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Copyright 1999, Society of Petroleum Engineers Inc.
This paper was prepared for presentation at the 1999 SPE Latin American and Caribbean
Petroleum Engineering Conference held in Caracas, Venezuela, 21–23 April 1999.
This paper was selected for presentation by an SPE Program Committee following review of
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Abstract
Extensive feasibility tests involving Microbial Improvement
Technology were conducted with the two main productive
formations in Piedras Coloradas Oilfield, Mendoza Province,
Argentina. The program started March 1997 and continued
during twelve non-consecutive months. Six producer wells,
two of them horizontals, were under a systematic program of
inoculations using hydrocarbon-degrading anaerobic-
facultative microorganisms. A complete set of rheology
parameters, specific geochemical fingerprints and biomarkers
comparison was used to evaluate pre- and post-trial
compositional alterations in produced fluids.
Project performance in terms of fractional flow evolution
was correlated with well completion configuration and
reservoir petrophysics by the use of parametric models and
compared on a well-by-well basis with corresponding decline
and complementary baselines. Incremental Oil averages 66%
over baseline with minimum values of 28.5% and maximum
above 110%. Results are consistent and show a clear
correlation between treatment design modifications and water
cut reduction. This correlation proves that Microbial Enhanced
Oil Recovery methods are controllable and predictable if team
integration and proper engineering methods are observed
during pilot design and well monitoring stages.
Cost per Incremental Barrel (CIB) was 5.1 $/barrel during
pilot stage. On MEOR Expanded scales, this value is forecast
to decrease to below 2 $/barrel. The project demonstrates that
this technology is cost effective, easy to implement and
complies very well with local environmental regulations and
biosafety issues.
This pilot program is the first part of an integral mid-term
strategy to use biotechnology in paraffinic oil bearing
reservoirs. Further evaluations in course will be covering
microbial influence mechanisms on waterflooding methods.
Introduction
Enhanced Oil Recovery pilot tests using biotechnology
methods were conducted with the two main productive
formations in Piedras Coloradas Oilfield,Mendoza Province,
Argentina (Figure 1). The objective of these trials was to
determine project performance in terms of fractional flow
evolution and its correlation with well completion
configuration and reservoir petrophysic parameters. By the use
of experimental design techniques, associated objectives were
achieved to determinate how predictable and controllable this
technology is based on previous screening criteria and
monitoring routines.
Piedras Coloradas Field Description
The field was discovered in 1953 and production started in
1956. It is located in Argentine Republic (South America), 65
km southwest of the city of Mendoza. It is part of NW-SE-
oriented trend of oilfields that parallels the western margin of
the Cuyo basin.
The field produces from two separate reservoirs:
Conglomerado Rojo Inferior, named C.R.I.(Barrancas Fm.)
and Victor Oscuro Member (Rio Blanco Fm.). The first
accounts for 80% of the total production (Figure 2). The area
produces 430 M3/D of very paraffinic oil becoming from 85
active wells. Average production per well is 5.8 M3/D with a
standard deviation of ±7.3 M3/D). Active wells are grouped in
four batteries and 24 of these are horizontal. Eighty percent of
Piedras Coloradas production comes from 38% of wells. The
field has incipient waterflooding projects with 6 wells
injecting 1100 M3/D in both reservoirs.
MEOR: Conceptual frame
Microbial Enhanced Oil Recovery (MEOR) technology is
based on the systematic inoculation of producing wells with
hydrocarbon-degrading anaerobic-facultative microorganisms.
The primary goal of the method is to extensively colonize the
poral medium of the oil bearing . [Ref .: 1, 16]
Seven different microbial products (sub-communities) of
highly motile, synergetic, symbiotic microorganism consortia
were initially used to test Piedras Coloradas oil biotreatability.
These strains are naturally occurring bacteria capable of
deriving nourishment from linear hydrocarbons. A
combination of products is necessary to adjust the bacterial
SPE 53715
Microbial Enhanced Oil Recovery Pilot Test in Piedras Coloradas Field, Argentina
M. A. Maure, SPE, and F. L. Dietrich, SPE, Microbes, Inc. and V. A. Diaz and H. Argañaraz, Perez Companc S.A.
2 M. A MAURE, F. L. DIETRICH, V. A. DIAZ, H. ARGAÑARAZ SPE 53715
community to specific substrates (oils) and reservoir
conditions. Microbial products are also conditioned to have an
adequate balance in type of complementary nutrients, buffers,
trace elements (K+, Na+, Mg++, Ca++, Fe++/+++, Zn++, Co++) and
bio-catalizers, since formation water usually lacks sufficient
nitrogen and phosphorous.
Secondary objectives of this stage are to stabilize
enzymatic reactions at water/oil interfaces in the productive
formation, in order that such biochemical action can modify
oil mobility, by the generation of solvents and bio-surfactants.
Differences in microbial effect in treated wells could be
detected in two consecutive stages:
1- Clean-up effects by the removal of organic damage
occurring in the near wellbore of the perforated
interval, opening non-productive zones bearing oils
with a more segregated, heavy and pseudoplastic
behavior. This effect produces a high peak in oil rate
but only for a limited time (Figures 19, 20 and 21).
2- Rheological effects by the compositional alteration
occurring at deeper colonization radius, in drainage
zones with extremely low shear rate values. This
effect is the most important MEOR objective to
pursue in treated wells, as this improvement is
sustainable for a long period if proper microbial
inoculation schedule is continued (Figure 23, c2
segment, Figure24, v-w segment).
The proof of these alterations and consequent modifications is
accomplished by serial Rheological Lab Procedures (Annex
A) in combination with Organic Geochemistry Methods
(Biomarkers and GC-MS Chromatography, Annex C).
The change in amount and compositional characteristic of
produced fluids arises as a consequence of microbial action on
saturated hydrocarbon substrates under anaerobic conditions
accompanied by a strong modification on N/P ratio in the
colonized poral volume. Changes in micro-environmental
parameters existing in poral space promote specific metabolic
paths that ultimately produce the cracking on linear and
branched paraffin compounds, which are present in abundance
in Piedras Coloradas oil (Figures 31, 32). The expected result
is the shifting in molecular weight and chain length toward a
lower range and greater compositional homogeneity. The most
significant evidence is the viscosity reduction at low shear
rates and the shift in pour and cloud temperature points
(Figures 42 and 43, Annex A).
Candidate wells were selected as producers from only one
reservoir (Barrancas or Rio Blanco), avoiding treatment of
multilayer systems, with different petrophysical parameters.
Related Case: Tupungato MEOR Project
Tupungato is a neighbor field in close connection with Piedras
Coloradas area. The North-West limit is common for both
areas. It is also part of NW-SE oriented trend of oilfields that
parallels the western margin of the Cuyo basin. In July 1994 a
MEOR pilot project was started and conducted for two years,
involving the same formations and showing very positive
results. Project details were discussed in a previous technical
paper [Ref.: 1], and served as an important reference to
encourage MEOR application in Piedras Coloradas field.
MEOR In Piedras Coloradas Field
General Screening Criteria
Primary requirements to check are:
1. Crude oil composition must contain n-alkanes in
sufficient amount and show little or no evidence of
previous levels of biodegradation by indigenous
microbiota. Table 6.
2. Bottom hole temperature need to be less than 250 °F.
Pressure is not a limiting factor.
3. Chlorides less than 100,000 ppm in the formation water.
4. PH is best near neutral.
5. Pore throat distribution in objective reservoirs needs to
have a minimal portion above the range of microbial
community size to permit microorganism migration. This
requirement means to have an "available window" in
poral geometry to permit profound microbial incursion
(Figures 3, 4, 5 and 6).
Fluid Evaluation, Oil
Comparison of a complete set of rheology parameters, specific
geochemical data, ionic patterns, fingerprints and biomarkers
was used to evaluate pre- and post-trial compositional
alterations in produced fluids.
PVT relevant data.
Bubble pressure (psi): 1023
GOR (M3/M3): 37
Bo factor (M3/M3 ): 1.176
Viscosity (cp, SR>20 s-1, 180°F): 4.5 (Roll Ball viscometer)
API°: 32 (Reservoir condition)
Geochemical background
In October 1988, Geochemical Analyses were performed on
five oils from Piedras Coloradas field (EI-14, PC-29, PC-44,
PC-55 and PC-74). This report provide a clear evidence that
these oils could be good targets for a MEOR program, in close
agreement with results obtained in Tupungato pilot project.
Main conclusions were [Ref.: 2]:
• All five Piedras Coloradas oils belong to one oil family.
• All are very paraffinic, undegraded oils that were sourced
from a single source facies.
• All geochemical parameters indicate a single oil type,
with normal alkane distributions.
• Pristane/Phytane ratios and carbon isotope ratios are
particularly diagnostic oil-oil correlation parameters.
• The oils show no signs of water washing or
biodegradation.
• An odd-carbon preference is discernable in the oils, both
in the medium range (C17, C19) and higher molecular
weight (C23, C25) n-alkanes. These preferences, together
with the presence of C27 and C29 steranes suggest the
oils were derived from both algal and terrestrial
precursors (Table 6).
SPE 53715 MICROBIAL ENHANCED OIL RECOVERY PILOT TEST IN PIEDRAS COLORADAS FIELD, ARGENTINA 3
MEOR-oriented geochemical studies
Two independent geochemical laboratories and consultants
were selected to evaluate compositional alterations and their
correlation with rheology parameter evolution.
Conceptual basis and methodology. Changes in the
composition of petroleum during a MEOR process can be
followed through analyses that are typically applied in the
geochemical characterization of rock bitumens and oils. These
changes could occur at a bulk or molecular level, most likely
both, and are difficult to anticipate: each oil type subjected to a
specific microbial batch treatment reacts in a different manner
under particular subsurface conditions. Moreover, these
changes are time-dependant and several of them sequential,
and could show up at very different times in non-related oils.
A summary list of the analytical techniques applied to the
geochemical characterization of oils can be found in Annex C.
