utchem chtterau example
TRANSCRIPT
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Society
of
PetroleumEngineers
SPE 24931
Simulation of a Successful Polymer Flood in the Chateaurenard Field
Sunao Takaqi, G.A. Pope* and Kamy Sepehrnoori,*
U.
of Texas; A.G. Putz,* Elf Aquitaine;
and Hichem BenDakhlia,*
U
of Texas
SPE Members
Copyright 1992 , Society of Petroleu m Engineers Inc.
This pape r was prepared for p resentation at the 67th Annual Techn ical Conferenc e and Exh ibition of the Society of Petroleum Engineers held in Washington,
DC
October 4-7, 1992.
This paper was selecte d for pres entation by an SP E Program Comm ittee following review of information containe d in an abstract submitted by the author@ ). Contents
of
the paper,
as prese nted, have not been reviewed by the Society of Petroleum Enginee rs and are subject to correction by the author(@ . The mater ial, as presente d, does not necessarily reflect
any position of the Society of P etmleum Enginee rs, its officers, or me mbe rs. Papers presented at SPE meetings are subject to publication review by Editorial Committees of the Society
of Petmleum Engineers. Permission o copy is restricted to an abstract of not more than 3 00 word . Illustrations may not be copied. The abs tract should contain conspicuous acknowledgment
of where and by whom the paper is presented. Write Librarian, SPE, P.O. Box
833836
ichardson.
TX
750834 836 U.S.A. Telex, 730989 SPEDAL.
BSTR CT
Early results of a successful polymer project started in
1985 in the Courtenay sand of the Chateaurenard field located
south of Paris, France, were presented at the fall 1988 SPE
meeting. We update these data and show that subsequent
performance has confirmed the highly favorable oil recovery
behavior of this project. The objective of this paper is
to
report
the results of a detailed compositional simulation study
conducted to understand this favorable result. Both alternative
reservoir and process characteristics were investigated in these
three-dimensional simulations. n particular, both a classical
layered reservoir description and a geostatistical reservoir
description were investigated. The latter represents a new
approach to the interpretation of polymer flooding and played an
important role in our study since the attenuation of reservoir
heterogeneities is known to be an important attribute of polymer
flooding. We also evaluated the importance of permeability
reduction and adsorption of the polymer on process performance.
After obtaining a good match of the production of oil, water and
polymer, we then investigated the importance of design factors
on the oil recovery performance. The actual polymer flood
consisted of injecting a large polymer slug followed by five
smaller slugs of decreasing polymer concentration
to
decrease the
time that a study of this type with an accurate compositional
simulator has been reported for polymer flooding. The
combition of better reservoir characterization methodology and
accurate process simulation of polymer flooding should aid in the
successful exploitation of this technology in the future.
This
project clearly shows the high potential of polymer flooding
under the appropriate reservoir conditions and with good design
and implementation methods.
INTRODU TION
polymer flood pilot test1 in the Courtenay sand of
the Chateaurenard field was started in 1985. This pilot test is
characterized by high oil recovery
1.5
bbl oil per lbm polymer)
and high retention of polymer in the reservoir. The performance
of this pilot was simulated using a compositional chemical
simulator called UTCHEM developed at The University of
exa as Actual field
data
and available physical property data
were used as much as possible to evaluate simulation input
parameters. UTCHEM is a three-dimensional, compositional,
multicomponent, multiphase, finite-difference simulator.
third-order correct in space finite-difference method3 with a flux
lirnitefi is used to approximate the partial differential equations.
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2
SIMUL TION OF SUCCESSFUL POLYMER FLOOD INT HE CH TE UREN RD FIELD
SPE
24931
Geology and Reservoir Characteristics
The Chateaurenard field is located 100 km south of
Paris, France, and is divided into three main structures: Saint-
Firmin, Chuelles, and Courtenay. There have been several
polymer and microemulsion pilots and a commercial-scale
polymer flood conducted by Elf Aquitaine in the Chateaurenard
field.lv6-l2
Elf Aquitaine started a polymer pilot in the Courtenay
reservoir sand of the Chateaurenard field on October 1, 1985.
The sand was deposited on an already pre-existing structure of
channels and basins, which explains rapid pay thickness changes
even though the top of the formation is essentially flat.
