This document summarizes a numerical simulation study that modeled gel treatments in injector and producer wells in fractured high pressure high temperature (HPHT) reservoirs in Eastern Venezuela. The simulation model was developed based on field and lab data to predict the reservoir response to gel treatments for sealing induced fractures and high permeability channels. The model included parameters for gel adsorption and permeability reduction based on lab data for a polyacrylamide gel system. The model was history matched to field production data from a well that saw improved sweep efficiency and an incremental oil rate increase after a gel treatment. The developed simulation model can be used as a tool to predict production performance and assist in planning optimized gel treatment scenarios.

1. SPE 92003
Reservoirs Simulations of Gel Treatments to Control Water Production, Improve
the Sweep Efficiency and the Conformance Factor in Eastern Venezuelan HPHT
Fractured Reservoirs
Julio Herbas, Herbas Consultore Asociados; Sujit Kumar, Schlumberger; Raul Moreno, HCA; Maria F. Romero,
U. Central de Venezuela; and Horacio Avendaño, RASA
Copyright 2004, Society of Petroleum Engineers Inc.
This paper was prepared for presentation at the 2004 SPE International Petroleum Conference
in Mexico held in Puebla, Mexico, 8–9 November 2004.
This paper was selected for presentation by an SPE Program Committee following review of
information contained in a proposal submitted by the author(s). Contents of the paper, as
presented, have not been reviewed by the Society of Petroleum Engineers and are subject to
correction by the author(s). The material, as presented, does not necessarily reflect any
position of the Society of Petroleum Engineers, its officers, or members. Papers presented at
SPE meetings are subject to publication review by Editorial Committees of the Society of
Petroleum Engineers. Electronic reproduction, distribution, or storage of any part of this paper
for commercial purposes without the written consent of the Society of Petroleum Engineers is
prohibited. Permission to reproduce in print is restricted to a proposal of not more than 300
words; illustrations may not be copied. The proposal must contain conspicuous
acknowledgment of where and by whom the paper was presented. Write Librarian, SPE, P.O.
Box 833836, Richardson, TX 75083-3836, U.S.A., fax 01-972-952-9435.
Abstract
A numerical simulation study was undertaken to model the gel
treatments in injector and producer wells in Eastern Venezuela
Fractured HPHT Reservoirs in exploitation under secondary
and tertiary recovery process.
The objective of the simulation study is to develop a
numerical simulation model based on field and laboratory data
to model the gel treatments to block induced fractures and
high permeable channels in water injection and oil producer
wells, and to improve the conformance and the recovery
factors.
Field data representation of a HPHT Fractured Venezuelan
reservoir with preferential water movement and induced
fractures was used to build a conformance field prototype
model.
The gel used in the simulation study is a polymer system
composed by polyacrylamide with phenol and formaldehyde
crosslinkers suitable to stand HPHT reservoir conditions.
Available laboratory work and field data to characterise the
performance of polymer gels in fractured wells were included
in the model and were history matched to predict alternate gel
treatment scenarios.
The developed simulation model provides a tool to predict the
production performance of gel treatment in Eastern Venezuela
Fractured HPHT Reservoirs under different treatment
scenarios; useful to assist in the determination of: optimum
treatment intervals, optimum procedures; and to develop data
for economic evaluations, improving the design of gel
treatment and reducing associated uncertainties.
Introduction
By 1992, a water injection secondary recovery project was
designed and implemented in a high pressure high
temperature, Eastern Venezuela reservoir that exhibited about
100% of overpressure over the normal pressure gradient. It
contains medium oil with variable composition.
The production mechanisms in this reservoir are rock and fluid
expansion; with a primary recovery factor estimated in 21%
and near 40% for the water displacement at pressures above
the saturation point1
.
After several years of water injection, most of the first line
wells shown an early water breakthrough, high water cuts and
reduction in the oil rates. Since then, several technologies to
mitigate the detrimental water breakthrough effects have been
evaluated, including the gel treatment in producer and injector
wells, as to improve the conformance factor and to produce
the secondary reserves estimated for the water displacement
process2
.