Short comments of the changes that could be expected after a
MEOR process on a particular oil are:
• Liquid Column Chromatography is applied after
precipitation of asphaltenes to determine the
proportions of saturated hydrocarbons, aromatic
hydrocarbons and resins + NSO (nitrogen, sulfur,
oxygen) compounds. The naphthenes can be later
estimated as a part of the saturates from the whole oil
gas chromatography. These five fractions are expected
to change after a MEOR process. Modification of API
gravity should be related to the changes in the bulk
composition of the oil.
• Percent Sulfur is a typical bulk parameter of an oil,
which will likely be modified after a MEOR process.
• High Resolution Whole Oil Gas Chromatography
typically allows determination of normal- and iso-
paraffins (quantitatively, in ppm) and defines the
“envelope” of an oil. Ratios between compounds and
relations between ranges of compounds (light,
medium, heavy) as well as the chromatogram baseline
should change after a MEOR process.
• Gas Chromatography of the Saturated
Hydrocarbon Fraction basically provides the same
information as whole oil gas chromatography but is
more precise in resolving peak co-elution and allows
better ratio calculations. However, a big disadvantage
is that during isolation of the fraction the light
compounds <C15 are partially or totally lost.
• Gas Chromatography of the Aromatic
Hydrocarbon Fraction allows identification and
quantification of the typical aromatic compounds
present in oils: methyl-naphthalenes, dimethyl-
naphthalenes, trimethyl-naphthalenes, phenanthrene,
methyl-phenanthrenes and dimethyl-phenanthrenes.
Relationships between these groups of compounds and
between isomers could change after a MEOR process.
• Detailed C6-C7 Gas Chromatography. Twenty-five
compounds are identified and quantified in the C6-C7
range through gas chromatography. The range is very
sensitive to microbial attack and should experience
changes after a MEOR process.
• Stable Carbon Isotopes of Whole Oil, Saturates
Hydrocarbon Fraction And Aromatic
Hydrocarbon Fraction. The δ 13C values are bulk
characteristics of oils. After a MEOR process the
values could hypothetically show minor to significant
modifications.
• Gas Chromatography – Mass Spectrometry Of
Saturates Hydrocarbons. The terpane and sterane
biomarker fingerprints represent extraordinary
valuable information in the characterization of an oil
(source, thermal maturity, biodegradation). A MEOR
process could very possibly modify molecular ratios
and parameters of these fingerprints.
• Gas Chromatography – Mass Spectrometry Of
Aromatic Hydrocarbons. Similar to saturate
biomarkers, the fingerprints of aromatic steranes are a
supplement to the molecular characterization of an oil.
In addition, the method allows quantification of 2- &
3-ring aromatic hydrocarbons (naphthalene,
phenanthrene and dibenzothiophenes compounds).
Rheological studies
Conceptual basis. Oil as very complex substance exhibits
typical non-Newtonian behavior. Viscosity is shear rate
sensitive (pseudoplastic model) and it correlates strongly with
the fluid dynamics occurring in the poral space. The concept
of constant viscosity in the drainage area is no longer valid,
rather "apparent" values are pertinent. Specific quantitative lab
procedures were conducted to measure the shift in rheological
properties in treated (inoculated) and untreated (control)
samples obtained from well head manifold for every
candidate well.
Lab indexes and methodology. Serial assays were
conducted to determine the alterability of Barrancas and Rio
Blanco oils under systematic microbial influence (enzymatic
cracking). Basically, lab procedures consisted of serial
inoculations of oil with seven different microbial products,
followed with 48 to 96 hours of controlled atmosphere
incubation at specific temperatures. Further examination of
inoculated and control oil (originals) using full computational
rotational viscometers (Brookfield DVII+/III models), will be
produced the necessary plots and data vectors to generate
quantitative indexes. Deviations in µapp.[mpa.s] vs.
Temperature [°F] and µapp.[mpa.s] vs. Shear Rate [1/s] curves
were the basis for calculating quantitative numbers describing
the degree of compositional alteration. Mathematical
expressions for these dimensionless indexes are described in
Annex A. These numbers translate the graphical information
into lab performance indicators. Furthermore, they are used
during pilot monitoring to contrast and compare lab and field
figures.
So, the Newtonian Index (NI) is used to evaluate the
shifting from shear rate sensitive (pseudoplastic) behavior
toward a more newtonian fluid. The comparison between
4 M. A MAURE, F. L. DIETRICH, V. A. DIAZ, H. ARGAÑARAZ SPE 53715
control and inoculated oil samples is evidence of microbial
cracking by each different microbial culture. To test as
positive NI need to be greater than 1.10. (Eq.32)
The Delta Viscosity (DV) Index measures the global
change in apparent viscosity in the explored range of shear
rates (minSR, maxSR). To test as positive DV need to be
greater than 0.10, (Eq.33)
By direct mathematical manipulation of DV index, a
simple version of Enhanced Oil Recovery factor (EOR Index)
is obtained, as related only to viscosity contribution. An
exceeding EOR value from 1.15 tests as positive, (Eq. 34)
A data base of 84 oil samples from 11 different fields (22
from P.C. area), pertaining to the same sector of Cuyo
sedimentary basin were tested to define general rheological
properties of Mendoza North oils. First evaluations start on
1994. In general all these crude oils tested far above cut-off
values, evidencing very good microbial treatability. Piedras
Coloradas values in pre-selected wells were:
Sample NI DV EOR
PC-1020 (Horizontal, V.O.) 1.64 0.38 1.61
PC-1022 (Horizontal, V.O.) 4.44 0.39 1.64
PC-86 (Vertical, V.O.) 20.80 0.76 4.13
PC-94 (Vertical, V.O.) 0.27 0.61 2.60
PC-19 (Vertical, C.R.I.) 13.50 0.39 1.64
PC-68 (Vertical, C.R.I.) 1.57 0.95 20.89
Limit for positive testing >1.10 >0.10 >1.15
Fluid Evaluation, Water
Ionic pattern and salinity of formation water need to meet
certain requirements to avoid side effects during the MEOR
pilot test. Maximum limit in chlorides is considered safe when
it has less than 100.000 p.p.m. PH is best near neutral.
Blending water is also conditioned and monitored for total
solid content and particulate size distribution (Figure 39)
Reservoir Characterization
Main Mechanism of drainage for both reservoir is due to gas
expansion assisted by incipient artificial water drive.
Waterflooding projects are not massive.
Structurally the Cuyo basin is an extensive NW-trending
depocenter that is limited by extension faults which were
subjected to several movements. In Piedras Coloradas area,
these tectonics movements formed an anticlinal structure that
plunges to the southwest. This structure continues westward to
the Tupungato field.
A- Barrancas Fm. (C.R.I.)
Poral geometry: Core testing using microporosity and
capillary pressures converted into poral throat distribution
show very large pore system with average values of 50 µm
(Figures 4, 6). Effective interval: 8 m
Petrophysical parameters
End Point relative permeabilities values
Kro(Swi): 0.46
Krw(Sor): 0.13
Swirr (%): 31.4
Sor (%): 23.3
Porosity (%): 16.8
Absolute Permeability (md): 120
Depth (m.b.s.): 1930
Reservoir Temperature (°F) 170
Original Reservoir Pressure (psi): 2285
Present Reservoir Pressure (psi): 569
Bubble Pressure (psi): 1023
GOR (M3/M3): 37
Bo factor (M3/M3 ): 1.176
Viscosity (cp, SR>20 s-1, 170°F): 4.5 (Roll Ball viscometer)
API° (Bottom Hole Conditions): 32
Lithology: Conglomeradic and sandstone with variable
interleaved shales and limonite components
B- Rio Blanco member (V.O.)
Poral geometry: The poral system is controlled by the quantity
and type of cement, which is related to the amount of tuff
ashes between the grains. Capillary pressures and electronic
microscopy runs on core specimens were used to determine
pore geometry characteristics. It follows a distinctive matrix
monomodal distribution with poral throat mean values
centered at 2 µm (Figures 3 and 5). Further evaluation has
detected the presence of microscopic fractures. These small
fractures, which are common in this tectonic framework
contribute to the movement of fluids and permit microbes
migration outward in the reservoir. Effective interval: 2-4 m
Petrophysical parameters
End Point relative permeabilities values
Relative permeabilities
Kro(Swi): 0.57
Krw(Sor): 0.36
Swirr (%): 30.6
Sor (%): 28.2
Porosity (%): 16.2
Absolute Permeability (md): 5-10
Depth (M.b.s.): 2030
Reservoir Temperature (°F) 180
Original Reservoir Pressure (psi): 3371
Present Reservoir Pressure (psi): 1279
Bubble Pressure (psi): 1026
GOR (M3/M3): 35
Bo factor (M3/M3 ): 1.154
Viscosity (cp, SR>20 s-1, 170°F): 4.5 (Roll Ball viscometer)
API°(Bottom Hole Conditions): 32
Lithology: Good reservoirs are mainly related to the
presence of sand associated with alluvial fan influx from the
western flank of the basin. Deposition occurred under a
persistent rain of ash, generating tuff and mixed rocks.
Pilot Design
Design of a pilot test is a complex task. To produce the best
results in terms of degree of significance and discrimination it
SPE 53715 MICROBIAL ENHANCED OIL RECOVERY PILOT TEST IN PIEDRAS COLORADAS FIELD, ARGENTINA 5
is necessary to integrate a multidisciplinary team in bio-
technology, reservoir, production and complementary areas
(rheology and geochemical topics). The main issues behind
pilot design is to achieve technical closure and good levels of
correlation between controllable and uncontrollable groups of
variables. The controllable variables are mainly MEOR
treatment parameters. The uncontrollable variables are related
with fluid and rock characteristics, which exert significant
influence on MEOR response. Additional goals are to confirm
feasibility indexes exhibited during laboratory testing. The
pilot was designed to define microbial impact on productivity
index for every treated well, completion method and reservoir
in exploitation.
A reasonable prediction capability between previous
screening and post-MEOR results is another important
objective. Discrimination in pre- and post-pilot data
information and good “signal to noise ratio” are essential for a
successful pilot. The trial needs to be programmed to see all
relevant processes in time (pilot duration) and spatial
dependence (number of wells, depth and structural position).
