Spe-29904-ms.pdf

Society of Petroleum Engineers

SPE29904 Numerical Simulation of Alkali/Surfactant/Polymer Flooding Yuan Shiyi*, Yang Puhua*, Dai Zhongqiu arid Shen Kuiyou Research Institute of Petroleum Exploration & Development , P.R. China .SPE Members

Copyright 1995, Society of Petroleum Engineers, Inc. This paper was prepared for presentation at the International Meeting on Petroleum Engineering held in Beijing, PR China, 14-17 November 1995. This paper was selected for presentation by an SPE Program Committee following review of information contained in an abstract submitted by the author(s). Contents of the paper, as presented, have not been reviewed by the Society of Petroleum Engineers and are subjected 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. Permission to copy is restricted to an abstract of not more than 300 words. Illustrations may not be copied. The abstract should contain conspicuous acknowledgment of where and by whom the paper is presented. Write Librarian, SPE, P.O. Box 833836, Richardson, TX 75083-3836, U.S.A. (Facsimile 214-952-9435).

ABSTRACT This paper presents a 3-D compositional numerical simulator of alkali!smfactant/polymer (ASP) flooding. It takes into consideration 5 major mass-transfer processes (convection, diffusion-dispersion, liquidliquid transfer, liquid-solid transfer and chemical reactions) and all important phenomena such as decrease of interfacial tension with synergism, variation of each phase residual saturation and relative permeability, polymer solution behavior (viscosity, rheology, residual resistance factor, in-situ gelation, etc.) and mobility control, fast and long-term alkali losses by different factors (ion exchanges, acid oil, C0 2, polymer and rock), chemical adsorptions in presence of alkali, fluid and rock compressibilities, capillary pressure, gravity, etc. All phenomenological parameters in this simulator have definite physical senses and are obtainable from experimental data without extra assumption so that it is more capable to simulate real problems. This simulator can be applied to simulate different chemical flooding processes using polymer, alkali and/or surfactant agents with any combination. It has been verified by comparing the results of calculation with experimental data and it is a reliable tool for simulating and forecasting ASP flooding processes. A complete series of runs presented in this paper make understanding various References and illustrations at end of paper 139

mechanisms and parameter effe~ts such as ASP synergistic actions, dynamic and equilibrium alkali interfacial tensions, fluid viscosities, consumption and other chemical losses, injection strategy, etc. The studies are very useful to guide ASP field application. The forecasting results of a real AP flooding pilot by using this simulator are presented in the paper.

INTRODUCTION The great attention has been given to synergistic chemical flooding processes using alkali, polymer and/or smfactant during last several years because the oil recovery can be greatly improved by synergism of these 2 or 3 chemicals, meanwhile the used quantity of expensive surfactant can be reduced even 10 times by using cheaper alkali agent so that the method will be of great prospect.· The alkali/surfactant/polymer (ASP) flooding is specially suitable to recover acid oil. According to numerous research results, the main oil displacement mechanisms of ASP flooding are as follows: · Reducing interfacial tension (1FT): the reaction between alkali and acid component in oil can produce in-situ surfactant to reduce 1FT and residual oil saturation, and the synergism of alkali with injected surfactant and/or polymer can further decrease 1FT and enlarge the low 1FT zone.