The gel treatments in water injector and in oil producer wells
are commonly designed by estimating empirically the volume
required to seal a high permeable channel or interpreted
induced fractures. The incremental production to be obtained
from the gel treatment is also empirically estimated.
Some operators have performed water shut off simulations
assuming a total sealing effect in the treated intervals3
.
However this assumption does not model the effects of the
adsorbed gel on the porous media, the permeability reduction
factor, nor the gel penetration into the reservoir.
This work was performed with the objective to develop a
prototype simulation model to predict quantitatively with a
black oil simulator, the reservoir response to the gel treatments
to seal induced fractures in water injection wells and highly
permeable channels in producer wells. The final objective is
to increase the feasibility of success of the gel treatments and
to provide a tool to generate data for economic evaluations
before the treatment.
The ECLIPSE black oil reservoir simulator was used to build
a prototype gel injection model for HPHT Eastern Venezuelan
HP HT reservoirs.

2. 2 SPE 92003
Chemical Parameters to Model the Gel Kinetics in a
Simulation Study
The gel used in this simulation study is a formulation
composed by a polymer polycrilamide and two organic
crosslinkers: phenol and formaldehyde4
.
The gel kinetic in the reservoir is defined using the basic
viscous-elastic theory. In the laboratory measures of the
Complex modulus (G*), Storage modulus (G’), Loss modulus
(G’’) and the shift angle (δ) were performed.
The rate of change in the Storage modulus G’, is proportional
to the rate of change of crosslink density. As the gelation
reaction proceeds, the number of crosslinks increases, causing
the storage modulus G’ to increase; therefore, dynamic
mechanical measurements of the storage modulus can be used
to follow the kinetics of crosslink formation.
The shear modulus of a gel sample (G) was correlated with
storage module (G') obtained in dynamic rheological
experiments. Applying a test with low frequencies (ω) inside
an interval of deformation time, then plots of G' and G'' versus
time were developed, and gelling time calculated when G' and
G'' are constant.
The most important property of the polymeric gels is crosslink
density. Elasticity theory has shown a relationship between the
storage modulus of a gel (G') at low frequencies and the
crosslink density (ν) given by:
G’ = q R T ν + Gen (1)
For isothermal systems, and assuming that Gen is constant, the
equation as a function of time is equivalent to:
δG’/δt = q R T δν/δt. (2)
The speed of change of G' (δG'/δt) is directly proportional to
the rate of change of crosslink density (δν/δt). Therefore, as
the reaction proceeds, the number of crosslinks increases
causing the storage modulus to increase, thereby defining the
gel kinetics.
Reservoir Modelling of the Gel Treatment
The Gel simulation study was performed using the ECLIPSE
Polymer Flood Model that assumes the flow of polymer
solution through the porous media has no influence on the
flow of the hydrocarbon phases.
When a polymer solution is injected into the reservoir some
molecules are adsorbed onto the rock surfaces. Mechanical
entrapments of large molecules at small pore throats may
occur. A further effect caused by adsorption and entrapment
processes is a reduction in the relative permeability of the
polymer solution, due to an interaction between the aqueous
solution and the polymer retained by the rock. For modelling
purposes it is assumed that the reduction in permeability of the
polymer solution is proportional to the quantity of polymer
adsorbed onto the rock. The permeability of the rock to water
is thus permanently reduced after the passage of a polymer
compared to its value before the passage5
.
Treatment of Polymer Adsorption. Adsorption is treated as
an instantaneous effect; the polymer adsorption is to create a
stripped water bank at the leading edge of the slug. The model
handles stripping and desorption effects by an adsorption
isotherm that tabulates the adsorbed polymer concentration
versus the polymer concentration in the solution.