Minimal time scale needs to be a twelve months period.
Another important concept behind of pilot implementation is
to reduce the uncertainty for all relevant measurement
occurring during the pre- and post-MEOR stages. Finally, cost
of pilot evaluation need to be consistent with expected benefits
under different scenarios, risk and expansion strategies.
Well Selection
Six producer wells from a pool of 29 possible candidates (12
from Barrancas and 17 from Rio Blanco Fms.) were selected
to implement the pilot according with following scheme:
• Barrancas Formation: PC-19 (Vertical), PC-68
(Vertical)
• Rio Blanco Formation: PC-1020 (horizontal), PC-
1022 (horizontal), PC-86 (Vertical), PC-94 (Vertical)
Main reasons behind this selection are:
1. Adequate number of candidates to have sufficient
statistical significance and good discrimination in well-
by-well performance evaluation.
2. Non-marginal wells having consistent and clear fluid
production histories.
3. Capable of discriminating microbial stimulation and EOR
improvements in corresponding with control variables for
each targeted reservoir (Barrancas Fm. and Rio Blanco
Fm).
4. Wells producing oils with positive bio-treatability tests.
5. Adequate completion and extraction configuration.
6. Relevance to determining design consideration for future
expansions.
Operative aspects
Treatments
Initial microbial treatments were variable amount of microbe-
laden water (having neutral PH and with solid particulate
control), followed by a 72 hour shut-in period. Subsequent
periodic treatments have been one third of initial volume every
15 days. Treatment design centers on seven items:
1. Method of inoculation based on well completion and
extraction method (Figures 37 and 38).
2. Microbial community structure.
3. The total biotic concentration to use during initial and
periodic treatments.
4. Blending and displacement water.
5. Microbial product structure (product participation).
6. Frequency of periodic inoculations.
7. Initial and periodic latencies (shut-in time) that follow
every treatment.
Horizontal wells. Initial inoculation was conducted by
squeezing method according to diagram of Figure 40. Initial
treatment size of 150 barrels was the minimum considered,
based on a lateral diameter of 0.15 m. This size would provide
a bio-reactor that the production would be in for one day as it
traveled to the wellbore, if the entire 150 barrels were
displaced into the formation. To ensure this the treatment size
was increased by the capacity of the lateral from 150 to 220
barrels. If the formation would accept a larger treatment at low
pressure, an initial treatment volume two to three times this
might be considered. A higher microbe concentration in the
maintenance treatments is advisable due the treatment size
mandated by the length of the lateral. The formation needs to
be over balanced in so that it can take fluid over the 3 day
shut-in time.
Periodic treatments were by batching using annulus space.
The volume of microbe-laden water was calculated so that as
the fluid level in the well gradually decreases, the fluid forced
into the formation is microbe-laden and not displacement
water. Using pressure build-up data, the bottom hole pressure
at the end of three days was used to determine approximately
what the fluid level in the well would be at the end of the shut-
in period, and the treatment was sized accordingly.
Vertical wells. The initial treatment was designed to use a
lower concentration than the maintenance treatment. Usually a
1: 210 dilution was used on the initial treatment (0.2 gal./bbl.)
and a 1:84 dilution on the maintenance treatments (0.5
gal./bbl.). The rationale is that with the longer shut-in times
the microbes have more time to grow and become established
than with the shorter times normally used on maintenance
treatments. For wells having a low average permeability
limiting fluid input, higher concentration for the initial
treatment is probably advisable.
The maintenance (periodic) treatment size of 50 barrels
was selected as a compromise between radius of microbial
penetration and quick fractional flow stabilization after shut-in
period. Results in Tupungato field validated this assumption.
Both initial and periodic treatments were by annulus (Figure
41).The original program of treatments is summarized in Table
1. Product participation was P #1: 28.5%, P #4: 13.5%, P #5:
9.5% and P #6: 48.5%. Microbial sub-communities are
presented in liquid medium as concentrates, having 106 - 108
viable microorganism per ml. Microbial liquid product (five
6 M. A MAURE, F. L. DIETRICH, V. A. DIAZ, H. ARGAÑARAZ SPE 53715
gallon drums) was stored out of direct sunlight and extreme
weather conditions (+5 to +30 ºC), avoiding freezing
temperatures.
Project evaluation
The inoculation program started March 1997 and continued
for twelve non-consecutive months. Two reservoirs and six
producer wells, two of them horizontals, were under a
systematic program of inoculations using hydrocarbon
degrading anaerobic-facultative microorganisms. A complete
set of rheology parameters, specific geochemical fingerprints
and biomarkers comparison was used to evaluate pre- and
post-trial compositional alterations in produced fluids.
Technical aspects
Methodology to evaluate MEOR performance
MEOR’s long-term distinctive response is to increase net oil
rate and simultaneously to reduce Water Cut (Figures 07 to
18). This typical duality in MEOR response is explained by
the change in apparent oil and water mobilities in the
colonized portion of the reservoir, the bioreactor.
Project Performance is evaluated well by well by tracking
Productivity Index (P.I.) evolution (Eq. 1). Individual well
testing into common battery and last generation echometry
were used to have good data input for calculating and updating
P.I. Four production tests per well per month, with
confirmatory duplicate tests, were the usual monitoring to
track project performance. Special care was taken to verify
constancy in dynamic fluid levels pre- and post-MEOR.
Pre-Meor adequate baselines for every well were
calculated before starting the program of inoculations. Low
noise (data scatter) allowing consistent decline curve
determination is of the upmost importance for proper
discrimination of microbial effects on well and reservoir
productivity.
Project evaluation is based on a customized set of MEOR
Performance Curves (MPC), Eq. 2 with embedded rock-fluid-
microbiota parameters which are validated using field data.
Annex B. The use of MEOR performance curve methodology
is accomplished in four basic steps:
• First, lab screening procedures are conducted to test
rheology behavior in produced oils using control and
inoculated samples for every well;
• Second, Incremental Oil Rates (IOR) and Water Cut vs.
time figures are forecast according to treatment design,
reservoir and well completion information;
• Third, predicted curves are correlated with field
performance data during pilot implementation; providing
insights and guidelines for process optimization and
treatment design alteration, permitting assessment of
MEOR prospects and offering practical guidelines during
field implementation and pilot project follow-up
monitoring; and
• Fourth, economical models are run to calculate updated
profitability indexes.
Field data was matched using radial/elliptical flow model
expressions considering concentric coupled zones of altered
and original fluids. The model considers the oil as non-
Newtonian, shear-rate-dependent fluid (Annex B).
Mechanistic models could be easily adjusted to take into
consideration horizontal completion geometry and
permeability anisotropy.
Net oil increment
Evaluation of incremental oil was performed using reservoir
simulations that consider two-parameter rheological models
(Ostwald de Waele Nutting scheme, Annex B). Results are
dimensionless time-dependent quotients of Productivity
Indexes for the oil fraction before and after MEOR. The
influence on MEOR response of petrophysic parameters is
mainly associated with two aspects:
1. Microbial Migration Rate (MMR) is related to reservoir
poral geometry (pore throats distributions); and
2. Shear Rate Field (SRF) is based on colonized reservoir
and fluid flow dynamics and their connection with
apparent viscosity.
MMR correlate very well with how quickly the maximum
MEOR response is obtained (improvement in Productivity
Index, PI). This point will be depends on final radius of
bacteria penetration and density of colonies in the
corresponding reservoir poral spectra. SRF has a singular
importance with shear rate sensitive oils (pseudoplastic
behavior) and degree of compositional alteration. Figures 07
to 18, and 25 to 30 summarize pre- and post-MEOR oil
production history. Composite performance is showing in next
graph. Change in oil decline tendency before and after MEOR
is clear and well defined. Incremental Oil averages 66% over
baseline (dashed) with minimal values of 28.5% and
maximum above 110%, in close correlation with oil °API
variation: PC-19 , Pre: 19.3 , Post: 24.0 °API; PC-1020, Pre:
21.9, Post: 23.3 °API.
Qoi t
Qbase t
ORm t
ORtot i
ORtotm x
Pilot_start
t shift t
,
t shift
,
Ti
,
Tx
,
1000 01000
0
50
100
150
200
MEOR curve-type
Baseline
Incremental Oil
Pre-MEOR production history
Post-MEOR experimental points
Oil Rate (6 wells composite)
Time [days from MEOR start]
[M3/D]
SPE 53715 MICROBIAL ENHANCED OIL RECOVERY PILOT TEST IN PIEDRAS COLORADAS FIELD, ARGENTINA 7
Water Cut Reduction
Figures 8, 10, 12, 14, 16 and 18 summarize pre- and post-
Meor water cut evolution. Water cut tendencies for the six-
well composite is shown below. Water influx is decreasing in
relation with oil. Change in water cut tendency is evident and
is a clear indication of compositional and mobility alteration at
reservoir conditions.
WRtoti
WRtotmx
Pilot_start
TiTx
,
1000 01000
40
60
80
100
Pre-MEOR history
Post-MEOR experimental points
Water Cut (6 wells composite)
[Time from MEOR start, days]
[%]
Experimental Design (E.D.)
To analyze MEOR performance correlation with specific
variations in treatment parameters a limited Experimental
Design was conducted beginning mid-course in the original
inoculation schedule. Mann-Whitney (Non parametric test,
also named U proof) statistic procedure was used to verify
degree of significance between treatment changes and MEOR
response. Tables 2, 3 and 4, Figure 19, 20 and 21, summarize
E.D. results: Segment Baseline-A: Clean up; BC: Microbial
colonization; CD: Colony retraction (well is under-
stimulated); DE: re-colonization after of concentration
changes.
Rheological comparison
A clear and remarkable improvement in oil rheology was
detected (Figures 33, 34, 35 and 36).