2

NUMERICAL SIMULATION OF ALKALI/SURFACTANT/POLYMER FLOODING

• Controlling mobility: the injection of polymer can increase aqueous phase viscosity and decrease its effective permeability to enlarge sweeping volume. • Reducing chemical losses: the adsorption losses of surfactant and polymer can be greatly decreased by alkali. • Mechanisms of alkali flooding such as emulsion and entrapment, emulsion and entrainment, wettability reverse, spontaneous emulsion and coalescence, rigid film dissolution, etc. In above mechanisms, the first three were considered as the most important ones. The main mass-transfer phenomena in such chemical flooding processes are as follows: • Convection • Diffusion-dispersion • Transfer between liquid-liquid phases • Transfer between liquid-solid phases • Chemical reactions A lot of physico-chemical phenomena are involved in above mass-transfer processes, mainly as follows: • 1FT reduction: this is a determinate effect for mobilizing residual oil. According to recent researches, there are some relationships between oil mobilization and dynamical 1FT. • Alkali loss: this affects greatly the oil recovery effeciency because alkali is a major chemical agent in ASP flooding (other chemicals are of very low concentration). There are many factors causing fast and long-term alkali losses in reservoir such as exchange between Na+ in alkali and H+, Ca 2+, Mg2+, etc. in rock, acid component in oil, divalent cations, C0 2 in fluid, reactions between alkali and polymer (long-term hydrolysis), and between alkali ... and rock. • Sutfactant and polymer losses by adsorptionretention. • Phase behavior: phase equilibria and properties will be variant because of chemical additives, but in very low concentration, the variation effect of phase equilibria is less important. • Residual saturation variation: residual saturations for each phase will be decreased owing to 1FT reduction. The enhanced oil recovery is essentially contributed by residual oil saturation reduction. • Relative permeability variation due to 1FT and residual saturation variation, emulsion formation, polymer injection, etc. 140

• Chemical dispersion and dilution which cause the concentration decrease of chemcial slug. • Polymer solution behavior such as viscosity, rheology, residual resistance factor, inaccessible porous volume, further hydrolysis by alkali, etc. • Ion exchange between fluid and rock, causing variation of salinity environment. • Salinity and its variation which effect 1FT, chemical adsorption, phase behavior, polymer solution viscosity, etc. • Others such as viscous fingering, flu!.d and rock compressibilities, compatibility of chemicals, precibitation, clay swelling, etc. It is shown that the mechanisms and physicochemical phenomena involved in ASP flooding process are very complicated. Even though the method has shown some advantages (better oil recovery and economic efficiency) over classic chemical flooding in theory and in laboratory, there are no many examples of successful field application. A lot of research works including experiments, theorical study, pilot tests have been carried out for understanding the process and for putting it in use earlier. Some attempt of numerical study has been made with considerable advances, which plays a very important role in mechanism study, factor sensibility analyses, pilot design, petformance forecast, field ' application guide, etc. The numerical simulation of ASP flooding is very difficult due to its complication. Although some works have been done, they are not applicable enough for well simulating oilfield cases because of their simplicity and/or preference in laboratory use. We will present below a compositional ASP flooding numerical simulator which takes into consideration all important mechanisms and phenomena involved in the process, and which is more capable to simulate real problems and more practical in use.

NUMERICAL SIM:ULATOR !.Equation system:

* Basic assumptions: • Reservoir is isothermal. • Local equilibrium exists.

YUAN SHIYI YANG PU HUA DAl ZHONG QIU SHEN KUI YOU

SPE 29904

• Generalized Darcy law is applicable to multiphase flow. • Generalized Fick law is applicable to multicomponendispersion. *Phases and components • Number of phases(n,): 3 phases (w,s,o) are considered in the model. Owing to the low concentration of surfactant (generally Cs< 1%) in ASP flooding, two phases (w,o) are essentielly in presence in most cases. • Number of components(nc): n components are designed, mainly as follows: w, o, s, p, Na+, Ca 2+, Mg2+, OH-, CO/-, (SiO/-, SiO/), C02, ~ crosslinking agent, rock components, etc. * Basic equations • Mass consetvation for each component (nc)

-

div [F. I

-

+

D ]

aA 1

+ -

f

at

•

B. I

(

1)

i. 1 ... n '

' c

where Convection term

Dispersion term

Accumulation term Source/ sink term • By definition(n,+2)

=1 Ei zi = 1 E.v1J.. = 1' J. Ejsj

I

=

1' ... '.-...,> n

(2) (3) (4)

• Relationships among Zi, Y u and Sj (n, •nc-1) . Y 1J.. =Y IJ..(Zk) i=} ... n-1 ' ' c k= 1 ... n ' ' c j = 1, .. ·,n,

(5)

Sj =Sj(Zk) k= 1 ... n ' ' c j = 1,. .. ,~-1

3

(6)

• Capillary pressure (n,-1)

The basic variables in the above system are n,(nc+2)+nc which are equal to the equation number so that the system can be solved in principle. Basic variables pj Zi

y IJ..

