla_UNFC_memo.pdf
Tobias Björn Weisenberger, Guðni Axelsson, Andri Arnaldsson, Anett Blischke, Finnbogi
Óskarsson, Halldór Ármannsson, Hanna Blanck, Helga Margrét Helgadóttir, Jean-Claude C.
Berthet, Knútur Árnason, Kristján Ágústsson, Sigríður Sif Gylfadóttir and Valdís
Guðmundsdóttir, 2015, “Revision of the Conceptual Model of the Krafla Geothermal
System”, ÍSOR-2015/012, Vatnaskil 15.03, LV-2015-040. Available at
http://www.landsvirkjun.is/Media/2015-040.pdf.
82

UNECEUNITED NATIONS
Application of the UNFC to Geothermal Energy Resources - Selected case studies
Palais des Nations
CH - 1211 Geneva 10, Switzerland
Telephone: +41(0)22 917 44 44
E-mail: info.ece@unece.org
Website: http://www.unece.org
Information Service
United Nations Economic Commission for Europe
This publication includes a set of 14 case studies on the application of the United
Nations Framework Classiÿcation for Resources (UNFC) to geothermal energy from
Australia, Germany, Hungary, Iceland, Italy, the Netherlands, New Zealand, the
Philippines and Russian Federation.
UNFC, which has been developed by the Expert Group on Resource Classiÿcation of
the United Nations Economic Commission for Europe (UNECE), applies to all energy
and mineral resources globally. This includes renewable energy resources,
anthropogenic resources and injection projects for the geological storage of carbon
dioxide.
UNFC can be applied to geothermal energy through two sets of Speciÿcations for the
application of UNFC to Renewable Energy Resources and Geothermal Energy
Resources developed in 2016.
The case studies are presented here to illustrate the application of the geothermal
energy speciÿcations for the uniform use of UNFC in di°erent contexts.
These application examples from di°erent countries provide a range of scenarios in
the classiÿcation of geothermal resources in a manner consistent with the
classiÿcation of other energy resources.
Selected case studies
Application of the United Nations
Framework Classication for Resources (UNFC)
to Geothermal Energy Resources
UNECE Energy Series
Application of the United Nations
Framework Classication for Resources (UNFC)
to Geothermal Energy Resources
Selected case studies
Layout and Printing at United Nations, Geneva – 1734615 (E) – November 2017 – 3,518 – ECE/ENERGY/110
ISBN 978 -92-1-117136-5