Geochemical comparison
A significant alteration in oil geochemical properties,
biomarkers and fingerprints was detected. Figures 31 and 32
summarize the changes in Piedras Coloradas MEOR
application. Light ends (S1) are mainly originated by
enzymatic cracking on n-alkanes (S2), and their increase
continues over the life of the project. On the other hand the
increase in heavy compounds (S3, S5) occur during initial
clean-up of the productive interval and by new oil produced
from original poor quality oil bearing zones. This increase is
not a trend and might better be viewed as a baseline shift.
Additional before and after MEOR samples from PC-19
(C.R.I. member) and PC-1020 (V.O. member) are currently
under analysis.
API gravity show a consistent and increasing trend:
°API variation (lab normalized conditions)
PC-19
Pre-MEOR: 19.3 Post-MEOR: 24.0 ∆: +4.7
PC-1020
Pre-MEOR: 21.9 Post-MEOR: 23.3 ∆: +1.4
Saturates hydrocarbons
PC-19
Pre-MEOR: 62.2 Post-MEOR: 66.9
PC-1020
Pre-MEOR: 57.1 Post-MEOR: 68.4
Light end alteration: C6 and C7 components
PC-19 C6 C7
Pre-MEOR: 0.30% 0.57%
Post-MEOR: 1.34% 2.08%
PC-1020 C6 C7
Pre-MEOR: 0.68% 1.00%
Post-MEOR: 0.82% 1.33%
Esteranes indicator
The molecular change that correlate positively with microbial
molecular attack is the decrease in the C29 Compounds in
relation to the C27 counterparts. This decrease is readily
apparent in the m/z 217 mass fragmentograms specific for
steranes. Also, detectable is a significative increase in αββ
isomers in respect to ααα (specially in C29 esteranes).
Biomarkers
A general increase in terms of absolute concentration (ppm)
for the complete series of usual biomarkers such as C30
Hopane is observed:
C30 Hopane (ppm)
Status PC-19 PC-1020
Pre-MEOR: 1486 1326
Post-MEOR: 2048 2052
Note: 25-Norhophanes series was not detected in post-MEOR
samples.
Phenathrene/Dibenzothiophene ratio
Status PC-19 PC-1020
Pre-MEOR: 14 9.5
Post-MEOR: 15.9 10.2
8 M. A MAURE, F. L. DIETRICH, V. A. DIAZ, H. ARGAÑARAZ SPE 53715
Quantified compounds (Methylnaphaftalenes, %)
PC-19
Status MN DMN TMN MP
Pre-MEOR: 2.79 18.30 26.79 22.69
Post-MEOR: 7.65 31.35 31.42 12.33
PC-1020
Status MN DMN TMN MP
Pre-MEOR: 8.53 26.29 27.57 16.54
Post-MEOR: 8.92 29.64 32.42 12.56
Where:
MN, Methylnaphaftalenes; DMN, Dimethylnaphaftalenes;
TMN, Trimethylnaphaftalenes; MP, Methylphenathrene.
A progressive decrease in Aromatics, NSO and
asphalthenes is detectable. Also observable is a clear variation
in CPI (Carbon Preference Index) with increasing tendency in
odd carbon chain predominance mainly in nC15 to nC27 range
[Ref: 5, 8].
Biosafety issues
MEOR bacteria used in Piedras Coloradas project are non-
pathogenic. During the pilot, special care was taken to meet
local and foreign regulation in regard to environmental and
health topics
Toxicity tests on animals and plants were done by the
Institute of Microbiology (Academia Sinica) and by the
Institute of Atom Energy Utilization, Chinese Academy of
Agriculture Science, both in the Peoples Republic of China.
Selected animals and plants were Kunming mice (200
individuals, weighting 18-20 grams., half-male, half-female)
and Cucumber (Jinyan #5 strain) and rice (Yuefu strain) seeds
respectively. Special essay protocols and method of exposure
using microbial products number #1, #4, #5 and #6 were
applied to germinated plants, seeds and animals under test.
All results were no adverse affects for plants or animals.
The microbial product caused no abnormalities in plants (rice
and cucumber) and mice. No abnormality or disease occurred
on different crops by different ways of treatment. No
abnormality occurred of heart, liver, spleen, lung, kidney or
intestine of test mice.
Economical aspects
Five year and longer forecasts using net present value curves
based on adjusted individual well performance curves were
calculated at project termination. Then an integrate set of NPV
figures for the six well composite was calculated over a
similar period with sensitivity and risk analysis. Different
economic indexes like Pay-Out (break even point analysis),
Exposure, and Internal Rates of Return (I.R.R.) were derived.
Further analysis with floating scenarios of oil prices (from
location-adjusted WTI of 17.5 to 10 $/barrel), taxes and
treatment alternatives provide a detailed profitability
evaluation (Tables 8, 9 and 10).
Pay-Outs (PO)
Based on a well by well analysis an average PO value of 75
days from pilot start was obtained.
Cost per Incremental Barrel (CIB)
CIB was 5.1 $/barrel during pilot stage. On MEOR Expanded
scales, CIB is forecast to decrease to below 2 $/barrel. The
difference is due to pilot trials being conducted at small scale,
and being intensive in studies, operative support and
engineering (Table 8).
Incremental Reserves (IR)
IR totalizes an optimized value of 141,800 M3 of oil at
economic limits (<1 M3/D per well). A mean value of 50,000
M3 were assumed as conservative. Values were considering
well-by-well analysis and the further integration of individual
calculations for the composite (Table 9).
Internal Rate of Return (IRR)
IRR value is above 200% at average optimized prospects.
Conclusions
1- MEOR is technically feasible in Piedras Coloradas field
2- Both formations test positive with similar performance
figures.
3- MEOR on horizontal completions has interesting and
positive effects in terms of restoring productive length
and size of colonized areas.
4- MEOR is profitable at pilot and scaled stages.
5- A high correlation exists between the Piedras Coloradas
and Tupungato-Refugio projects in both conditions and
performance.
6- Multidisciplinary team integration and proper monitoring
techniques are key factors to optimize fractional flow and
incremental recovery in microbial stimulated reservoirs.
Course of future actions
1- To conclude in-course optimization stage in a cluster of
wells under treatment.
2- To evaluate best expansion strategies for vertical and
horizontal wells to maximize economic return..
3- To evaluate MEOR potential in waterflooding schemes.
SI metric Conversion Factors
acre-foot x 1.233 489 E+03 = m3
barrel x 1.589 873 E-01 = m3
foot x 3.048* E-01 = m
md x 9.869 233 E-04 = µm2
ml x 1.0 E-06 = m3
psi x 6.894 757 E+00 = kPa
U.S.Gal x 3.785 412 E+00 = L
°F (°F -32)*5/9 E-01 = °C
* Conversion factor is exact
Acknowledgements
We want to thank to Perez Companc Company and Microbes
Inc. for permission to publish this paper. Special thanks to
Piedras Coloradas directive staff and operative team for
SPE 53715 MICROBIAL ENHANCED OIL RECOVERY PILOT TEST IN PIEDRAS COLORADAS FIELD, ARGENTINA 9
valuable discussion, follow-up effort and contribution to
interpret MEOR field data. We also thank Alfredo
Rezinovsky, for his assistance in preparing this manuscript.
References
1. Microbial EOR Technology Advancement: Case Studies
of Successful Projects. F.L. Dietrich, SPE, F.G. Brown,
SPE, Z.H.Zhou, SPE, Microbes, Inc.; and M.A.Maure,
SPE, Green Consultores. SPE 53715.
2. Geochemical Report, Source Rock Evaluation of the
PCXP 1002 Well and Characterization of Five Oils,
Piedras Coloradas Field, Cuyo Basin, Argentina, October
1988, Exlog Consulting Services.
3. Wettability Literature Survey - Part 2 :Wettability
Measurement. William G. Anderson, SPE, Conoco Inc.
Journal of Petroleum Technology, November 1986.
4. Effect of Wettability Alteration on Water/Oil Relative
Permeability, Dispersion, and Flowable Saturation in
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Research Co. SPE Reservoir Engineering, May 1988.
5. New Tools Target Oil-Quality Sweet Spots in Viscous-Oil
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Exploration (Alaska) Inc. ; and R.J. Drozd, IITRI. SPE
36652.
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D.O. Hitzman, Injectech Inc. SPE 17341.
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Okla. U. of Kansas. Lawrence , Kans. Paper presented at
SPE Annual Fall Meeting, held in Houston, Tex., Oct. 11-
14-1964.
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managing heavy oil assets (17th. International Meeting on
Organic Geochemistry, Donostia- San Sebastian,
September 6, 1995). Mark A. McCaffrey.
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Oil Fields. Voordouw. G. ; Telan , A. J. Department of
Biological Sciences, The University of Calgary, Alberta,
T2N 1N4, Canada.
10. Surfactant - Base EOR Mediated by Naturally Occurring
Microorganisms. CP. Thomas, SPE, M.L. Duvall, SPE,
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EG&G Idaho Inc.. SPE 22844.
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Field Performance Data. Iraj Ershaghi, SPE, U. of
Southern California. Doddy Abdassah, SPE, U. of
Southern California. SPE 6977.
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Composition. Chapter I. 6. Ph. Blanc and Connan. (Elf
Aquitaine , Centre Scientifique et Technique Jean Feger
64018 Pau Cedex, France.)
13. Laboratory Testing of a Microbial Enhanced Oil
Recovery Process Under Anaerobic Conditions. Bruce
Rouse, Franz Hiebert, and L.W. Lake, U. of Texas. SPE
24819.
14. A Mathematical Model for Microbially Enhanced Oil
Recovery Process. Xu Zhan, R.M. Knapp, and M.J.
Mclnerney, U. of Oklahoma. SPE/DOE 24202.
15. Mathematical Modeling of Microbial Enhanced Oil
Recovery. M. R. Islam, U. of Alaska-Fairbanks. SPE
20480.
16. MEOR - Altamont/ Bluebell Field Project. L.P. Streeb,
Coastal Oil & Gas Corp., and F.G. Brown, Natl.
Parakleen Co.. SPE 24334.
17. A Study of Formation Plugging with Bacteria. J.T.
Raleigh. D.L. Flock. Members AIME . The U. of Alberta.
Edmonton, Alta. Journal of Petroleum Technology, July
14, 1964.