Vertically this structure consists of three unconsolidated sand
layers. The lower layer is the polymer flood pilot target. The
reservoir thickness varies between 0 and 7 meters with an average
of 3.2 m. The structure of the Courtenay is a monocline with a
low dip of 2 to the northwest. In the southeast direction, the
structure is terminated by fingered stratigraphic traps with the
reservoir becoming increasingly shaly. In the northwest
direction, the oil zone is limited by a very large aquifer. This
reservoir is an unconsolidated sand with a small percentage of
clay (2 to 15 ), mainly composed of kaolinite. The porosity
is nearly uniform and about 30 . The field permeability varies
from 800 to 3,000 md and the mean value is estimated to be
1,600 md in the pilot area.
The original oil in place was 11.7 million m3 (73.6
million bbl) in the Chateaurenard field of which 1.3 million m3
(8.2 million bbl) is in the Courtenay sand. The pore volume and
original oil in place inside the five-spot used in the Courtenay
polymer pilot were estimated to be 44,444 m3 (280,000 bbl) and
27,555 m3 (173,000 bbl), respectively. A summary of original
oil in place and pore volume of each area is given in Table 1.
The oil viscosity is 40 cp at 3 0 ' ~ reservoir temperature) and the
oil density is 0.89 (~~'API) .The wells do not produce free gas.
The formation water is fresh with a total dissolved solids content
of about 0.4 glliter. The water viscosity is 0.73 cp at reservoir
temperature.
Production History
The Chateaurenard field was put into production in
1960. By December 1987, the cumulative production was 3.8
million m3 (23.9 million bbl). The total cumulative production
from the Courtenay reservoir was 0.389 million m3 (2.5 million
bbl). Well CY30 had been producing for five years with a total
production of 25,000 m3 (157,000 bbl), and wells CY40, CY41,
and CY42 had been producing for three years with a production
of about 11,000 m3 (69,000 bbl) for each well before the
polymer project.
well (CY543) was drilled for polymer injection in 1984. The
well pattern is shown in Fig. la.
The injected polymer was a partially hydrolyzed
polyacrylamide. The pilot operation consisted of successive
injections of a slug of 1,000 ppm polymer concentration,
followed by a tapered concentration as shown in Table 2. After
the final slug of 200 ppm polymer solution was injected, chase
water was injected. The total volume of polymer solution
injected was 47,200 m3 (297,000 bbl), which is 1.06 times the
pore volume of the five-spot, and the total amount of polymer
injected was 37.3 metric tons (82,300 lbm). The four producing
wells were kept at about the same producing rate and the total
production rate from the wells has been almost the same as the
injection rate.
Pilot Performance
The polymer solution injection started on October 1,
1985, and the injection rate was increased from the level of 50
m3/d (314 BID) until it reached 100 m3/d (629
BID
at the
beginning of 1987 after which it was kept nearly constant. Both
injection and production volumes in this paper refer to standard
conditions.
A distinctive characteristic of the injection well was that
the wellhead pressure of 18 bars (260 psia), which corresponds to
about 1,100 psia bottomhole pressure, did not increase even
when the injection rate increased or when the injection viscosity
was suddenly increased. This indicates that the injector was
operating above the parting pressure of the sand at least part of
the time. The very good injectivity of polymer is one of the
most favorable characteristics of this successful polymer pilot.
Putz
et
a1.l reported that 18,300 m3 (115,000 bbl) of
oil were produced from the Courtenay sand reservoir by 1987.
The average field oil cut was then 16.6 , with 38 for the
polymer pilot and 11 for the other wells. By June 1989, the
cumulative oil production from the pilot was 26,013 m3
(164,000 bbl), (about 94 of the initial oil in place inside the
five-spot; see Table 1) and the produced polymer was only 0.3
tons. Corlay t a1.13 estimated that the additional oil recovered
in the polymer pilot was 19,000 m3 (120,000 bbl), which is
about 1.5 bbl oil per Ibm of polymer, a very favorable result.