There are two adsorption models, the first ensures that each
grid cell retraces the adsorption isotherm as the polymer
concentration rises and falls in the cell; the second assumes
that the adsorbed polymer concentration on the rock may not
decrease with time and hence does not allow for any
desorption5
.
Treatment of Permeability Reduction. The adsorption
process causes a reduction in the permeability of the rock to
the passage of the aqueous phase and is directly correlated
with the adsorbed polymer concentration. The effect on pore
blocking and adsorption on the aqueous phase relative
permeability is treated through the term, Rk, which requires the
input of a residual resistant factor for each rock type. To
compute the reduction in rock permeability (Rk) it is required
to specify the residual resistant factor (RFF), then the actual
resistant factor can be calculated with the formula:
Rk = 1+ (RRF-1) Ca/Ca max (3)
The maximum adsorbed concentration (Ca max) depends on the
rock type and needs to be specified. The dead pore space
represents the total pore space in each cell that is inaccessible
to the polymer solution.
The ECLIPSE Polymer Flood Model modifies the standard
water equation and introduces additional equations to describe
the flow of polymer and brine within the finite difference grid,
as follows:
d/dt [VSw/BrBw] =∑[(Tkrw/Bw µweff Rk) (δPw- ρwgDz)]+Qw
(4)
d/dt[VSw*Cp/BrBw]+d/dt[VρrCa(1-φ)/φ]=∑[((Tkrw Cp)/(Bw
µpeff Rk)) (δPw- ρwgDz)]+QwCp (5)
d/dt[VSwCn/BrBw]=∑[(TkrwCp/BwµpeffRk)(δPw-
ρwgDz)]+QwCn (6)
Sw* = Sw - Sdpv (7)
The ECLIPSE model assumes that the density and formation
volume factors of the aqueous phase are independent of the
local polymer and sodium chloride concentration in the
aqueous phase, where the degree of mixing is specified
through the viscosity terms in the conservation equations. The
polymer solution, reservoir brine and the injected water are
represented in the model as miscible components.

3. SPE 92003 3
The principal effects of polymer and brine on the flow of the
aqueous phase are represented by equations 4 and 7. The fluid
viscosities (µpeff, µseff) are independent on the local
concentrations of polymer and salt in the solution.
The polymer adsorption is represented by the additional mass
accumulation term on the left hand side of equation 5. The
adsorption term requires specifying the adsorption isotherm,
Ca as a function of the local polymer concentration for each
rock type5
.
Reservoir Description
North Monagas HPHT reservoirs considered in this study are
highly overpressured composed of consolidated sandstones
with shale breaks that correlate well to well. The reservoir
structure is an anticline 13,500 feet depth that contains
medium oil with a variable composition from 29° API at the
top to 15 ° API at the bottom6
.
Limited core description has identified fractures as granulation
fractures and open fractures, its population remains a key
reservoir uncertainty. Granulation fractures act as baffles to
fluid flow and reduces horizontal permeability, in contrast
open fractures may significantly increase the effective vertical
permeability and act as thief zones during water injection7
.
The sand thickness, porosities and horizontal permeabilities,
are shown in table 2, the vertical permeability was defined
with a 0.2 Kv/Kh ratio, and shale breaks of 20 feet thickness
separate the main producer sands.
Field Production and Injection Data
The production data for the model was obtained from the
literature 2
; the reservoir was produced by natural depletion, to
reduce the pressure from an initial value of 11,514 psia, until it
reached 6,500 psia, then water injection was started in the year
1992 at balanced injection rates to maintain an average
pressure of 6,500 psia similar to the operational conditions in
the North Monagas HPHT reservoirs.
In the field data, a gel treatment was performed in an injector
well; before the treatment in the injector the associated
producer well was producing around 120 BOPD of 24° API
oil per day at 80-85 % water cut (Figure 1).
After the treatment in the injector well, the producer well
exhibited a reduction in the water cut to 30-40 % and an
incremental oil rate of 1,200 bbl per day.