18. Microbes Deep inside the Earth. James K. Fredrickson
and Tullis C. Onstott. Scientific American, October 1996.
19. Optimization of Microbial formulations for Oil
Recovery : Mechanisms of Oil Mobilization, transport of
Microbes and metabolities , and Effects of Additive. R.S.
Bryant, T.E. Burchfield, K.L. Chase, K.M. Bertus, and
A.k. Stepp, IITRI/NIPER. SPE 19686.
20. A Parametric Comparison of Horizontal and Vertical Well
Performance. Hemanta Mukherjee and Michael J.
Economides. Dowell Schlumberger. SPE 18303.
21. Productivity of a Horizontal Well. D.K. Babu and
A.S.Odeh, Mobil R&D Corp.. SPE 18298.
22. Augmentation of Well Productivity with Slant and
Horizontal Wells. SD.Joshi, SPE, Phillips Petroleum Co.
SPE 15375.
23. Dimensionless Methods for the study of particle settling
in Non-Newtonian Fluids. Liang Jin, SPE, and Glenn S.
Penny, SPE, Stim-Lab Inc. SPE 28563.
24. The Transport of Bacteria in Porous Media and its
Significance in Microbial Enhanced Oil Recovery. Long
Kuan Jang, M.M. Sharma, and T.F. Yen, U of Southern
California. SPE 12770.
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in the subsurface. Ian Head. NRC News, May 1996,
Subsurface Microbial Populations.
10 M. A MAURE, F. L. DIETRICH, V. A. DIAZ, H. ARGAÑARAZ SPE 53715
Tables
Treatment Design (original)
Well Start Date
[dd/mm/aa] C.I.
[Gal] L.I.
[hs] C.P.
[gal] L.P.
[hs] Frequency
[T/month] Method
PC-1020 H (V.O.) 17/3/97 63 72 9 24 2 *Squeeze/Batch
PC-1020 H (V.O.) 03/04/97 63 72 15 24 2 *Squeeze/Batch
PC-68 (B.R.C.) 31/03/97 63 72 8 24 2 Batch
PC-19 (B.R.C.) 27/03/97 63 72 8 24 2 Batch
PC-94 (V.O.) 24/03/97 63 72 8 24 2 Batch
PC-86 (V.O.) 20/03/97 63 72 7 24 2 Batch
C.I.: Initial Concentration of Microbial Concentrates (P#1,P#4, P#5 and P#6)
L.I.: Latency (initial shut-in time)
C.P.:Periodic Concentration
L.P.:Latency (Periodic shut-in time)
Frequency: Treatments per month
* Inoculation method, Squeeze only for Initial Treatment
Table 01: MEOR, Inoculation parameters
Treatment modifications (Experimental Design)
Well Original
concentration Modified
concentration
Time interval [gals] Time
interval [gals]
Percentage
of change
PC-1020 H (V.O.) 17/3 - 15/5 9 15/5 - 15/6 20 +122 %
PC-1020 H (V.O.) 3/4 - 15/5 15 15/5 - 15/6 25 +66 %
PC-68 (C.R.I.) 31/3 - 15/5 8 15/5 - 15/6 16 +100 %
PC-19 (C.R.I.) 27/3 - 15/5 8 15/5 - 15/6 8 0 %
PC-94 (V.O.) 24/3 - 15/5 8 15/5 - 15/6 8 0 %
PC-86 (V.O.) 20/3 - 15/5 7 15/5 - 15/6 14 + 100 %
Table 02: MEOR, sensitive analysis on concentrations
Oil rate comparison
Well ORo [M3/D]
Pre-MEOR
ORm1 [M3/D]
Post-MEOR
Phase 1
ORm2 [M3/D]
Post-MEOR
Phase 2
ORm3 [M3/D]
Post-MEOR
Post. Modif.
PC-1020 H (V.O.) 8.8 18.3 13.0 17.0
PC-1020 H (V.O.) 19.9 33.9 14.6 20.7
PC-68 (C.R.I.) 3.9 4.4 5.9 6.1
PC-19 (C.R.I.) 2.3 4.4 8.3 Unmodified
PC-94 (V.O.) 13.6 23.9 15.5 Unmodified
PC-86 (V.O.) 8.0 8.2 6.7 11.7
Table 03: MEOR, Experimental Design results
SPE 53715 MICROBIAL ENHANCED OIL RECOVERY PILOT TEST IN PIEDRAS COLORADAS FIELD, ARGENTINA 11
Water Cut comparison
Well Wc [%]
Pre-MEOR
Wcm1 [%]
Post-MEOR
Phase 1
Wcm2 [%]
Post-MEOR
Phase 2
Wcm3 [%]
Post-MEOR
Post. Modif.
PC-1020 H (V.O.) 64.0 39.0 45.8 39.1
PC-1020 H (V.O.) 72.5 44.0 70.7 59.5
PC-68 (C.R.I.) 68.6 67.5 65.0 55.6
PC-19 (C.R.I.) 86.6 72.3 72.8 Not modified
PC-94 (V.O.) 62.3 51.6 58.7 Not modified
PC-86 (V.O.) 56.6 54.5 63.3 40.0
Table 04: MEOR, Experimental Design results
Oil viscosity comparison
Well µ apparent
Pre-MEOR
Control
[cp]
Laboratory
[cp] µ apparent
Post-MEOR
Series 1
[cp]
µ apparent
Post-MEOR
Series 2
[cp]
Temp.
[°F]
PC-1020 H (V.O.) 270-340 170 50 65 100
PC-1020 H (V.O.) 70 62 51 57 95
PC-68 (C.R.I.) 380 20 20 25 170
PC-19 (C.R.I.) 330 200 20 9 180
PC-94 (V.O.) 148 50 37 39 130
PC-86 (V.O.) 275 73 62 55 94
Table 05: MEOR, Oil viscosity alteration at MDT temperatures and below SR: 1 s-1
Geochemical parameters
Well Pristane/nC-17 Phytane/nC-18 Obs.
PC-1022 0.22 0.13 Rio Blanco Fm. (P. Coloradas)
PC-19 0.26 0.14 Barrancas Fm. (P. Coloradas)
LL-7 5.02 13.51 Llancanelo (extremely biodegrated oil)
Table 06: MEOR, Natural biodegration status in Piedras Coloradas oils
MEOR performance
Well IOR: (MEOR365 –1) x 100
[% over baselines] Oil Rates [M3/D]
Values at pilot start
PC-1020 H (V.O.) 118 8.8
PC-1022 H (V.O.) 68 19.9
PC-68 (C.R.I.) 92 3.9
PC-19 (C.R.I.) 97 2.3
PC-94 (V.O.) 124 13.6
PC-86 (V.O.) 60 8.0
Table 07: MEOR, Incremental Oil (Optimized, mid term inference)
12 M. A MAURE, F. L. DIETRICH, V. A. DIAZ, H. ARGAÑARAZ SPE 53715
Economic Analysis
Well VAN365
[M$] VAN1825
[M$] Pay Out
[Days] C.B.I.
[$/Incremental
barrel]
PC-1020 H (V.O.) 112 324 91 4.8
PC-1020 H (V.O.) 88 278 108 5.7
PC-68 (C.R.I.) 36 212 88 7.3
PC-19 (C.R.I.) 48 113 75 6.5
PC-94 (V.O.) 181 792 36 2.6
PC-86 (V.O.) 130 583 51 3.8
Table 08: MEOR, Profitability and cost parameters
Incremental Reserves and Economic Limits
Well Incremental Reserves at
economic limit
[MEOR - Conventional]
[Mm3]
Shiftment in economic
limits from Meor start
[MEOR - Conventional]
[Days]
PC-1020 H (V.O.) 18.7 - 9.8 2891 - 1890
PC-1020 H (V.O.) 25.7 - 11.1 3591 - 2822
PC-68 (C.R.I.) 17.5 - 17.5 1825 - 1825 *
PC-19 (C.R.I.) 8.4 - 3.7 1999 - 1188
PC-94 (V.O.) 39.7 - 39.7 3650 - 3650 *
PC-86 (V.O.) 31.8 - 31.8 3650 - 3650 *
Table 09: MEOR, comparative analysis (*, Economic limit is not reached)
Well Investment
First inoculation
Alt. 1, alt 2
[M$ - M$]
Periodic inoculations
program (annual cost)
Alt. 1, alt 2
[M$ - M$]
PC-1020 H (V.O.) 17.2 - 18.2 52.9 - 44.0
PC-1020 H (V.O.) 17.2 - 18.2 52.0 - 44.0
PC-68 (C.R.I.) 4.2 - 5.2 44.8 - 37.5
PC-19 (C.R.I.) 4.2 - 5.2 48.0 - 40.7
PC-94 (V.O.) 4.2 - 5.2 40.7 - 34.4
PC-86 (V.O.) 4.2 - 5.2 42.3 - 35.8
Table 10: MEOR, Range of Investment and Annual cost for two alternatives of treatments
in Piedras Coloradas field
SPE 53715 MICROBIAL ENHANCED OIL RECOVERY PILOT TEST IN PIEDRAS COLORADAS FIELD, ARGENTINA 13
Figures
Piedras Coloradas Field
(Cuyo Basin, Argentina)
Figure 1: Field Location
Quaternary
Terciary
Triasic
Paleozoic
Barrancas
Formation
Rio Blanco
Formation
Upper Member
Medium Member
Lower Member
Complex A
Layer A-1
Layers C, D
2050 M
A Member
B Member
C Member
2400 M
1800 M
2100 M
Figure 2: Target Reservoirs
Bacteria Size Ran
g
e
Rio Blanco Fm. ( V.O )
0
5
10
15
20
25
0.1 1 10 100
Poral throat diameter [Microns ]
Frecuency [ % ]
Bacteria Size Ran
g
e
Figure 3: Rio Blanco Fm., Poral Distribution and Bacteria Size
Barrancas Fm. (B.R.C.)