Number n, nc n,•nc

sj Total

~

Basic equations (1) (2) (3) (4) (5) (6) (7) Total

Number nc 1 1 n, n,(nc-1) n,-1 n,-1

n,(nc+2)+nc

~(nc+2)+nc

This is a very complicated equation system which is nonlinear and coupled with a lot of variable parameters. We need complimental functional relationships describing phenomenological parameters and numerical solution techniques to solve the system.

2.Pbenomenological parameters The important parameters and their description will be given as follows: * Alkali concentration conversion Alkali types used in ASP flooding may be NaOH, Na 2 C03 , Na 2 Si03 , Na 2 Si04 , Na3P04 , and so on in which OH- produced by alkali dissolution in water plays a key role. The OH- concentration can be obtained directly for 141 NaOH, and convertibly for Na2 C03 by following

4

NUMERICAL SIMULATION OF ALKALI/SURFACTANT/POLYMER FLOODING

equations: Experiments can provide r 2 in different concentration of~andoH-.

• r 3 : long-term alkali loss by rock dissolution. This loss can be modelled by the following dynamical equation: where equilibrium constant K can be get from Chemical Handbook. The conversion for other alkalis can be made in the same way. * Alkali loss (or OH- consumption) Alkali loss is a very important parameter in ASP flooding, which are affected by many factors with very complicated mechanisms. We will deal with this parameter in a simplified way both to model major phenomena and to have practical use. The alkali loss is described by reaction term ~ in Eq( 1): RoH-

=

-

«<» S w

a

a; (r 1

+

r2 +

, ••• '

where K31 is from laboratory data. • r4 : alkali loss by C02 in water: K41

[C0 2 ] 0

[C0 2 ]w

.,....

K42

co 2 +on- . . . nco; This loss can be converted by HC0-3 produced by reaction of C02 and OH-. • r 5 : alkali losses by Ca2+, Mg2+, etc.

rn )

Kst

C a 2 + + 2 0 H - ..... C a ( 0 H ) 2 !

where "-"-OH- loss r-loss quantity in unit volume n-n influential factors Main factors are as follows: • r 1 : fast alkali loss caused by ion exchange between N a+ in alkali and W on rock surface. According to Re£ 10, this loss can be represented approximatively by an equation similar to Langmuir type adsorption function:

This loss can be calculated by solubility product K. The similar treatment is for the losses by Mg2+, etc. * Adsorption of injected surfactant • The adsorption can be modelled by the following equation for Langmuir type

where qs0 and as are dependent on cation strength E. • The measured qs 1 ~Cs cwves for different E can be directly input. • When alkali is in presence, the adsorption will be reduced with pH increase:

where C-OH- concentration, a 1 - coefficient r 1°-maximum loss by this factor a1,r1°-determined from experimental data

q

• r2 : alkali loss by acid component in oil.

=q G

1

s

•(1-b

s

pH -7 ) pHmax.-7

where ~ 1 -adsorption for pH=7.

142

SPE 29904

YUAN SlllYI YANG PU HUA DAI ZHONG QIU SHEN KUI YOU

where ~t and ej are end-point values and exponents respectively. * Capillary pressure

Pl\nax-pH in injected alkali concentration. bs-coefficient. * Polymer adsorption Its description is similar to the above treatment. * Other component consumption The comsumptions ofNa+, IfAo, C02, Ca2+, Mg2+, and so on can be converted and calculated from r 1, r 2 , r 4, r 5 and ion exchange. *Ion exchange The exchange between monovalent cation c+ in aqueous phase and divalent cation C2+ on rock surface can be modelled by the following equation[71

(c)2_..

c~-·

where P row ( S n )

=

C pc·

lf.

