Geo4P - Geothermal Pilot Project Pisan Plain: quantitative assessment of very low, low and medium temperature shallow geothermal resources

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European Geothermal Congress 2016
Strasbourg, France, 19-24 Sept 2016
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Geo4P - Geothermal Pilot Project Pisan Plain: quantitative assessment of very
low, low and medium temperature shallow geothermal resources
Alessandro Sbrana1, Giuseppe Pasquini1, Paola Marianelli1, Dario Bonciani2, 3 and Loredana
Torsello2, 3
1 University of Pisa, Dipartimento di Scienze della Terra, via Santa Maria 53, 56126, Pisa, Italy
2 EnerGea, via G.Carducci 4, 56044, Larderello (PI), Italy
3Co.Svi.G. via T. Gazzei 89, 53030, Radicondoli (SI), Italy
alessandro.sbrana@unipi.it
Keywords: geothermal exploration, 3D modelling,
Pisan plain, renewable heating and cooling,
multidisciplinary approach.
ABSTRACT
This paper presents the first results of an integrated
geothermal research project. Geo4P (Geothermal –
Pilot Project Pisan Plain) is started in July 2014 for the
development of a multidisciplinary methodology,
aimed at carrying out a quantitative assessment of low
temperature shallow geothermal resources in Pisa
plain. The ultimate aim is to produce a tool useful to
enhance the use of geothermal heat pumps in heating
and cooling plants, for public utilities. Concerning
geological and geothermal researches, 3D integrated
subsoil models are produced within Geo4P, whereas
3D results are implemented in thermo-fluid dynamic
simulations in order to increase the thermal knowledge
of the subsurface.
1. INTRODUCTION
The aim of this project is to develop an innovative
multidisciplinary approach, including geological,
geochemical, geophysical and numerical modelling,
for assessment of low temperature geothermal
potential of the Pisan plain. Despite the existence of
many information and many data have already been
collected in the past, all the investigation elements
took into account by this Project are not always treated
in a systematic way and made easily accessible. In
addition difficulties are encountered within local
authorities, which does not always have appropriate
tools for a proper use of local resources.
The Geo4P Project is therefore mainly aimed at
supporting public and private players potentially
interested in considering the opportunities offered by a
more efficient development of shallow geothermal
resources.
The studied area includes the municipalities of
Vecchiano, San Giuliano Terme, Calci, Buti, Bientina,
Vico Pisano, Calcinaia, Pisa, Cascina, Pontedera,
Fauglia, Crespina Lorenzana, Casciana Terme Lari
and Ponsacco and it covers more than 570 Km2 (Fig.
1).
The project is developed on the following steps:
 research and collection of existing data from
different sources,
 creation of a geographical information system
for data storage, management and updating,
 data validation and analysis and interpretation
to obtain a geothermal conceptual model,
 3D geological modelling,
 surveys for collection of geothermal chemical
and physical subsoil parameters,
 thermofluidodynamic 3D modelling
 recommendations to local decision makers
and presentation of project results to local
stakeholders.
Figure 1: The studied area.

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2. GEOLOGICAL AND HYDROGEOLOGICAL
SETTINGS
The Pisa plain is located in Nord West side of
Tuscany region and is mainly made up of
neoautochtonous deposits that fill a wide graben
striking NW-SE (Bellani et al 1995). The coastal plain
is bounded by the Pisa Mountains to the Northeast, the
Leghorn and Pisa hills to the South, and the
Tyrrhenian Sea to the West (Sarti et al 2012).
Because of tectonic and climatic events, sediments
were deposited on the rock substratum from Miocene
to Quaternary. After two major transgressive cycles
(Upper Miocene, Lower Pliocene), which led to the
deposition of conglomerates, sands, clay and
evaporitic sediments, an important regressive phase
ensued during the Middle Pliocene. This brought
about land emergence and widespread erosional
activity (Grassi and Cortecci 2005). During the
Pleistocene there were several eustatic fluctuations
and the sediments were deposited in the area
according with the flooding stage of Arno-Serchio
water system. Then (Upper Pleistocene – Holocene),
mainly fluvial and marshy sediments were deposited,
due to reduced fluvial activity linked to both the
eustatic sea-level lowering and progressive drying of
the climate (Grassi and Cortecci 2005).
The historical evolution of Pisa plain results in a
complex stratigraphic pattern: the generally accepted
hydrogeological scheme (Trevisan and Tongiorgi
1953; Dini 1976; Fancelli 1984, Baldacci et al 1994;
Rossi and Spandre 1994) is that there is a multi-
layered confined aquifer (MCA) system with two
major confined aquifers, locally connected.
3. GEOGRAPHICAL INFORMATION SYSTEM
FOR GEOTHERMAL PLANNING
The first step of the project was to research and collect
all available information on Pisa basin evolution:
geology, stratigraphy, hydrogeology, chemical and
isotopic analysis of aquifers. All data were collected in
a dedicated geo-database developed on Esri ArcGis
10.2.2. Gis structure reflects the following scheme
(Fig 2) and is organized in 5 information layers
(shapefiles) mutually connected to each other from the
key field “identifies”.
Figure 2: DB setting with Informative Layers
The Geographical Information System also contains
raster elements:
 Geomorphologic map of Pisa (Cerratori et al
1994),
 Geological map of Tuscany, sheet 273, Pisa
Section 273010, scale 1: 10.000 (ISPRA),
 Rocks permeability map, Aquifer System of
Pisa plain (Baldacci et al 1998),
 Geological Map of the North-western part of
Pisa Mountain, scale 1: 25.000 (Giannini and
Nardi 1964),
 II interpretative geological map of the Pisan
hills to the Southeast of the Guappero Valley,
scale 1: 25.000 (Rau and Tongiorgi 1974),
 Topographic map in scale 1: 10.000
 Digital elevation model (DEM) of the area,
cell size 20m.
All data were georeferenced in
WGS_1984_UTM_Zone_32N (WKID 32632)
coordinate system.
3.1 Informative layer “IL_001_Wells”
“IL_001_Wells” contains all the available information
regarding 2740 water wells and geotechnical surveys
(Fig 3) in the area of study: latitude, longitude,
altitude, depth and data source.