Figure 2 shows the total oil production rate from the
four producers in the pilot area after starting the polymer
injection. After the start of polymer injection, the oil cut of the
producing wells remained unchanged for 250 days, after which
two wells encountered a sharp increase in oil cut. For well
CY30, the oil cut increased from 18 to a maximum of 61 at
500 days (Fig. 3). For well CY42, the oil cut increased from
19 to a maximum of 50 at 450 days (Fig. 4). Well CY41
experienced the arrival of the oil bank a little later, with an oil
cut increase from 12 to 37 (Fig. 5). Only a weak response
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SPE 24931
S.TAKAGI H. BENDAKHLIA G.A. POPE,A. PUTZ
ND K.
SEPEHKNOORI
3
arrival of tertiary oil banks in five wells and a high concentration
of polymer in one well have been observed.
S I M U L A T I O N
A complete description of the simulation input as well
as the polymer models used for each polymer property are given
in ~ a k a ~ i . l ~summary of the most important simulation
input parameters is given below.
Stat is t ical ly Dis tributed Permeabil i ty Field
Heterogeneous permeability fields were generated by the
method of moving averages or Matrix Decomposition Method
(MDM) using a spherical variogram and a log-normal
permeability distribution.15*16 A common measure of
permeability variation is the Dykstra-Parsons coefficient (VD~).
If the permeability distribution is log-normal, the Dykstra-
Parsons coefficient is described as
where k50 is the median permeability, kg4.l is the permeability
one standard deviation below k50 on a log-permeability plot, and
o nk is the standard deviation of log permeability.
A correlation length scale, h is the parameter used to
express spatial correlation. The degree of correlation between the
permeabilities at two points decreases as the distance between
them increases. The correlation length scale was normalized by
the length of the side of the simulated area (500 m or 1,640.5 ft).
For the base case, I 1,549 md, V D ~ 0.221, ~ D X
h ~ y1.0, and DZ 0.33. These parameters represent
relatively low permeability variations, a strong correlation in the
horizontal direction, and a low correlation in the vertical
direction. A verticaVhorizonta1 permeability ratio (kv /k~)f 1.0
was used throughout this study. The permeability field generated
by MDM for the 15x15~3rid is shown in Figs. 7 through 9.
Unfortunately, these parameters had to be inferred from history
matching rather than from core data or other measured reservoir
data since these were not available on this sand.
Injection Rate
The four producing wells were constrained by a constant
pressure of 100 psia, the same pressure as the initial reservoir
pressure. The total injection volume of this pilot was about 6
more than the total production volume from the four wells, so
the injection rate was made the same rate as the total producing
rate (Table
3 .
As a result, the total volume of polymer
solution injected was 44,524 m3 (280,000 bbl), which was
paper by Putz t a1.l with the calculated viscosity is shown in
Fig. 10. The parameters that determine the effect of shear rate on
polymer viscosity were obtained from data on partially
hydrolyzed polyacrylamide.17 The polymer viscosity at the
injected polymer concentration of 1000 ppm and 90 s-l is about
20 cp. This gives a mobility ratio between the initial polymer
slug and the oil bank of about 0.4.
For modeling the polymer adsorption in the simulator,
the salinity dependency was neglected since the salinity in the
reservoir is essentially constant. The adsorption isotherm for
both the base case and the final simulation are shown in
Fig. 11.
The permeability reduction was reported by Putz l a1.l
as 1.3. However, in order to simulate the high oil cut of the
producing wells, higher permeability reduction Rk than this
value had to be used. Figure 12 shows the calculated Rk as a
function of polymer concentration and permeability for the two
assumed cases that we simulated. In the final simulation, the
maximum gridblock permeability reduction was 9.182. The
reason why higher values are needed to match the field behavior
of this pilot is not known. Low values of permeability on a
small scale is one possible explanation for these higher values.
A value of 0.15 was used for inaccessible pore volume
in all simulation runs. Longitudinal and transverse dispersivities
were 1.0 and 0.0 ft, respectively.
The oil relative permeability was based on the data by
Putz
t
a1.l However, the water relative permeability was
modified by changing the endpoint relative permeability to water
and the residual oil saturation. The original values were 5.8
and 27 , respectively, and the modified values were both 20 .
Recent experimental research18 has revealed the fact that the
residual oil saturation to polymer (Sorp) in heterogeneous cores
is often about 6 lower than that to water (So,,) even when the
capillary number for each coreflood is kept precisely the same.
This is consistent with the residual oil saturation to polymer of
20 being lower than that to water of 27 needed to match this
field pilot data. We consider this to be one of the most
interesting and significant observations about this pilot study.