N

·(1-S n)

pc

a

P cow-capillary pressure for o/w system 0 0 w-IFT for o/w system sn-wet phase saturation Cpc and Npc-constants.

(c)2

-QvPc

5

c 2·

where Ov-exchange capacity Pc-exchange coefficient * Interfacial tension In order to really behave the synergism of chemicals, the interfacial tension will be represented by measured isovalue diagram which is function of injected alkali, surfactant and polymer concentrations for a given oil and a water salinity (E):

* Residual saturation Srj The residual saturation for each phase is dependant on Capillary Number N c defined as follows: Nc

I:L

=

u1 v1

I

The measured P cow~Sn cmve can be input too. * Polymer solution viscosity • The viscosity under low shear rate can be represented by 0 II r-p

=

2

II

r-w

(1 +Q 1C p+Q 2CP +

"" •)

where a 1, a2•·• are coefficients dependent on E. • The measured Jlp 0 dependent on polymer/alkali concentrations and water salinity can be input too. * Polymer solution rheology The polymer solution viscosity will be reduced by shear effect, which can be modelled by the following ~' viscosity reduction factor dependent on porous velocity:

1 -~---'--

a

R ,.

=

"' - "' P 0

w =

R ,. ( V)

J!p- flw

The Sti for different N c can be obtained by laboratory measurement. * Relative permeability ~j

The viscosity Jlp under different velocity can be get from measured ~~V relationship:

Jlp • Jl w

+

(Jlpo - Jl w ) • R,.

* Residual resistance factor(RRF) 143

6

NUMERICAL SIMULATION OF ALKALI/SURFACTANT/POLYMER FLOODING

Rk

=

p 0-density at P 0 P-compressibility coefficient

(R:-x - 1) qp 1 + ---,-----=max

*Component dispersion coefficient Dij

qp

where qpmax and Rxmax are saturated polymer adsorption and correspondant RRF in a given salinity environment(£). * Polymer inaccessible porous volume This parameter can be measured by experiment. *In-situ gelation The gel( G) can be formed in-situ by injection of polymer (P) and crosslinking agent(L ). The rates of consumed P/L and formed G can be represented by~ in Eq(1):

where D 0-molecular diffilsion coefficient * Other required parameters: measured experiments.

by

3.Numerical solution The above equation system will be solved by the process of implicit pressure, explicit overall composition, other basic variables' and related parameters' calculation. The simulator is named ASP executable in VAX, CONVEX, SUN workstations or other similar computers.

SIMULATION EXAMPLES

where m-reacting mass in unit volume K-reaction constant n-exponent The treatment and solution of these equations are given in detail in Ref 15. * Phase equilibria The variation effect of phase equilibria for ASP flooding is less important because of very low surfactant concentration (C 8 ). For higher Cs(> 1o/o), the representation and treatment of multiphase equilibria is given in Ref 14. * Phase density p j

where P0-reference pressure 144

The above simulator ASP can be applied to simulate water flooding, polymer flooding, in-situ gelation, and ASP flooding in any combination. The following simulation examples are essentielly for exhibiting main :functions of the software and presenting ASP flooding mechanism studies, parameter sensibility analyses and forecast results of a real alkali/polymer flooding pilot design. (The simulation studies for surfactant/polymer flooding and in-situ gelation were given in detail in Ref 11~ 15).

1.Phenomenological parameters The parameters used in simulation are measured in laboratory and arranged for normalization. The importants are as follows: • Intetfacial tension: The equilibrium 1FT values (a e) dependent on ( CA' Cs) and on (CA, Cp) in water salinity (TDS=3000ppm, the same for following parameters) are given in Fig. 1 and 2 respectively. According to recent researches, some ones report the minimum dynamic 1FT (am) value could play an important role in residual oil

SPE 29904

YUAN SHIYI YANG. PU HUA DAI ZHONG QIU SHEN Kill YOU

mobilization. We have prepared am too for investigating its effect. The am values are about 10 times lower than a e in most cases. • Residual saturation and relativ~ permeability: Table 1 for 3 Nc values (Nee and Ncm in the table are calculated by using ae and am respectively). • Alkali loss: 3.2mg/g rock for CA=2%. • Surfactant adsorption: 2.3mg/g rock for Cs=0.4%. • Polymer adsorption: 34ug/g rock for Cp=0.1 %. • Polymer solution viscosity: Fig.3 for different CA. • Fluid properties: Table 2.