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Figure 3: IL_001_Wells; features are coloured
according to the depth of survey, hot colours
for deeper wells.
3.2 Informative layer “IL_002_Stratigraphy”
“IL_002_Stratigraphy” contains the stratigraphic
description for each survey. Each point represents a
lithological layer (Fig 4).
Figure 4: IL_002_Stratigraphy.
3.3 Informative layer “IL_003_Temperature”
“IL_003_Temperature” collect 193 temperature
measures (Fig. 5): these data come from bibliographic
sources and fieldwork survey that interested 97 wells
between 2015 and 2016. Temperature values are
associated, where is possible, with the filter depth.
Figure 5: IL_003_Temperature.
3.4 Informative layer “IL_004_Hidrogeology”
“IL_004_Hydrogeology” holds 1449 elements (Fig. 6)
and manages the hydrogeological information like
permeability, transmissivity, flow rate, storage coefficient,
number and depth of filters in wells.
Figure 6: IL_005_Hydrogeology.
3.5 Informative layer “IL_005_Water_chemistry”
“IL_005_Water_chemistry” contains chemical results
of water analysis from bibliography and from field
sampling during the last year (Fig. 7). Light blue
points represent sampling taken during this project and
subjected to chemical and isotopic analysis.
Figure 7: IL_005_Water_chemistry. The map
shows the wells for which you have the
results of chemical analysis.
Chemical analysis results (Fig. 8) and isotopic survey
will be useful to improve the knowledge of
underground circulation in aquifers.

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Figure 8: Piper diagram for chemistry
classification of Pisan plain underground
waters.
4. 3D HYDROGEOLOGICAL MODELLING
4.1 Hydrogeological conceptual model
According with existent bibliography (Baldacci et al
1994, Sarti et al 2012, Grassi and Cortecci 2005.) and
using database information, a 3D hydrogeological
model of Pisan plain was set. The model realization
was carried out through a series of operations that
allowed extending punctual information to the whole
studied area. The hydrogeological interpretation of
significant stratigraphy and the creation of 16
hydrogeological sections provided the characterization
of following hydrogeological units:
 Recent Alluvial Cover: clays and
discontinuous sand bodies, related to recent
Arno and Serchio flooding deposits, host
suspended aquifers with low flow rates;
 Multilayer Confined Aquifer (MCA): is
composed by 2 permeable levels with sands
and gravels, locally connected. It hosts
aquifers with high flow rates;
 Clay 1: where it exists, separates the
permeable horizons of MCA System.
 Clay 2: clayey sediments below MCA
deposits.
 Coastal Dune Aquifer: eolian and marine
sand deposits. It extends from the coast to the
western side of Pisa. This aquifer is locally
connected with MCA.
 Alluvial Fans Aquifer: dense succession of
gravelly deposits that move from Pisan
mountains to Arno valley. It hosts several
spring and high water circulation.
4.2 Petrel workflow for model creation
Modelling process was performed with Petrel E & P
Software Platform, Version 2013.6, using the
following input data:
 450 wells (Fig. 9 and Fig. 10), selected
considering depth and quality of information.
For each well, hydrostratigraphic units top
(“well top”), was located (Fig. 11),
 16 hydrological sections (Fig. 12). For each
section were located points (“additional
points”) matching with the top of
hydrostratigraphic units,
 Petrel has processed well tops and additional
points, building the surfaces of the different
units to be modelled. The interpolation was
led by “convergent interpolation algorithm”
generating regular mesh grids, 50x50 m. The
surfaces were further refined by the operator
where software performed anomalous or
irregular results (Fig. 13),
 Bedrock top surface was obtained by
inversion of gravimetric measures (Fig. 14),
 Finally, starting from surfaces, a complete 3D
hydrogeological underground model of Pisan
plain was built (Fig. 15, Fig. 16, Fig, 17).