When large amounts of highly viscous polymer are injected into
heterogeneous rock containing oil above residual oil saturation,
both laboratory and field data support the conclusion that the
residual oil saturation in the swept zone will be lower to
polymer than to water, so polymer flooding has the potential in
some favorable circumstances of not only improving sweep
efficiency and accelerating oil recovery, but also of reducing the
ultimate oil saturation locally.
For the simulated area of 1,640.5 ft x 1,640.5 ft shown
in Fig. lb, a 15 x 15 grid with AX AY 109.367 ft was used.
For the three vertical layers used for the base case, A was equal
to 3.60858 ft. For the final match to the field data, variable
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SIMULATION OF A SUCCESSFUL
OLYMERFLOO N
THE
CH TE UREN RD
FELD
SPE 24931
oil in place inside the five-spot was produced. The slope of the
recovery w e ecame steeper aftcr 500 days because the oil bank
formed by the polymer started to break through to the producing
wells. To determine the effect of mesh refinement on the base
case, one run with a 25 25 3 areal mesh refinement was
made. The effect of this mesh refinement on the oil recovery
efficiency is shown in Fig. 13. The areal mesh refinement
resulted
in
a change of only 2.3 in the oil recovery. A vertical
mesh refinement was done for the final field simulation shown
later and resulted
in
even less change in oil recovery.
Sensitivity of Oil Recovery to Adsorption
The adsorption isotherm with one-half the maximum
adsorption plateau of the base case (Fig. 11) was used for
comparison with the base case. As shown in Fig. 14, the oil
recovery for this Run PF2 increased 9 . The adsorption of
polymer in mass units was 105 pglg. This level of adsorption
resulted in 83.3 retention of the injected polymer for Run PF2,
while for the base case Run PFO, with an adsorption of 118
pgjg, 93.7 of injected polymer was retained. These retention
values are based upon the pore volume inside the five-spot
pattern. The actual local adsorption in any given gridblock
varies but is lower. The lower adsorption of Run PF2 resulted
in higher simulated polymer concentrations and earlier polymer
breakthrough times as would be expected. Detailed analysis of
s
nd other results can be found
in
Takagi's thesis.14
Sensitivity of Oil Recovery to Permeability
Reduction
The permeability reduction of the polymer was reduced
from the base values as shown in Fig. 12. A comparison of the
oil recovery for this Run PF3 with that of Run PFO is shown in
Fig. 15. The oil recovery is about 9 less than that of Run
PFO. Each well had a higher simulated polymer concentration.
The maximum permeability reduction in any gridblock was 10.8
for the base case but only 3.0 for Run PM. As expected, lower
permeability reduction resulted in lower oil cut and lower oil
recovery.
Sensitivity of Oil Recovery to the Dykstra-Parsons
Coefficient V D ~ )
A
VDP value of 0.5695 was used for the case of higher
heterogeneity (Run PF4)
th n
the base case (Run PFO; V D ~
0.221). A comparison of the cumulative oil recovery for Run
PF4 with that for Run PFO is shown in Fig. 16. The oil
recovery for Run PF4 is about 3 more than that for Run PFO.
This result indicates that the higher heterogeneity (VD~)han the
base case causes higher oil recovery, which was not expected.
Recall that the vertical and horizontal permeabilities are equal,
which is favorable for crossflow. The gravity number Ng)or
regions free of polymer is about 0.006 based upon an aqueous
viscosity of 0.73 and for regions with 1000 ppm of polymer is
about 0.0003 based upon 20 cp aqueous viscosity. The effective
This would not happen in most cases. Tables and contour plots
showing precisely how and where this happened in this
realization are given in Takagi's thesis.14
Comparison Between Layered and Stochastic
Permeability Distribution
Next, a simulation was made using a reservoir
description consisting of three permeability layers with 400 md
on top, 4000 md in the middle layer and 400 md on the bottom.
A comparison of the oil cumulative recovery for this Run PF5
with that for Run PFO is shown in Fig. 17. The oil recovery for
Run PF5 is about 5 more th n that for Run PFO. However,
as shown in Takagi, the agreement with the water cuts and
polymer production data from individual wells was not as good
as for the final field case using a statistically generated
permeability field as shown next and there is no easy mechanism
for systematically assessing the uncertainty of the result as there
is for the stochastic case.