2.Simulation of laboratory experiment Experiment The experiment was completed on an oilfield core with the following process: • Saturating oil (Soi=0.67) • Waterflooding to residual oil saturation (S 0 r1=0.33) • Alkali/polymer flooding to residual oil saturation (Sor2=0.20) • Alkali/surfactant/polymer flooding to residual oil saturation (Sor3 =0.09) Data about the core and test are given in Table 2. 'f4e oil recovecy and watercut for 3 phases of displacement are presented in Fig. 4. The incremental recoveries of AP and ASP floodings in comparison with waterflooding are 20% and 3 7% respectively. Marching simulation The experiment is simulated by using the above simulator and parameters under the same conditions (Table 2). The simulating results are given in Fig.4 too. The very good agreement between calculation and experiment data has been obtained so that the simulator and the compatibility of parameters have been checked successfully.

3. Cross-section simulation The following examples are for selecting the injecting composition and studying the effects of several ·important parameters. According to experimental results, the oil recovecy of ASP flooding is much better than that of AP flooding. But in oilfield application, the effects of factors such as alkali loss, chemical 145

7

adsorption, reservoir heterogeneity, and so on are very important and difficult to be modeled by core test. An important decision to be made before field application is to determine the system of 3 or 2 chemical agents to be injected in the same investment of chemicals. The ASP flooding will be used only in cases of its oil recovery and economic efficiency much better than those of AP flooding because of surfactant expensiveness and much more problems of ASP compatibility. We will select the formulation system to be injected by simulation study. A cross-section of reservoir with stratified heterogeneity (Table 3) is designed for considing oilfield condition. The starting conditions for ASP flooding are 44.3% of oil recovery and 98.6% of watercut. A lot of runs have been serially performed for different study purposes. The results of principal runs are given in Table 4 (for f(J) =98% ). Injection formulation system: We can see under oil field conditions, the oil recovery by ASP flooding is not much better than that by AP flooding( see li 1, li3 or li2, li4 ) because of limited slug size, more chemical losses, etc. But the chemical cost for one ton of incremental.oil is much higher so that the injection of AP system is preferable in these reservoir conditions. ae andam: Higher oil recovery is obtained by using am , but the time for watercut reaching to 98% is longer(li 1, li 11 or li2, 112 ). For the same injected porous volume, the oil recovery is similar by using both a e and am. We think the recovecy is conservative·by using a e and optimistic by using am so that the real recovery is between the two's. Chemical slug size: The recovery increases with the chemical slug size, but the chemical cost .for one ton of incremental oil increases too(I 1,I3). In addition, more total injected PV results in more operation expenses so that the slug size of0.3PV is preferable. Chemical concentrations: Alkali, surfactant and polymer concentrations which give better oil recovery and economic efficiency are 2%, 0.4o/o and 0.1% respectively.

8

NUMERICAL SIMULATION OF ALKALI/SURFACTANT/POLYMER FLOODING

Polymer contribution: Though polymer contribution to 1FT reduction is not considerable, its mobility control effect is very important on oil recovery improvement(li 1, li7 ). Chemical synergism: Under the comparable conditions, the synergistic chemical flooding gives better recovery than the flooding using any single chemical agent and their simple addition so that the importance of synergism is obseiVed(li 1, li 2 , li 5 ,li7).

• A 3-D multifunctional compositional numerical simulator of alkali/surfactant/polymer flooding has been established, checked and applied successfully to simulate real problems. It is a powerful and practical tool to study and forecast ASP flooding processes. • Various mechanisms and parameter effects of ASP flooding have been deeper understood by this simulation study. • The pilot design presented in this paper is guiding the oilfield operations.