3-D Prototype Model
A conceptual prototype reservoir model was built based on
structural, petrophysical, fluid and production data
representative of a depth North Monagas waterflood pattern.
The model represents a reservoir section with 5 hydraulic
units, 784 feet thickness at 13,000 feet depth. A producer well
is located in the top and a water injector well at the bottom
(Figure 2).
Fluid Properties An extended PVT data set was used to
represent the oil column with variable composition from 29°
to 14° API in a reservoir section with 784´thickness
representative of North Monagas1
depth. A bubble point
pressure varying with depth table was also set as given below:
Table 1 Bubble Point Pressure versus Depth
Depth (feet) Bubble Point Pressure (psi)
12,000 4,980
14,000 3,800
15,000 2,993
The oil viscosity at reference pressure 4,110 psia and 296 °F is
0.427 cP; and the gas in solution is 1,090 scf/bbl. The oil
formation volume factor at bubble point is 1.205, the fluid
compressibility 3.2E-06 psi-1 and 7.25E-06 psi-1 for water
and oil respectively.
The water saturation was defined constant equal to 0.071, and
relative permeability’s for oil-water and gas-oil systems were
generated with Corey type end points for North Monagas
intermediate wettability rocks.
The model was initialised at 11,514 psia and 290 °F at 14,500
feet reference depth. Initial fluid saturation and pressures in
the model were calculated for equilibrium conditions.
The grid model has 25,296 grid blocks, with 34 x 24 x 31 cells
in the X, Y and Z direction. Dimensions in X an Y (Figure 3
& 4) are:
• X direction 34 blocks: 3x21´, 1x11’, 4x5´, 3x21’, 2x43´,
6x86´, 2x43´, 4x21´, 1x11´, 4x5’, 1x3´, 2x21´.
• Y direction 24 blocks: 2x84’, 2x21’, 3x14’, 10x7´, 2x10,
2x21´, 1x42´, 2x21´.
In the Z direction 31 layers were defined representing 5
hydraulic units (Table 2 & Figure 4).
Table 2. Rock Properties 3-D Model
Hydraulic
Unit
Layers Rock Type Porosity (%) Permeability
(mDarcys)
1 1-5 Sandstone 15 150
6 Shale 3 10
2 7-11 Sandstone 16 650-1200
12 Shale 3 10
3 13-17 Sandstone 17 550-3000
18 Shale 3 10
4 19-25 Sandstone 17 150-4000
26 Shale 3 10
5 27-31 Sandstone 14 2000-4000
In the model, two fractures were induced in the year 1995, that
is three years after the initiation of the water injection, the
induced fractures are in the flow unit 4, layers 22 and 24,
propagating radially reaching 30 feet radius (Figure 5). The
induced fractures permeability is estimated 20,000 mD.
Gel Chemical Parameters in the Model
Rheology data from laboratory for the gel used in this study
was used to model the pore blocking and adsorption effects on
the aqueous phase relative permeability.

4. 4 SPE 92003
Gel Adsorption The adsorption of the gel system was
measured by static adsorption experiments on Berea
sandstone. The polymer adsorption is considered as the gel
adsorption because the organic crosslinkers: phenol and
formaldehyde did not show adsorption in the experiments.
From the static adsorption experiments, the maximum
adsorption was determined and results were fitted to a
Langmuir Isotherm form (Figure 6). The maximum polymer
adsorption adjusted to a Langmuir Isotherm reached a plateau
of 0,06 gPolymer/gBerea, and the adsorption slope constant
calculated with a value of 45.49 7
.
The Polymer and Rock properties included in the model are as
follows:
Dead pore 0.06
Adsorption Index: 1
Maximum Polymer Adsorption: 0.06
In the model it is assumed that 100% of the injected polymer
is adsorbed on the rock. For example, for a Polymer
concentration of 1 lb/stb, 1 lb of Polymer is adsorbed on the
rock.