Simulated (Run PF6) and field oil production are shown
in Figs. 2-6 and 18, and comparisons of the simulated water cuts
and aqueous phase polymer concentrations with the field data for
each producing well are shown in Figs. 19 through 22. For the
base realization, the field oil recovery at 1,369 days after start of
polymer injection was 94.4 of the initial oil in place inside the
five-spot (26,013 m3 or 163,600 bbl).
The simulated oil
recovery at 1,369 days was 90.3 of the initial oil in place
inside the five-spot (24,923 m3 or 156,600 bbl).
Increasing the number of vertical gridblocks from three
to six made almost no difference in these results. We also show
on
each of these figures another realization created by simply
changing the seed for the random number generator. Again, there
is little difference between this realization and the one labelled
base realization that was used to generate all of the results shown
in this paper. We did many more realizations with similar
results. This reflects the insensitivity of the results to small
changes in heterogeneity. The results of this fhal case differ
from the base case because log based variable sand thicknesses
were used rather than a uniform average thickness.
The simulated and field polymer breakthrough times are
very close. The simulated maximum polymer concentrations in
wells CY30 and CY40 are close to the field values, whereas the
simulated
peak
polymer concentrations for well CY42 and CY41
are about 70 ppm too high. The simulated retained polymer was
120 pg/g rock, or 95.0 of the injected polymer compared to
99.2 field retention. Retention of polymer in pg/g rock is
based on the rock volume inside the five-spot pattern. Local
adsorption values vary but are lower than this average based upon
the five-spot volume, which is used merely for a convenient
reference. The maximum adsorption for any gridblock was about
36 pgtg. This amount of adsorption is about the same as the
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SPE
24931
S.TAKAGI.H. BENDAKHLIG
G A
POPE.A PUTZ
AND K
EPEHRNOORI
of simulated water cuts to the field data. Thus, a comprom ise is
required to simultaneously achieve a good agreement match of
both water cut and polymer production.
Field water cuts in well CY30 (Fig. 19) show a
stronger oil bank than the simulated water cuts. A comparison
of the simulated and field water cuts in well CY42 (Fig. 20)
shows good agreem ent in the first 800 days, but the simulated
water cuts are too high after 800 days.
A comparison of the
simulated and field water cuts in well CY41 (Fig. 21) show s that
the simulated water cuts are too high except for the time period
from
4
to 800 days. A comparison of the simulated and field
water cuts in well CY40 (Fig. 22) shows good agreement most
of the time.
Polymer concentration grading is a strategy for
decreasing fingering of the chase water through the polymer slug.
The
effect of graded polymer flooding was studied by comparing
its results with those of a single-slug polymer flood of
1,000 ppm polymer co ncentration. The single-slug polymer
flood case was simulated with the same amount of polymer as
the graded polymer case. The simulated area, the grid, the well
pattern, and all other parameters were the sam e as for the base
case.
There was essentially no difference between the
simulations for the base case (graded) and the ungraded
simulation, so the results are not plotted here but c nbe found in
Takagi, who also shows other simulations to study grading and
fingering. This may seem like a surprising result given the high
mobility ratio between injected polymer solution and chase water
and thus the tendency for viscous fingering. However, detailed
simulation studies of the unstable dis lacement of polymer
solutions by water made by KruegerlBand ~ U ~ Os well as
Takagi s results including some a t higher mobility ra tios and
using finer grids have shown that decreasing polymer
concentration gradually (polymer grading) often makes very little
difference in oil recovery for a given total amount of injected
polymer. Although space does not allow us to discuss these
results in detail, the general nature of the result can be
summarized as follows. Other factors may be so dominant that
fingering has little effect. In the case of the Courtenay sand
polymer flood, the dominant facto r was polymer adsorption. A
secondary factor was heterogeneity. Large directional variations
in
permeability caused the chase water to channel rather than
finger.
Several papers21-23 have recently addressed the
conditions under which channeling, fingering, or gravity
segregation tends to be the dominant flow mechanism in
miscible displaceme nts at unfavorable mobility ratios. High
heterogeneity, especially high correlation length, tends to
promo te channeling as opposed to fingering. Also, the very
high value of RL of 50 tends to suppress fingers and promote
cases, the dominant polymer design factors are likely to be the
total amount of polymer and its initial concentration rather than
grading. High concentrations and large amounts of polymer as
used in this Courtenay pilot have been found to be the best
approach to polymer flooding in the field cas es that Krueger and
Liu have studied to date.