4. 3-D simulation

ACKNOWLEDGEMENTS The following presentation is about main forecasting results of a real AP flooding pilot test by using our simulator. The pilot zone is in a stratified sandstone reseiVoir vvith the properties between homogeneous and heterogeneous characteristics of the above crosssectional model. 4 wells (Fig. 5, 3 chemical injectors and 1 producer) are involved in the center, and 7 equilibrium wells in the rounding zone. According to the above results, the AP system was choose to be injected. We have performed about 40 runs for selecting operation parameters such asAP injection concentrations, slug size, injection opportunity, rate and strategy, and so on, and for studying effects of different factors such as 1FT ( oe, oJ, viscosity reduction caused by pump, pipeline, well hole and perforation, etc. The simulations involve oil recovery forecasting and economic analysing for both the center triangle and total pilot zone. Based on the above research, the pilot test has been designed with the main injection parameters selected as follows: • Alkali concentration:2% • Polymer concentration: 0.1% • Slug size:0.35PV Under the above conditions, the forecasting incremental oil recovery will be between 6. 7 6~7. 58% forecasted by using a e and am' and the chemical cost for one ton of incremental oil is between ¥425~379. The forecast performence is given in Fig.6. Now, the pilot is underway.

We are very thankful to President Shen Pingping and Chief Engineer Han Dakuang of Research Institute of Petroleum Exploration & Development (RIPED), and professor Liu Pu of Beijing Petroleum University for their direction and help in various aspects.

REFERENCES [1] Nelson R C et al. Cosurfactant-enhanced alkaline flooding. SPE/DOE 12672. April1984. [2]Mihcakan I M et al. Blending alkaline and polymer solution together into a single slug improves EOR. SPE 15158. May 1986. [3]Schuler P J et al. Improving chemical flood efficiency vvith Micellar/Alkaline/Polymer Processes. SPE/DOE 14934. April 1986. ,, [4]Islam M R et al. Mathematical modeling of enhanced oil recovery by alkali solutions in the presence ofcosurfactant and polymer. JPSE. 5. 1991. [5]Breit V Setal. An easily applied black oil model of caustic waterflooding. SPE 7999. April 1979. [6]Ramakrishnan T Setal. Fractional-flow model for high pH flooding. SPERE. Feb. 1989. [7]Bhuyan D et al. Mathematical model of high pH chemical flooding. SPE/DOE 17398. April1988.

CONCLUSIONS 146

SPE 29904

YUAN SHIYI YANG PU HUA DAI ZHONG QIU SHEN KUI YOU

[8]Bhuyan D et al. Simulation of high-pH coreflood experiments using a compositional chemical flood simulator. SPE 21029. [9]0koy C U et al. A chemical displacement model for alkaline steam flooding in linear systems. SPE 13580, 1985. [10]Bunge A. C.e et al. Migration of alkaline pulse in reservoir sands. SPE 10288, 1981. [11]Yuan Shiyi, Etude numerique de la recuperation assistee d' hydrocarbures en place par injection d' additifs chimiques, PhD Dissertation, Paris, 1986. [12]Yuan Shiyi and N.Van Quy, Effects of main parameters of the chemical flooding process, AIChE 1987 spring meeting, Houston, 1987. JPSE 3, 1989. [13]N.Van Quy and Yuan Shiyi, A twodimensional chemical flooding simulator using measured phenomenological data, 4th European Symposium on EOR, Hamburg, 1987. [14]Yuan Shiyi and N. Van Quy, Chemical flooding simulation (Part !:theory, Part :U:: application), Acta Petrolei sinica, (1) 1988 and (3) 1989. [ 15]Yuan Shiyi, Polymer in-situ gelation numerical simulator, Acta Petrolei sinica, (I) 1991.