The shear viscosity of the gel is 4 cP at 90 °C and the
deformation rate is 1 s-1
.
Run Description
The initial volumes calculated in the model are shown in
Table 3:
Table 3 Initial Volumes in the Prototype Model
Oil (Barrels) Water (Barrels) GIIP (MSCF)
7,060,622 785,950 6,745,284
In the model, a gel treatment was performed in the injector
well located down dip about 330 meters from the producer
well. The treatment was performed by injecting a gel in
aqueous phase composed by polyacrylamide and phenol-
formaldehyde, in a 171 feet thickness interval at 14,585 feet
depth, identified as preferential water injection sand in PLT
logs.
The model was run in natural depletion (base case) from 1992,
until an average reservoir pressure of 6,500 psia was reached
(Figure 7).
Thereafter water injection was started at a balanced rate to
maintain approximately 6,500 psia average that is the average
operating pressure of North Monagas reservoirs that are
produced under water injection secondary recovery (Figure 8).
In the model, a decline in oil rate is observed in the year 1993
at water breakthrough time in the producer well.
A first water injection case was simulated that showed a 93 %
water cut by the year 2000 (Figure 9).
A second case considering a gel treatment in the water injector
well with induced fractures was simulated; injecting 5,000
barrels of gel in the injector well in the year 1996 when the
water cut in the producer well was 75 %. The gel treatment
was targeted to seal interpreted induced fractures identified in
PLT logs that were possibly generated by thermal differences
as a result of cold water injection (Figures 10 & 11). Injection
rates were 1,000 barrels a day of aqueous polymer solution of
1 lb/stb concentration for 5 days.
The effect of the induced fractures was investigated; obtaining
results that indicates that under the fractures characterisation
that were modelled with the available information, the effect
in the final recovery is negligible.
Results
The results obtained in the model show that the gel treatment
in the water injector well, performed in November 1996 with
5,000 barrels of gel improves the sweep efficiency generating
an increase in the oil rate of 837 barrels per day (Figure 7).
The sweep efficiency is improved as a result of a more
uniform water injection profile.
The incremental cumulative produced oil observed for the
case of water injection and gel treatment in the injector well, is
118,617 barrels in 1.5 years time compared with the case of
water injection without gel treatment (Figure 12). The
recovery factor increases 1.6 % (Table 4). The effect of the
gel treatment in reducing the produced water can be seen in
Figure 13.
In the model the reservoir pressure is maintained constant at
6,500 psi, the bottom hole pressures at the injector and
producer wells are shown in Figures 14 and 15.
Table 4 Simulation Results Oil Rates and Incremental Oil
Oil Rate
(Barrels/Day)
Treated
Well
Injected
Gel
Volume
(Barrels)
Before
Gel
After
Gel
Cumulative
Produced Oil
(Barrels)
Incremental
R. F.
(%)
- - 837 - 4,185,400 -
Injector 5,000 837 1,412 4,314,017 1.68
Incremental Production 118,617
The gel treatment with 5,000 barrels of gel improves the water
injection profile, and the water cut is reduced from 85% to 30-
35 % as shown in Table 5. In the Figures 16 & 17 the
differences in sweep efficiency for the cases of water injection
and water injection followed by a gel treatment can be
observed.
Table 5 Simulation Results Water Cuts
Water Cut (%)
Treated Well Injected Gel in the
Treatment (Barrels) Before After
Injector 5,000 82 65
The average permeability reduction factor predicted in the
model is equal to 20 in the near wellbore zone with 30 feet
penetration. This value is similar to the results obtained from
core laboratory test injecting the gel formulation used in this
study8
. The polymer production rate plot (Figure 18) indicates
an instantaneous rate in the producer well indicating that most
of the injected polymer remains adsorbed onto the rock.