ON LUSIONS
Good agreement was obtained between the simulated and
field performance of the Courtenay polymer pilot in the
Chateaurenard field using a statistically generated permeability
field. Better agreement with the field
data
and better ins ight into
the behavior of the pilot was obtained using this approach rather
than a reservoir description consisting of uniform layers. More
information from logs, cores, tracers or other sources would have
been very desirable to use in conditioning these stochastic
permeability fields, but even in the absence of conditioning some
insight into the uncertainty and importance of the reservoir
heterogeneity was obtained by a combination of sensitivity
studies and multiple realizations. Both areal and vertical mesh
refinement indicated that these simulation results were
numerically accurate since the oil recovery changed very little as
the gridblock sizes decreased . Sensitivity studies showed that
this polymer pilot was dominated by polymer adsorp tion. The
oil recovery was surprisingly insensitive to change in the
permeability distribution (heterogeneity as measured by the
Dykstra-Parsons coefficient). Reduction of residual oil saturation
by the polymer to values below that expected of water may have
contributed to the good oil recovery in this pilot.
Although the actual polymerflood pilot used a large,
graded polymer injection scheme, comparisons w ith simulated
resu lts for a single , large polymer slug with the same total mass
of polymer indica ted that grading made very little diffe rence in
this pilot, i.e., finge ring was not important. This result can be
explained in terms of the dominant importance of polymer
adsorption and fractional flow effects and to a lesser extent the
effects of heterogeneity with large correlation length and large
effective length to thickness ratio that promotes channeling
rather than fingering. The exc ellent oil recovery of this pilot
(1.5 bbl of incremental oil per lbm of polymer) was a result of
using a large amount of polymer, favora ble reservoir conditions
and good des ign and implementation of this technology.
NOMENCLATURE
kH
Horizontal permeabiiity (md)
k = Vertical permeability (md)
=
Endpoint relative permeability to aqueous
phase
0
Ng = kxAp H Gravity
Number
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STMUL TIONOF
A
SUCCESSFULPOLYMER FLOO NTHECH TE UREN RD
FIELD
SPE
2493
Greek
Symbols
L
correlation length scale (ft)
p
Viscosity of aqueous phase
Porosity (fraction)
ACKNOWLEDGMENTS
We thank Ph. Corlay, Ph. DeLapace, J. Lecourtier, and
1. P~ersonfrom IFP for their contribution to the paper.
Financial support from the U.S. Department of Energy and the
participating companies of the Enhanced Oil and Gas Recovery
Research Program of the Center for Petroleum and Geosystems
Engineering at The University of Texas at Austin is gratefully
acknowledged. Computing resources for this work were provided
by
The University of Texas Center for High Performance
Computing. Sunao Takagi would like to thank Japan China Oil
Development Co. (JCODC) and Japan National Oil Co. JNOC)
for the financial support during this study.
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A.
G.A. Pope, K. Sepehmoori, and R.L.
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20-22, 1991.
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Saturation, M.S. thesis, The U. of Texas, Austin (1989).
Krueger, C.:
Viscous Fingering, M.S. thesis, The U. of
Texas, Austin (1989).
Liu, J.: Ph.D. dissertation (in progress), The U. of Texas,
Austin (1992).
Chang, Y.B., M.T. Lim, G.A. Pope, and K. Sepehrnoori:
Carbon Dioxide Flaw Patterns Under Multiphase Flow,
Heterogeneous Field Scale Conditions, paper SPE 22654
presented at the 66th Annual Technical Conference and
Exhibition of the Society of Petroleum Engineers, Dallas,
TX, Oct. 6-9, 1991.
Ringrose, P.S., K.S. Sorbie, F. Feghi, G.E. Pickup, and
J.L. Jensen: Relevant Reservoir Characterisation:
Recovery Process, Geometry and Scale, paper presented at
the 6th European IOR-Symposium, Stavanger, Norway,
May 21-23, 1991.
