Abstract

In this paper, the characterization parameter “effective displacement flux” is employed to describe the flushing intensity, and a new numerical simulator in which the rock-fluid properties considered functions of the effective displacement flux is developed based on the black oil model. Additionally, a conceptual reservoir model is established to validate the effective characterization of the time-varying mechanisms: the time-varying oil viscosity can characterize the viscous fingering of the water phase and the time-varying absolute permeability can present the aggravation of reservoir heterogeneity, the alteration of wettability is characterized with the time-varying relative permeability, and the ultimate recovery will increase with the combined effect of all three time-varying factors. Eventually, the new simulator is applied to the simulation of an actual waterflooding reservoir to illustrate the assistance in history matching. The simulation results of our simulator can readily match the history data, which proves that the consideration of comprehensive time-varying rock-fluid properties can significantly improve the accuracy during the numerical simulation of waterflooding reservoirs.

References

1.
Bautista
,
J. F.
, and
Taleghani
,
A. D.
,
2017
, “
The State of the Art and Challenges in Geomechanical Modeling of Injector Wells: A Review Paper
,”
ASME J. Energy Resour. Technol.
,
139
(
1
), p.
012910
.
2.
Sun
,
X.
,
Zhang
,
Y.
,
Wu
,
J.
,
Xie
,
M.
, and
Hu
,
H.
,
2019
, “
Optimized Cyclic Water Injection Strategy for Oil Recovery in Low-Permeability Reservoirs
,”
ASME J. Energy Resour. Technol.
,
141
(
1
), p.
012905
.
3.
Xu
,
J.
,
Guo
,
C.
,
Jiang
,
R.
, and
Wei
,
M.
,
2016
, “
Study on Relative Permeability Characteristics Affected by Displacement Pressure Gradient: Experimental Study and Numerical Simulation
,”
Fuel
,
163
, pp.
314
323
.
4.
Zhang
,
N.
,
Cao
,
J.
,
James
,
L. A.
, and
Johansen
,
T. E.
,
2021
, “
High-Order Streamline Simulation and Macro-Scale Visualization Experimental Studies on Waterflooding Under Given Pressure Boundaries
,”
J. Pet. Sci. Eng.
,
203
, p.
108617
.
5.
Kwak
,
D.
,
Han
,
S.
,
Han
,
J.
,
Wang
,
J.
,
Lee
,
J.
, and
Lee
,
Y.
,
2018
, “
An Experimental Study on the Pore Characteristics Alteration of Carbonate During Waterflooding
,”
J. Pet. Sci. Eng.
,
161
, pp.
349
358
.
6.
Purswani
,
P.
, and
Karpyn
,
Z. T.
,
2019
, “
Laboratory Investigation of Chemical Mechanisms Driving Oil Recovery From Oil-Wet Carbonate Rocks
,”
Fuel
,
235
, pp.
406
415
.
7.
Cui
,
C. Z.
,
Li
,
K. K.
,
Yang
,
Y.
,
Huang
,
Y. S.
, and
Cao
,
Q.
,
2014
, “
Identification and Quantitative Description of Large Pore Path in Unconsolidated Sandstone Reservoir During the Ultra-High Water-Cut Stage
,”
J. Pet. Sci. Eng.
,
122
, pp.
10
17
.
8.
Sun
,
S.
,
Han
,
J.
, and
Guo
,
Y.
,
1996
, “
Laboratory Experiment on Physical Properties of Flooding Sandstone in Shengtuo Oilfield
,”
J. China Univ. Petr. Nat. Sci. Ed.
,
20
, pp.
33
35
.
9.
Anderson
,
W. G.
,
1987
, “
Wettability Literature Survey Part 5: The Effects of Wettability on Relative Permeability
,”
J. Pet. Technol.
,
39
(
11
), pp.
1453
1468
.
10.
Zhang
,
H. X.
,
Liu
,
Q. N.
,
Li
,
F. Q.
, and
Lu
,
Y. P.
,
1997
, “
Variations of Petrophysical Parameters After Sandstone Reservoirs Watered Out in Daqing Oilfield
,”
SPE Adv. Technol. Ser.
,
5
(
1
), pp.
128
139
.
11.
Matthew
,
D. J.
,
Per
,
H. V.
, and
Martin
,
J. B.
,
2003
, “
Prediction of Wettability Variation and its Impact on Flow Using Pore- to Reservoir-Scale Simulations
,”
J. Petrol. Sci. Eng.
,
39
(
3–4
), pp.
231
246
.
12.
Graue
,
A.
,
Aspenes
,
E.
,
Bognø
,
T.
,
Moe
,
R. W.
, and