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Figure 9: Wells imported in Petrel project, in studied area.
Figure 10: Wells in Pisa city.
Figure 11: Well tops in Pisa city area.

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Figure 12: Hydrogeological sections imported in Petrel project, in studied area.
Figure 13: Obtained surfaces, in Pisa city area.
Figure 14: Bedrock, top surface.

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Figure 15: 3D hydrogeological underground model of Pisan plain.
Figure 16: EW model section.
Figure 17: NS model section.

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5. THERMOFLUIDODYNAMIC MODELLING
A portion of the hydrogeological model was imported
in PetraSim 5, RockWare software with graphical
interface for the TOUGH2 family of simulators.
(Fig.18, Fig.19, Fig. 20). Values of density,
permeability, porosity, conductivity and specific heat
were associated to single hydrostratigraphic units.
The top of model, has been set with a temperature of
16°C (mean value of atmospheric temperature in
Pisa). For the bottom of the model, represented by
bedrock surface, were used temperature values
variable, according with the depth and with the local
geothermal gradient.
Figure 18: Surfaces imported in PetraSim 5.
Figure 19: Hydrogeological model in PetraSim 5.
Figure 20: Layers volumes were divided in regular
cells on XY plane (500x500 m).
5.1 Simulation results
The simulation distributes temperature values on all
the cells of model (Fig.21, Fig.22), according with
initial condition and with the lithological and
geothermal properties of sediments.
Figure 21: Temperature results, interpolated at
specified horizontal slice. In blue cold
temperature, in yellow hottest sectors.
Figure 22: Temperature results. The upper blue
surface describes the trend of 20°C isotherm.
The horizontal slice below represents
temperature values at -200m of depth. The
vertical slices show the complete
temperature range from the top to the
bottom of the model.
Temperatures in the middle of upper Multilayer
Confined Aquifer level were extracted from this
model (Fig. 23 and Fig. 24). Obtained results are
comparable with the temperature collected during
field surveys.

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Figure 23: temperature interpolation simulated at the middle of upper MCA level. The hot colours represent
areas with higher temperatures. South view.
Figure 24: temperature interpolation simulated at the middle of upper MCA level. The hot colours represent
areas with higher temperatures. Southwest view.
6. LOCAL IMPLEMENTATION OF PROJECT
RESULTS
As well as giving information about the shallow
geothermal potential of the whole study area,
geological results so obtained will be used to suggest
best suitable technologies to use locally available
geothermal heat, also taking into account specific
users features and requirements. These plant solutions
will be indeed identified taking into account the
sustainable use of geothermal resources, both under
the economy related issues and the environmental
point of view, avoiding negative impacts in shallow
aquifers.
Project results will be particularly helpful in case of
integration into urban plans and/or local energy plans.
Municipalities will thus be able to better support their
decision-making processes, the preparation of
datasheets in SEAPs or other local energy planning
tools, thanks to the use of results obtained by the
Geo4P Project.
In a time when public acceptance towards geothermal
projects the involvement of territories involved in the
project has not been overlooked. Local decision
makers and technicians of municipalities are indeed
being involved, proposing them useful
recommendations to allow the promotion of
appropriate local energy planning tools and to foster

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appropriate activities for the use of geothermal
resources. Project results will also be made available
to citizens and companies who intend to take into
account geothermal resources for thermal uses and to
produce cool, with economic and environmental
benefits.
7. CONCLUSIONS
Once the multidisciplinary methodology for the
Geo4P project will be validated, as well as promoting
sustainable energy consumption in territories of the
Pisan plain, through the use of shallow geothermal
resources, it will be made available to stakeholders.
This will allow to export and implement these geology
and energy related analysis techniques in similar
contexts. The Pisan plain is indeed a typical example
of alluvial plain, as many others in Italy and Europe.
Projects results will be published by the second half of
2016 at the following web address:
http://www.distrettoenergierinnovabili.it/der/s/energea
/progetto-geo4p/progetto-geo4p.
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Acknowledgements
Geo4P was developed within the Memorandum of
understanding among the following Organizations:
Italian Ministry of economic development (UNMIG),
Regional Government of Tuscany, Province of Pisa,
Consortium for the Development of Geothermal
Areas, University of Pisa, Sant’Anna School of
Advanced Studies, EnerGea, Acque and AEP. This
Project is financed by the Geothermal Fund, through
the “General Agreement on Geothermal”, signed by
the Tuscany Region, Enel Green Power,
municipalities of Tuscan geothermal areas, their
unions and provinces of Grosseto, Pisa and Siena and
CoSviG. The Geothermal Fund collects economic
compensations that geothermal territories receive from
Enel Green Power for the use of geothermal resources.