5. SPE 92003 5
Sensitivity Treated Wells. In addition to the base case of
treatment with 5,000 barrels of gel in the injector well,
sensitivities with gel treatments in the producer well, and gel
treatments in the injector and in the producer wells were also
perfomed. The case of treatment in the injector well showed
118,617 barrels of incremental production. The case of gel
treatment in the producer well showed an incremental
production of 145,291 barrels. And the best performance was
obtained for the treatment in the injector well followed by a
treatment in the producer well that showed an incremental
cumulative production of 227,485 barrels of oil (table 6).
Table 6 Well Treatment Sensitivities Incremental Oil
Rates
Oil Rate
(Barrels/Day)
Treated
Well (s)
Gel
Treatment
(Bbls) Before
Treatm.
After Treat.
Incremental
Oil (Barrels)
Incremental
R. F. (%)
- - 837 - -
Inj. 5,000 837 1,400 118,617 1.68
Prod. 5,000 837 1,800 145,291 2.06
Inj. &
Prod.
10,000 837 2,500 227,485 3.22
The water cut performance shows that the treatment in the
injector and in the producer wells cause a stronger reduction
effect compared to the gel treatment in the injector or in the
producer well (Table 7).
Table 7 Well Treatment Sensitivities Water Cuts
Water Cut (%)
Treated Well Injected Gel in the
Treatment (Barrels) Before After
Injector 5,000 82 65
Producer 5,000 82 60
Injector and
Producer
10,000 82 40
Sensitivity Date of Gel treatment. Three sensitivities were
performed to evaluate the timing of gel treatment, considering
gel treatments in both wells: injector and producer. The dates
were selected for water cuts of 85 %, 90% and 93 %.
The results obtained show that the sooner the treatment is
done i.e., when the water cut is low the treatment effectiveness
improves (Figures 19, 20 & 21). However, when the treatment
is done at 93 % water cut the models predicts 153,000 barrels
of incremental production as can be seen in table 8.
Table 8 Sensitivity Dates of Treatment
Date of the
Gel
Treatment
Water Cut
(%)
Incremental Produced
Oil in 3 Years (Barrels)
Incremental
R. F. (%)
End 1996 80 225,000 3.0
End 1997 85 196,000 2.6
End 1998 90 177,000 2.4
End 1999 93 153,000 2.0
Future Work
Future planned work considers continuation of gel modeling
investigations of gel treatments in black oil and compositional
models using conceptual and complex full field models for
application in HPHT and conventional reservoirs. The
development of simple predictive models in various
commercial simulators for gel treatment modeling in injector
and producer wells.
Conclusions
1. A prototype model was built for HPHT reservoirs using
the ECLIPSE Black Oil Polymer option, to model gel
treatments to block preferential water movement channels
in water injector wells with interpreted induced fractures.
2. The prototype model predicts the residual resistant factor
to water after the gel injection in the treated intervals with
reasonable accuracy in the order of 20 in a fractured water
injector well. This value matches reasonably well with
laboratory measurements4
.
3. For the reservoir characteristics used in this study, the gel
treatments in the injector and producer wells predicted
increases in the recovery factor from 1.68 to 3.2% and
incremental productions from 118,617 to 227, 485 barrels
in 3 years of forecast after the treatment.
4. The prototype model predicts lower incremental
production for gel treatment at higher water cut. In this
study, the treatment performed by end of the year 2000 at
93 % water cut predicts 153,000 barrels of incremental
oil, which is 72,000 barrels less than that of the treatment
in the year 1996.
5. The results from the simulation suggest that induced
fractures in sandstones, as they were modeled with the
available information, are not sensitive to the recovery
after the gel treatment.
6. The black oil formulation to model gel treatments is an
instantaneous gel settling model where exact chemical
reactions can not be represented, resulting in limitations
to include the gel kinetics to model the gelation time.
7. A black oil simulation model is a useful tool to design gel
treatments and to develop data for economics evaluations
to optimize its design.
Acknowledgments
We thank Schlumberger Information Solutions in Venezuela,
for its permission to perform this study in ECLIPSE reservoir
simulator and for its support in the development and
presentation of this paper.