0
5
10
15
0.1 1 10 100
Poral throat diameter [ Microns ]
Frecuency [ % ]
Bacteria Size Ran
g
e
Figure 4: Barrancas Fm., Poral Distribution and Bacteria Size
Figure 5: Rio Blanco Fm., Pore Structures Figure 6: Barrancas Fm., Pore Structures
14 M. A MAURE, F. L. DIETRICH, V. A. DIAZ, H. ARGAÑARAZ SPE 53715
30
0
ORai
ORmax
10003000
Pilot_start
TiTx
,
3000 2000 1000 01000
0
10
20
30
Pre-Meor
Post-Meor
Oil rate [M3/D]
[Time from MEOR start, days]
Figure 7: Well PC-86, Production Response (V.O. Formation)
100
30
WCa i
WCma x
10003000
Pilot_start
TiTx
,
3000 2000 1000 0 1000
50
100
Pre-Meor
Post-Meor
Water cut [%]
[Time from MEOR start, days]
Figure 8: Well PC-86, Water Cut Response (V.O. Formation)
30
0
ORbi
ORmbx
10003000
Pilot_start
TiTx
,
3000 2000 1000 0 1000
0
10
20
30
Pre-Meor
Post-Meor
Oil rate [M3/D]
[Time from MEOR start, days]
Figure 9: Well PC-94, Production Response (V.O. Formation)
100
30
WCb i
WCmb x
10003000
Pilot_start
TiTx
,
3000 2000 1000 0 1000
50
100
Pre-Meor
Post-Meor
Water cut [%]
[Time from MEOR start, days]
Figure 10: Well PC-94, Water cut Response (V.O. Formation)
20
0
ORci
ORmc x
10003000
Pilot_start
TiTx
,
3000 2000 1000 0 1000
0
10
20
Pre-Meor
Post-Meor
Oil rate [M3/D]
[Time from MEOR start, days]
Figure 11: Well PC-19, Production Response (B.R.C. Formation)
100
0
WCc i
WCmc x
10003000
Pilot_start
TiTx
,
3000 2000 1000 0 1000
0
50
100
Pre-Meor
Post-Meor
Water cut [%]
[Time from MEOR start, days]
Figure 12: Well PC-19, Water Cut Response (B.R.C. Formation)
SPE 53715 MICROBIAL ENHANCED OIL RECOVERY PILOT TEST IN PIEDRAS COLORADAS FIELD, ARGENTINA 15
10
0
ORdi
ORmdx
10003000
Pilot_start
TiTx
,
3000 2000 1000 01000
0
5
10
Pre-Meor
Post-Meor
Oil rate [M3/D]
[Time from MEOR start, days]
Figure 13: Well PC-68, Production Response (B.R.C. Formation)
100
0
WCdi
WCmdx
10003000
Pilot_start
TiTx
,
3000 2000 1000 01000
0
50
100
Pre-Meor
Post-Meor
Water cut [%]
[Time from MEOR start, days]
Figure 14: Well PC-68, Water Cut Response (B.R.C. Formation)
60
0
ORei
ORmex
10002000
Pilot_start
TiTx
,
2000 1000 01000
0
20
40
60
Pre-Meor
Post-Meor
Oil rate [M3/D]
[Time from MEOR start, days]
Figure 15: Well PC-1020, Production Response (V.O. Formation)
100
20
WCei
WCmex
10002000
Pilot_start
TiTx
,
2000 1000 01000
50
100
Pre-Meor
Post-Meor
Water cut [%]
[Time from MEOR start, days]
Figure 16: Well PC-1020, Water Cut Response (V.O. Formation)
100
0
ORfi
ORmfx
10001400
Pilot_start
TiTx
,
1000 01000
0
50
100
Pre-Meor
Post-Meor
Oil rate [M3/D]
[Time from MEOR start, days]
Figure 17: Well PC-1022, Production Response (V.O. Formation)
100
40
WCfi
WCmfx
10001500
Pilot_start
TiTx
,
1000 01000
40
60
80
100
Pre-Meor
Post-Meor
Water cut [%]
[Time from MEOR start, days]
Figure 18: Well PC-1022, Water Cut Response (V.O. Formation)
16 M. A MAURE, F. L. DIETRICH, V. A. DIAZ, H. ARGAÑARAZ SPE 53715
Econ_lim
ORi
Qcpv
Qcpvco
3
Qcpvco
3
ORmu
Qcpmxkj
Qcpmykj
Qcpmzkj
Tecon_limTmeor_start
TiTxv
,
Txv
,
Txv
,
Tmu
,
kj
,
kj
,
kj
,
1500 1000 500 0 500 1000 1500 2000 2500 3000
0
5
10
15
20
25
30 Piedras Coloradas - Well: PC-1020 (H)
Time (days)
Oil Rate (M3/D]
Figure 19: MEOR Response, Control Bands On Baselines and Curve-Type sensitive Analysis
67.97
17.36
WCi
WCmu
200300
Tmeor_start
TiTmu
,
200 0200
0
20
40
60
80 Water Cut [%]
Time (days)
Figure 20: Water Cut Response in Horizontals
30
0.663
ORi
Qhv
Qhvco
3
Qhvco
4
Qcpv
ORmu
200300
Tmeor_start
TiTxv
,
Txv
,
Txv
,
Txv
,
Tmu
,
200 0 200
0
10
20
30 Oil Rate (M3/D)
Time (days)
Net oil (m3/day]
A
B
C
D
E
Figure 21: Oil Rate Response and Controllability
SPE 53715 MICROBIAL ENHANCED OIL RECOVERY PILOT TEST IN PIEDRAS COLORADAS FIELD, ARGENTINA 17
Econ_lim
ORi
Qhv
Qcpv
ORmu
Qcplw
Qm1y
Qm0y
Qm2y
Qcupy
Tmeor_start
TiTxv
,
Txv
,
Tmu
,
Txw
,
Tyy
,
Tyy
,
Tyy
,
Tycy
,
2000 1500 1000 500 0 500
0
5
10
15 Oil rates [M3/D]
Time (days)
Wellbore
Clean-Up
Reservoir
colonization
Figure 22: MEOR Clean-up effect discrimination from Reservoir Colonization Behaviour (PC-19 (Barrancas Fm.))
72.8
WRi
QWcpv
QWcpm1v
QWcpm2v
WCmu
QWcppq
00
TiTxv
,
Txv20
,
Txv10
,
Tmu
,
Txqq
,
500 0 500
0
20
40
60
80
100 Water Cut [%]
Time (days)
C1
C2
Baseline
Figure 23: Water Cut Evaluation Using MEOR Curve-Type
Analysis
Econ_lim
ORi
Qhv
Qcpv
ORmu
Qcplw
Qm1y
Tmeor_start
TiTxv
,
Txv
,
Tm u
,
Txw
,
Tyy
,
500 0 500
0
5
10
15 Oil Rates [M3/D]
Time (days)
U
V
W
I
Figure 24: Long Term MEOR Response need to be evaluated
using V-W curve segment and after clean-up baseline (dashed
decline baseline, " I " difference)
18 M. A MAURE, F. L. DIETRICH, V. A. DIAZ, H. ARGAÑARAZ SPE 53715
ORtoti
ORtotmx
Pilot_start
TiTx
,
1000 500 0 500
0
50
100
Pre-Meor
Post-Meor
Oil Rate [M3/D]
[Time from MEOR start, days]
Figure 25: MEOR Perfomance (Six Well Composite)
WRtoti
WRtotm x
Pilot_start
TiTx
,
1000 500 0500
40
60
80
100
Pre-Meor
Post-Meor
Water cut [%]
[Time from MEOR start, days]
Figure 26: MEOR Perfomance (Six Well Composite)
ORtoti
ORtotmx
Pilot_start
TiTx
,
1000 500 0500
0
5
10
15
20
Pre-Meor
Post-Meor
Oil Rate [M3/D]
[Time from MEOR start, days]
Figure 27: MEOR Performance (Barrancas Fm.)
WRtoti
WRtotm x
Pilot_start
TiTx
,
1000 500 0 500
40
60
80
100
Pre-Meor
Post-Meor
Water cut [%]
[Time from MEOR start, days]
Figure 28: MEOR Performance (Barrancas Fm.)
ORtoti
ORtotmx
Pilot_start
TiTx
,
1000 500 0500
20
40
60
80
Pre-Meor
Post-Meor
Oil Rate [M3/D]
[Time from MEOR start, days]
Figure 29 MEOR Performance (Rio Blanco Fm.)
WRtoti
WRtotmx
Pilot_start
TiTx
,
1000 500 0500
30
40
50
60
Pre-Meor
Post-Meor
Water cut [%]
[Time from MEOR start, days]
Figure 30: MEOR Performance (Rio Blanco Fm.)
SPE 53715 MICROBIAL ENHANCED OIL RECOVERY PILOT TEST IN PIEDRAS COLORADAS FIELD, ARGENTINA 19
012345678910 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40
0
2
4
Pre-Meor
Post-Meor
PC-1022 - Normal Alkanes
Carbon order
p.p.m.
012345678910 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40
0
2
4
Pre-Meor
Post-Meor
PC-1022 - Branched Alkanes
Carbon order
p.p.m.
S1
S2
S3
S4 S5
Figure 31: MEOR, Geochemical Signature (Rio Blanco Oil, Horizontal Completion)
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40
0
2
4
Pre-Meor
Post-Meor
PC-19 - Normal Alkanes
Carbon order
p.p.m.
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40
0
2
4
6
Pre-Meor
Post-Meor
PC-19 - Branched Alkanes
Carbon order
p.p.m.