NOMENCLATURE C-concentration E-cation strength g-gravity acceleration K-absolute permeability or reaction constant ~-relative permeability HA-acid component Q-mass rate in unit porous volume q-adsorption in unit porous volume R-reaction rate S-saturation s..-residual saturation V-Darcy velocity Yij-mass fraction of component i in phase j Zi-overal1 mass fraction of component i 147

a-accessible porous volume fraction a-interfacial tension Jl-viscosity p-density «1>-porosity 'tl 0-oil recovery ratio Subscript: i-component j-phase w-aqueous phase o-oleic phase p-polymer s-surfactant A-alkali

9

Table 1. Relative permeability data NCe

4. 23X 10- 7

5. 68 X 10- 5

3. 80 X 10- 3

NCm

4. 23X 10- 7

2. 08 X 10- 3

2. 49 X 10- 2

Sor

0.33

0. 20

0.09

K~w

0.07

0. 11

0. 16

Table 2

Basic experimental data

Core data: Length : 11. 4cm Diameter: 2. Scm Porosity: 29. 9% Permeability (air): 1. 01t-tm2 (water) : 0. 66t-tm2 Fluid properties: Temperature: 58 ·c Water viscosity: 0. 48mPa • s Oil viscosity: 18. 2mPa • s (Surface) 6. 3mPa • s (Reservoir) Injection rate: 0. 2mllmin Injection formulation: AlP: 2%Na 2C0 3+800ppmAC530 AlSIP: 2%Na2C03+o. 125%LPS6+800ppmAC530 Table 3

Cross-section model parameters (%)

K(fLm 2)

H(m)

1

26. 1

3.000

1.2

2

26. 1

1. 000

1.2

3

30.5

1. 000

1. 65

4

30.5

3. 000

1. 65

Note :Distance between injector and producer= 200m

148

Table 4. Simulation results Chemical slug Run No. CaC%)

Cs(%) t:pCppm)

PV

l]o C%) / Total PV

Chemical cost C¥) 6oil(t)

Notes

ll 1

2

0

800

0. 3

51. 1/1. 07

286

Basic AP f.

ll 2

2

0. 4

800

0. 3

54. 4/1. 08

432

Basic ASP f.

ll 3

2

0

800

0. 5

52. 9/1. 30

376

n4

2

0.4

800

0. 5

57. 6/1. 30

547

ll 5

0

0

800

0. 3

47. 1/0. 94

336

ll 6

1

0

800

0. 3

48. 9/0. 96

313

ll 7

2

0

0

0. 3

45.2/0.85

1172

ll 8

2

0

1200

0. 3

52. 6/1. 12

294

ll 9

2

0. 2

800

0. 3

51. 5/1. 06

437

ll 10

2

0

800

0. 3

54. 3/1. 12

194

Using

C1m

ll 11

2

0.4

800

0.3

56. 4/1. 13

361

Using

C1m

Notes: 1. Starting conditions: 1]0 = 44. 3%, fw= 98. 6% 2. Chemical prices: Alkali: 1000¥ /t Surfactant: 12000¥ /t Polymer: 23000¥ /t

149

0.4

O.J

§

0.2

J

0.1

0.0

-r:::;:=;~;=r,-~~~~:.:r=;:::=;i=i=i=:.;:;=r=r~~T"'""T'""'T"~~

0.0 CA(%)

I

f"l

\

0.04

150

25

CA=O.O% 20

c.a o;j

15

CA=0.5%

p..

s

Ill

CA=l. O%

10

::1.

c. . . =2. O%

500

1000 Cp(ppm)

1500

2000

Fig. 3 Polymer solution viscosity

-~ ~

ct-4

60

-

~40 0

- Experiment · · · Simulation

r::-

5

10 PV

15

20

Fig. 4 Production curves and their marching

151

Ia

Fig. 5 Well location 1n pilot center zone

0

(T)

~

~···

•

a

........

-a

8

lD

0 N

0

, ::E

>-

c....

Q.)

~

>

0

u Q.) a:

~

Cl)

0

b. A - WF 0 e- A/PF '-J

0

0

0

2

3

4

5

6

7

8

9

Time (year) Fig. 6 Comparison of AP flooding with water flooding

152