References
1. J, Herbas et al. “Reservoir Engineering Studies to Implement
Additional Recovery Projects in El Furrial Field”, (March 1992)
SPE 23685.
2. Schlumberger Surenco (Diciembre 1997) Venezuela WEC
“Evaluación de Pozos” Caracas, C.A.
3. W. Obrien, J. Jay, R. Lane. “Mechanistic Reservoir Modeling
Improves Fissure Treatment Gel Design in Horizontal Injector,
Idd El Shargi North Dome Field Qatar” SPE 56743

6. 6 SPE 92003
4. J. Herbas, R. Moreno, M.F. Romero, D. Coombe & A. Serna.
“Gel Performance Simulations and Laboratory/Field Studies to
Design Water Conformance Treatments in Eastern Venezuelan
HPHT Reservoirs” SPE 89398
5. ECLIPSE Technical Description and Reference Manual
Schlumberger.
6. M. Todd, E. Claridge C. Chase J. Herbas, P. Marquez, M.
Mendes (December 1992) “Preliminary Investigation of
Enhanced Oil Recovery in El Furrial Reservoir”, TCA Reservoir
Engineering Services, Lagoven S.A.
7. Romero M.F. “Estudio Cinético y Adsorción de Geles
Poliméricos para el Control de Agua y Gas durante la
Producción de Petróleo”, (Junio 2002), Universidad Central de
Venezuela.
8. Gamboa M. “Evaluación de un Sistema Gelificante Polimérico
de Baja Densidad a 90° C en un Núcleo de Alta Permeabilidad “
(2002) Universidad Central de Venezuela.
Symbols and Units:
δG’/ δt: speed of change
δυ/ δt: rate of change of crosslinking density
q: a constant with values between 0,4 and 1,0
R: universal gas constant,
T: absolute temperature
Gen: contribution of increased storage modulus due to the
temporary entanglements of diluted solutions.
Sdpv : dead pore volume
Ca: adsorption isotherm a function of local polymer
concentration
Ca max: maximum adsorbed concentration
ρr : mass density of the rock formation
φ: porosity
ρw : water density
∑ : sum of neighbouring wells
RK: relative permeability reduction factor for the aqueous
phase due to polymer retention
Cp Cn: local concentration of polymer and sodium chloride in
the aqueous phase
µeff : effective viscosity of the water, polymer and salt
components
R.F.: Recovery factor %
RRF: Residual Resistance Factor
Dz : cell centre depth
Figure 1 Production Performance North Monagas HPHT Well
WATER INJECTOR
WELL
PRODUCER WELL
’
Figure 2 North Monagas Conceptual Reservoir Structure
Figure 3 Areal Grid 3D Prototype Model

7. SPE 92003 7
Figure 4 Vertical Permeability 3D Model
Figure 5 Permeability in the Induced Fractures
Figure 6 Adsorption Isotherm Polymer Berea System
Figure 7 Oil Rates Before and After Gel Treatment
Figure 8 Reservoir Pressure
Figure 9 Water Rates Before and After Gel Treatment

8. 8 SPE 92003
Figure 10 Near Wellbore Permeability Reduction
Figure 11 Zoom Near Wellbore Permeability Reduction
Figure 12 Effects of Gel Treatment Cumulative Produced Oil
Figure 13 Water Production Rates
Figure 14 Producer Well Bottom Hole Pressure
Figure 15 Water Injector Well Bottom Hole Pressure

9. SPE 92003 9
Figure 16 Water Saturation at breakthrough time 3D Before Gel
Treatment
Figure 17 Water Saturation at breakthrough time After Gel
Treatment
Figure 18 Polymer Production Rate
Figure 19 Sensitivities Dates of Treatment - Oil Rates
Figure 20 Sensitivities Date of Treatment - Cumulative Oil
Figure 21 Sensitivities Date of Treatment - Water Cuts