Figure 32: MEOR, Geochemical Signature (Barrancas Oil, Vertical Completion)
20 M. A MAURE, F. L. DIETRICH, V. A. DIAZ, H. ARGAÑARAZ SPE 53715
350
15
0 5 10 15
0
50
100
150
200
250
300
350
400
450
500
Control at Low Shear Rate (Pre-Meor)
Lab biodegradated (Pre-Meor inference)
Lab biodegradated (Pre-Meor inference, duplicate)
Post-Meor (after fifth treament)
Post-Meor (after third treatment)
Viscosity [mpa.s] vs. shear rate [1/s]
Shear rate [1/s]
Viscosity [mpa.s]
Control
Lab Inference
T5, Field
T3,
Field
Figure 33: Rheological Signature, PC- 1020 H
10
50
100 Reservoir_temperature
80 100 120 140 160 180 200
0
500
1000
1500
Control, Pre-Meor
Control, Pre-Meor (duplicate)
In-Vitro biodegradation, Pre-Meor Lab Inference
Post-Meor (after third treatment), field sample
Post-Meor (after third treatment), duplicate
Post-Meor (after fifth treatment), field sample
Post-Meor (after fifth treatment), duplicate
Viscosity vs Temperature
Temperatura (F. deg.)
Viscosidad (mPa.s)
Figure 34: Pour and Cloud Point alteration, PC- 1020 H
350
1
0 1 2 3
0
50
100
150
200
250
300
350
400
450
500
Control at Low Shear Rate (Pre-Meor)
Lab biodegradated (Pre-Meor inference)
Lab biodegradated (Pre-Meor inference, duplicate)
Post-Meor (after fifth treament)
Post-Meor (after third treatment)
Viscosity [mpa.s] vs. shear rate [1/s]
Shear rate [1/s]
Viscosity [mpa.s]
Figure 35: Rheological Signature, PC-19 (Vertical)
340
180
92 Reservoir_temperature
80 100 120 140 160 180 200
0
500
1000
1500
2000
Control, Pre-Meor
In-Vitro biodegradation, Pre-Meor Lab Inference
Post-Meor (after third treatment), field sample
Post-Meor (after third treatment), duplicate
Post-Meor (after fifth treatment), field sample
Post-Meor (after fifth treament), duplicate
Viscosity vs Temperature
Temperatura (F. deg.)
Viscosidad (mPa.s)
Figure 36: Pour and Cloud Point alteration, PC- 19 (Vertical)
SPE 53715 MICROBIAL ENHANCED OIL RECOVERY PILOT TEST IN PIEDRAS COLORADAS FIELD, ARGENTINA 21
PC-1020 (Horizontal)
2059 - 2 672 (T.D.) M
Tbg. 2 7/8" - J55 - 6.5 lb/ft
Csg. 7"- J55 - 23 lb/ft.
Rio Blanco Fm.
Oil: 8.8 M3/D
Water Cut: 64 %
Piedras Co loradas F ield
Pump Intake
(2008.6 M)
SBHT: 18 0 F
SBHP: 1560 psi
GOR < 100
SRP lifting device
Dynamic
Fluid Level
(1818 M)
Production Data (April 97)
Slotted liner 5"- 15 lb/ft.
Anchor 7" x 5"
Horizontal lenght 500 M
Figure 37: Horizontal completion and extractive system
PC-19
2009/212 7 M
Tbg. 2 7/8" - J55 - 6.5 lb/ft
Csg. 7"- J55 - 23 lb/ft.
Barrancas Fm.
Oil: 2.3 M3/D
Water Cut: 86 %
Piedras Co loradas F ield
Pump Intake
(2093.6 M)
2126 M
SBHT: 17 0 F
SBHP: 498 p si
GOR < 100
SRP lifting device
Dynamic
Fluid Level
(1473 M)
Production Data (April 97)
Figure 38: Vertical Completion and extractive system
PH
Cl
SO4
CO3Ca
CO3H
Ca
M
g
Na
1
10
100
1000
10000
100000
12345678
Concentrations in mg/liter
PC- 7
PC- 1 3
PC- 6 8
PC- 8 6
PC- 1 9
PC- 9 4
PC-1020
PC-1022
T-80
FIgure39: Formation Water, Typical Ionic Pattern
22 M. A MAURE, F. L. DIETRICH, V. A. DIAZ, H. ARGAÑARAZ SPE 53715
AB
Positive
displacement
pump
AB
Positive
displacement
pump
PC-1020
Piedras Co loradas F ield
Step 01 Step 02
Step 03 Step 04
Blending area
Prod#1
Prod#4
Prod#5
Prod#6
Formation water
used for blending
(150 bbls.)
Formation water
used for displacement
(Var iable fr om well to we ll)
Blending formulation by diluting microbial cultures in
formation water
Microbial concentrates
(From five gallons drums)
Microbia l blending injection by annulus (1 to 2 BPM)
Low Rate Squeeze into fo rmation Shut-in period
(latency)
The well is
closed during 72 hours.
AB
Oil
Water
Gas
Step 05
Well is restablished to production
using standard pulling operation
Displacement water
Microbial Blend
Produced fluids
References
PC-1020 (Horizontal)
Piedras Co loradas F ield
2059 - 2 672 (T.D.) M
Tbg. 2 7/8" - J55 - 6.5 lb/ft
Csg. 7"- J55 - 23 lb/ft.
Rio Blanco Fm.
Pump Intake
(2008.6 M)
SBHT: 18 0 F
SBHP: 1560 psi
Dynamic
Fluid Level
(1818 M)
Slotted liner
5"- 15 lb/ ft.
Anchor 7" x 5"
Horizontal lenght 500 M
Retrievable Packer
Tbg. 2 7/8" - J55 - 6.5 lb/ft
Csg. 7"- J55 - 23 lb/ft.
Rio Blanco Fm.
Retrievable Packer
Tbg. 2 7/8" - J55 - 6.5 lb/ft
Csg. 7"- J55 - 23 lb/ft.
Anchor 7" x 5"
Retrievable Packer
Tbg. 2 7/8" - J55 - 6.5 lb/ft
Csg. 7"- J55 - 23 lb/ft.
Slotted liner
5"- 15 lb/ ft.
Anchor 7" x 5"
Closed
Pump Intake
Dynamic
Fluid Level
Critical Penetration Radii
according with Kv/Kh
perm eabilit ies rat io
Figure 40: Operative Procedure used to Inoculate Horizontal Wells (Initial Treatment), PC-1020 H
SPE 53715 MICROBIAL ENHANCED OIL RECOVERY PILOT TEST IN PIEDRAS COLORADAS FIELD, ARGENTINA 23
AB
Positive
displacement
pump
2126 M
AB
Positive
displacement
pump
2009/2127 M
Tbg. 2 7/8" - J55 - 6.5 lb/ft
Csg. 7"- J55 - 23 lb/ft.
Barrancas Fm.
Pump Intake
(2093.6 M)
2126 M
SBHT: 170 F
SBHP: 498 psi
SRP lifting device
Dynamic
Fluid Level
(1473 M)
PC-19
Piedras Coloradas Field
Peforated interval
Step 01 Step 02
Step 03 Step 04
Blending area
Prod#1
Prod#4
Prod#5
Prod#6
Formation water
used for blending
(20 to 50 bbls.)
Formation water
used for displacement
(Variable from well to well)
Blending formulation diluting microbial cultures in
formation water
Microbial concentrates
(From five gallons drums)
Microbial blending injection by annulus (1 to 2 BPM)
Low Rate Gravity Displacement into formation Shut-in period
(latency)
The well is
closed during 24 hours.
AB
2126 M
Critical Radius
2126 M
Oil
Water
Gas
Step 05
Well is restablished to production
Dynamic
Fluid Level
Static
Fluid Level
Displacement water
Microbial Blend
Produced fluids
References
Peforated interval
Barrancas Fm.
Figure 41: Operative Procedure used to Inoculate Vertical Wells (Initial and Periodic Treatment), PC-19 V
24 M. A MAURE, F. L. DIETRICH, V. A. DIAZ, H. ARGAÑARAZ SPE 53715
Annex A
NI
µ
app control minSR
µ
app control maxSR
µ
app inoculated minSR
µ
app inoculted maxSR
TMD
DV minSR
maxSR
i
µ
app i
control
= minSR
maxSR
i
µ
app i
inoculated
=
minSR
maxSR
i
µ
app i
control
=
TMD
EOR 1
1DV
()
Where:
NI Newtonian Index
DV Delta Viscosity
EOR Enhanced Oil Recovery index
minSR Minimum explored Shear Rate, [1/sec]
maxSR Maximum explored Shear Rate, [1/sec]
Apparent viscosity measured at min
SR on control oil
µ
app control minSR
Apparent viscosity measured at SR (i )
on control oil
µ
app i
control
Apparent viscosity measured at SR (i )
on inoculated oil
µ
app i
inoculated
TMD Temperature of Maximun Discriminatio
n
of rheological properties
15
0 5 10 15
30
33
36
39
42
45
48
51
54
57
60
1+
2+
3
4
5
6
BB
Control
Viscosity [mpa.s] vs. shear rate [1/s]
Shear rate [1/s]
Viscosity [mpa.s]
minSR maxS
R
µ
app i
control
µ
app i
inoculated
SRi
Figure 42: Methodology to analize MEOR microbial
subcommunities (1 to 6, BB) in oils
340
180
92 Reservoir_temperature
80 100 120 140 160 180 200
0
500
1000
1500
2000
Control, Pre-Meor
In-Vitro biodegradation, Pre-Meor Lab Inferenc
e
Post-Meor (after third treatment), field sample
Post-Meor (after third treatment), duplicate
Post-Meor (after fifth treatment), field sample
Post-Meor (after fifth treament), duplicate
Viscosity vs Temperature
Temperatura (F. deg.)
Viscosidad (mPa.s)
Rcontrol
R3
R5
TMD
tg1
Tg2
Ts
Figure 43: Compositional changes in treated (lab, field) and
untreated samples (control). Rcontrol, R3 and R5 are indicators of
molecular homogeneity, Ts is the shift in precipitation points.
SPE 53715 MICROBIAL ENHANCED OIL RECOVERY PILOT TEST IN PIEDRAS COLORADAS FIELD, ARGENTINA 25
Annex B
MEOR ti
Qmeor ti
Pe Pwfmeor ti
Qo ti
Pe Pwf ti
where:
Qo tiDeclined oil production
(convtentional), [BOPD]
Qmeor tiEnhanced oil production
[BOPD]
Pwf tiPwfmeor ti
,
Dynamics pressures, [psi]
Pe Static reservoir pressure, [psi]
Radial model case with:
MEOR ti
A
BtiCtiD
.