Waggoner, J.R., J.L. Castillo, and L.W. Lake:
Simulation of EOR Processes in Stochastically Generated
Permeable Media, paper SPE 21237 presented at the SPE
1 th Symposium on Reservoir Simulation, Anaheim, CA,
Feb. 17-20, 1991.
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Table 1. Pore Volume, OOIP and Cu mulative Oil Production
f December 1987
as of June 1989
Table 2. Injection Scheme of Polymer Solution in the Chateaurenard Polymer Pilo t
Table 3.
Injection Schedule of Polymer and Chase Water used in Simulations
Date started Time, t t
Injection Rate Concentration
Volume Polymer
mo/day/yr)
days)
days) B P I
[m3/dl
PPm)
@b l) [m31 Quantity
tons)
10/01/85 273 273 252 [40]
334 [531
408 [64.8]
230 [36.6] 1,000
555 [88.21 800
622 98.91 625
586 [93.1] 500
537 B5.41 400
531 [84.3] 200
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Figure 1A Isopach map of the Courtenay field
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0 200 400 600 800 1000 1200 1400 1600
Time
Days)
Figure 2. Com parison of the total oil production rate for the final simulatio n
PF 6) with the field data.
ield data
Base realization 15 x1 5~ 3)
*
Realization 3
200 400 600 800 1000 I200 1400 1600
Time
Days)
Figu re 4. Com parison of the oil production rate of well CY4 2
for the final simulation PF6 ) with the field data.
Time Days)
Figure 3 Co mp arison of the oil production rate of well CY3 0
for the final simulation PF6 ) with the field data.
Time
Days)
Figure 5 Com parison of the oil production rate of well CY41
for the final simulation PF 6) with the field data.
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I l l l t l l l l l [ l l l { l l l l l r a l l l l r
ield data
Base rea li zat ion 15 x1 5~ 3)
Mesh refinement 15 x15 ~6 1
Realization 3
Figure 6. Comparison of the oil production rate of well CY40
for the final simulation PF 6) with the field data.
x direction
1 7
4
5
8
9
I 0 1 1 1 2 1 3 1 4 1 5
x
direction
1 2
4
5
6 7 8
9 1 0 1 1 1 2 1 3 1 4 1 5
Figure 7. Permeability contour map for the top layer 1 5x 1 5~ 3) .
Figure
8
Permeability contour map for the middle layer 15 x1 5~ 3) .
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x direction
I 2 6
7 8 9 1 0 1 1 1 2 1 3 1 4 1 5
Polymer concentration (wt 7c)
Figure 10. Comparison of measured and modeled viscosities
of polymer solution at zero shear rate.
Figure
9.
Permeability contour map for the bottom layer 15x 15x3 ).
Polymer concentration
wtclc
Figure I I. Polymer adsorption isotherms.
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1 5 . I I
ase case and at lOW md
Base case and at 1500md
- - - Base case and at 2000md
-
ow case and at 1000md
- - - .
Low
case and at 1500md
-
Low
ase and at
2000
md
Polymer concentration
( ~ 1 )
Figure 12. Permeability reduction factor for the base case and the low case.
200 400 600 800 1000 1200 1400 1600
Time Days)
Figure 13. Comparison of the oil recovery for the base case PFO: 15 ~15x3) ith
the oil recovery for the areal mesh refinement case PF1: 25x25~3).
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0 200 400 600 8 00 1000 1200 1400 1600
Time
Days)
Figure 15. Comparison of the oil recovery for the base case PFO) with
the oil recovery for the lower permeability reduction case PF2).
0 200 400 600 8 1000 1200 1100 I600
Time Days)
Figure 16. Comparison of the oil recovery for the base case
PFO)
with
the oil recovery for the higher VDpcase PF4).
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Time
Days]
Figure 18. Com parison of the oil recovery for the final
simulatio n PF6 ) with the field oil recovery.
200 400 h00 XI10 1000 1?00 1400 h l l
me Days
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0 2 0 0 OO 600 SO0 1000
1200 1100
Time Days)
Figure 20. Comparison of simulated well performance PF6)with the field well
performance in well CY42.
2 0 0 400 600 8 0 0 I J00 12illl 11110 lh 00
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SP 24931
ield data
Base realization l S x l h 3
Mesh refinement
1 5 x 1 5 ~ 6
........