P
.
ζ
.δ
.
tiElapset time from
MEOR start [days]
Associated equations
A1
ξ
etv
Bti1 RDie ti
etv
Cti1 RDiw ti
etmv
D
ξ
etmv
P
ν
β
η
Factor
.
.
λ
δ
Ktmv
Ktv
ζ
1 ntv
1 ntmv
Factor 2106
.
24 3600
.π
.
Scale factor
h
Qo (ti), Qw(ti), Qg(ti)
Rm, R(ti)
Re
Rw
Sw,So
Swirr, Sor
Kro,Krw,Kabs
Ø
Ktmv,ntmvKtv,ntv
Kv
Kh
Effective Lenght, L
Vertical Section
PC-68, PC-19
(Barrancas Fm.)
PC-86, PC-94
(Rio Blanco Fm)
Horizontal Section, PC-1020, PC-1022, Rio Blanco Fm.
Figure 44: Simplified diagram showing completions and colonized zones (bioreactors) coupled with untreated outer areas
26 DIETRICH F.A., MAURE M.A, DIAZ V.A., ARGAÑARAZ H. SPE 53715
Annex C
Geochemical Methods and instrumentation
Fractionation by Liquid Chromatography: Asphaltenes are
precipitated with hexane and soluble fraction is separated into
saturate hydrocarbons, aromatic hydrocarbons and resins/NSO
compounds on a silica column by successive elutions with
hexane, benzene, and benzene-methanol. The solvents are
evaporated and weight percent of each fraction is determined.
Gas Chromatography (GC): The whole oil is analyzed with
a Varian model 3300 gas chromatograph fitted with a 50 m
fused silica capillary column. Analytical data are processed
with a Nelson Analytical Model 3000 chromatography data
system.
Very High Resolution C7 Gas Chromatography: A sample
of oil is injected directly into a Varian model 3400 gas
chromatograph fitted with a split injector and a Quadrex 100
meter fused silica capillary column. The GC run is isothermal
at 35°C while collecting the data from C2 – C8 , then heated to
purge the remaining sample from the column. Analytical data
are processed with a Nelson Analytical model 3000
chromatographic data system and IBM computer hardware.
Biomarker Analysis (GC-MS): The saturate or aromatic
fractions separated by liquid chromatography from whole oils
or source rocks extracts are injected into a HP5890 gas
chromatograph coupled to the HP5971A MSD. The Selected
Ion Monitoring (SIM) capabilities of the computer data
acquisition system permit specific ions to be monitored. Ion
m/z = 191 allows characterization of specific saturate
triterpenoid compounds and m/z = 217 certain saturate
steranes. The ions m/z = 253 and 231 are respectively specific
for mono and triaromatic steroids; m/z = 156 and 170, for C2–
naphthalenes; m/z = 178 and 192, for phenanthrene and
methylphenanthrenes, respectively; m/z = 184 and 198, for
dibenzothiophene and methyldibenzothiophene, respectively.
SPE 53715 MICROBIAL ENHANCED OIL RECOVERY PILOT TEST IN PIEDRAS COLORADAS FIELD, ARGENTINA 27
Nomenclature
ψ
= anisotropy factor
k
µ
= apparent viscosity based on Ostwald de Waele
Nutting rheological model, [cp]
α
= apparent viscosity relationship after and before
MEOR evaluated at 1 sec –1 (shear rate), [cp]
app
µ
= apparent viscosity, [cp]
β
= beta parameter as function of total well
production (QT), water cut (Wc) and poral
volume, [days]
λ
= derived rheological parameter, dimensionless
ν
= perforated interval (h) to drainage radius (Re)
coefficient, dimensionless
η
= perforated interval (h) to mean poral radius
(Dpmic), dimensionless
ξ
= wellbore radius (Rw) to drainage radius (Re)
coefficient, dimensionless
ζ
= conventional to enhanced rheological parameter,
dimensionless
δ
= conventional to enhanced rheological parameter,
dimensionless
ε
= reservoir Microbial Migration Efficiency
(RMME), dimensionless
A,B,C,D = intermediate variables, dimensionless
Bo = volume factor, [std m3/reservoir m3]
Dpmic = mean poral throat diameter, [
µ
m]
DV = Delta Viscosity index
EOR = EOR index
etmv = derived rheological parameter, dimensionless
etv = derived rheological parameter, dimensionless
Factor = scale factor
GOR = gas oil relationship, [m3/ m3]
h(h) = effective interval, [m]
K = absolute permeability, [md]
Kh= horizontal permeability, [md]
Kr = relative permeability, dimensionless
Ktmv,Ktv = first Ostwald de Waele Nutting rheological
parameters, after MEOR (Krmv) to conventional
(Ktv), [cp.(1/s)(ntv-1)]
Kv= vertical permeability, [md]
L = effective lenght, horizontal well, [m]
maxSR =maximum explored Shear Rate, [1/s]
)( i
t
MEOR = productivity index ratio, MEOR performance
index, dimensionless
Mf = rotational to capillary geometry correction factor
minSR =minimun explored Shear Rate, [1/s]
NI = Newtonian index
ntmv,ntv = second Ostwald de Waele Nutting rheological
parameters, after MEOR (ntmv) to conventional
(ntv), dimensionless
P = derived scaling group
pwf = dynamic pressure before MEOR, [psi]
pwfmeor = dynamic pressure after MEOR, [psi]
Pe = static reservoir pressure, [psi]
)( i
t
Qmeor = oil rate after MEOR, [m3]
)( i
t
Qo = oil rate before MEOR, [m3]
)( i
t
R= migration radius at time ti, [m]
)( i
t
RDie = instantaneous migration radius at timetito
drainage radius, dimensionless
)( i
t
RDiw = instantaneous migration radius at timetito
wellbore radius, dimensionless
Re = drainage radius, [m]
Rm = radius of microbial bioreactor (size of colonized
zone) [m]
Rw = wellbore radius, [m]
Rwhoriz = equivalent wellbore radius, horizontal well, [m]
Sirr = irreductible water saturation
Sor = residual oil saturation
SR = shear rate, [1/s]
TMD = Temperature of Maximum Discrimination of
rheological properties, [
°
F]
p
V = poral volume at drainage radius (Re), net pay (h)
and porosity (Por), [m3]
Vrest = restricted Microbial Migration Velocity, [m/day]
Vfree = unrestricted Microbial Migration Velocity,
[m/day]
Subscripts
control = original sample condition (pre MEOR)
e = natural logarithms base, 2.7172...
h = horizontal.
i = data point, spatial reference
m = microbial enhanced
max = maximum
min = minimum
o = original
t = time
v = vertical
x = direction along well axis
y = direction perpendicular to well axis
28 DIETRICH F.A., MAURE M.A, DIAZ V.A., ARGAÑARAZ H. SPE 53715
Equations
)(
)(
)(
)(
)(
i
i
i
i
i
t
t
t
t
T
PwfPe
Qo
PwfmeorPe
Qmeor
MEOR
−
−
=.............................. (Eq. 1)
δ
ζ
....
)()(
)( PDCB
A
MEOR
ii
itt
t−
=........................... (Eq. 2)
yxh KKK .
=....................................................... (Eq. 3)
v
h
K
K
=
ψ
.................................................................. (Eq. 4)
)1.(
2
ψ
+= Rw
Rwhoriz ........................................ (Eq. 5)
ψ
hh h=
)( ............................................................. (Eq. 6)
etv
A
ξ
−= 1.............................................................(Eq. 7)
etv
tt ii RDieB)(1 )()( −= ............................................ (Eq. 8)
etmv
tt ii RDiwC )(1 )()( −= ......................................... (Eq. 9)
etmv
D
ξ
=.............................................................. (Eq. 10)
λ
η
β
)
.
.( factor
vP =................................................ (Eq. 11)
λ
δ
Ktv
Ktmv
=........................................................... (Eq. 12)
ntmv
ntv
−
−
=1
1
ζ
......................................................... (Eq. 13)
π
.3600.24
10.2 6−
=
Factor ............................................ (Eq. 14)
appo
appm
µ
µ
α
=.......................................................... (Eq. 15)
Vfree
Vrest
=
ε
.............................................................. (Eq. 16)
RmeR i
i
tVrest
t).1( .
)( −= ..........................................(Eq. 17)
)1.( WcQT
Vp
−
=
β
..................................................(Eq. 19)
PorhVp .
4
Re.2
π
=................................................(Eq. 20)
Re
h
v=..................................................................(Eq. 21)
Re
L
v=..................................................................(Eq. 22)
6
10.
.2
−
=Dpmic
h
η
...................................................(Eq. 23)
Re
Rw
=
ξ
.................................................................(Eq. 24)
Rw
R
Rdiw i
i
t
t
)(
)( =.....................................................(Eq. 25)
Re
)(
)( i
i
t
t
R
Rdie =......................................................(Eq. 26)
)1(
).( −
=ntv
kk SRKtv
µ
.............................................(Eq. 27)
ntmvntv −=
λ
......................................................(Eq. 28)
ntvetv −= 1 ..........................................................(Eq. 29)
ntmvetmv −= 1 .....................................................(Eq. 30)
ntmv
ntmv
ntmv
Mf )
.4
1.3
(+
=...........................................(Eq. 31)
TMD
SRinoculatedSRinoculated
SRcontrolSRcontrol
appapp
appapp
NI )
)()(
)()(
(maxmin
maxmin
µ
µ
µ
µ
−
−
=
...............................................................................(Eq. 32)
TMD
SR
SRi
control
i
SR
SRi
inoculated
i
SR
SRi
control
i
app
appapp
DV )
)(
)()(
(max
min
max
min
max
min
∑
∑∑
=
==
−
=
µ
µ
µ
......................................................................................(Eq.33)
DV
EOR −
=1
1.....................................................(Eq. 34)
SPE 53715 MICROBIAL ENHANCED OIL RECOVERY PILOT TEST IN PIEDRAS COLORADAS FIELD, ARGENTINA 29