Ramsdal
,
J.
,
2002
, “
Alteration of Wettability and Wettability Heterogeneity
,”
J. Petrol. Sci. Eng.
,
33
(
1–3
), pp.
3
17
.
13.
Ma
,
M. X.
,
Ju
,
B. S.
, and
Wang
,
S. F.
,
2013
, “
Wettability Change and Its Effect on Flow in Waterflooding Reservoir
,”
Petrol Drill Technol.
,
41
(
2
), pp.
82
86
.
14.
Xu
,
J.
,
Guo
,
C.
,
Wei
,
M.
, and
Jiang
,
R.
,
2015
, “
Impact of Parameters׳ Time Variation on Waterflooding Reservoir Performance
,”
J. Petrol. Sci. Eng.
,
126
, pp.
181
189
.
15.
Guo
,
Y. L.
, and
Su
,
G. Y.
,
1998
, “
An Analysis of Factors Affecting the Precision of log Interpretation of Water Cut in a Watered Out Reservoir
,”
Pet. Explor. Dev
,
25
(
4
), pp.
59
61
.
16.
Ju
,
B. S.
,
Fan
,
T. L.
, and
Zhang
,
J. C.
,
2006
, “
Oil Viscosity Variation and its Effects on Production Performance in Water Drive Reservoir
,”
Pet. Explor. Dev
,
33
(
1
), pp.
99
102
.
17.
Park
,
H.
,
Park
,
Y.
,
Lee
,
Y.
, and
Sung
,
W.
,
2018
, “
Efficiency of Enhanced Oil Recovery by Injection of Low-Salinity Water in Barium-Containing Carbonate Reservoirs
,”
Pet. Sci.
,
15
(
4
), pp.
772
782
.
18.
Lee
,
Y.
,
Park
,
H.
,
Lee
,
J.
, and
Sung
,
W.
,
2019
, “
Enhanced Oil Recovery Efficiency of Low-Salinity Water Flooding in Oil Reservoirs Including Fe2+ Ions
,”
Energy Explor. Exploit.
,
37
(
1
), pp.
355
374
.
19.
Karabakal
,
U.
, and
Bagci
,
S.
,
2004
, “
Determination of Wettability and Its Effect on Waterflood Performance in Limestone Medium
,”
Energy Fuels
,
18
(
2
), pp.
438
449
.
20.
Eydinov
,
D.
,
Gao
,
G.
,
Li
,
G.
, and
Reynolds
,
A. C.
,
2007
, “
Simultaneous Estimation of Relative Permeability and Porosity/Permeability Fields by History Matching Production Data
,”
J. Can. Petr. Technol.
,
48
(
12
), pp.
13
25
.
21.
Zhang
,
R. H.
,
Wu
,
J. F.
,
Zhao
,
Y. L.
,
He
,
X.
, and
Wang
,
R. H.
,
2021
, “
Numerical Simulation of the Feasibility of Supercritical CO2 Storage and Enhanced Shale Gas Recovery Considering Complex Fracture Networks
,”
J. Petrol. Sci. Eng.
,
204
, p.
108671
.
22.
Akbarifard
,
M. G.
,
Azdarpour
,
A.
,
Aboosadi
,
Z. A.
,
Honarvar
,
B.
, and
Nabipour
,
M.
,
2020
, “
Numerical Simulation of Water Production Process and Spontaneous Imbibition in a Fractured Gas Reservoir—A Case Study on Homa Gas Field
,”
J. Nat. Gas Sci. Eng.
,
83
, p.
103603
.
23.
Zhao
,
Y. L.
,
Lu
,
G.
,
Zhang
,
L. H.
,
Wei
,
Y. S.
,
Guo
,
J. J.
, and
Chang
,
C.
,
2020
, “
Numerical Simulation of Shale Gas Reservoirs Considering Discrete Fracture Network Using a Coupled Multiple Transport Mechanisms and Geomechanics Model
,”
J. Pet. Sci. Eng.
,
195
, p.
107588
.
24.
Gai
,
Y. J.
,
Lu
,
D. L.
, and
Guo
,
Y. L.
,
2000
, “
Numerical Simulation by Stages About the Reservoir at Highwater Cut Period
,”
Oil Gas Recov. Technol.
,
7
(
1
), pp.
55
59
.
25.
Gao
,
B. Y.
,
Peng
,
S. M.
, and
Huang
,
S.
,
2004
, “
Staged Numerical Simulation of Layer 31, Member 21, Shahejie Formation in District 2 of Shengtuo Oilfield
,”
Pet. Explor. Dev.
,
31
(
6
), pp.
82
84
.
26.
Cui
,
C. Z.
, and
Zhao
,
X. Y.
,
2004
, “
The Reservoir Numerical Simulation Study With the Variety of Reservoir Parameters
,”
J. Hydrodyn.
,
19
, pp.
912
915
.
27.
Liu
,
X. T.
,
2011
, “
Numerical Simulation Technique for Time-Varying Reservoir Properties in Medium and High Permeability Sandstone Reservoirs
,”
Pet. Geol. Recovery Effic.
,
18
(
5
), pp.
58
62
.
28.
Jiang
,
R.
,
Zhang
,
W.
,
Zhao
,
P.
,
Jiang
,
Y.
,
Cai
,
M.
,
Tao
,
Z.
,
Zhao
,
M.
,
Ni
,
T.
,
Xu
,
J.
,
Cui
,
Y.
, and
Hua
,
J.
,
2018
, “
Characterization of the Reservoir Property Time-Variation Based on ‘Surface Flux’ and Simulator Development
,”
Fuel
,
234
, pp.
924
933
.
29.
Sun
,
Z.
,
Li
,
Y.
,
Ma
,
K.
,
Xu
,
J.
,
Zhang
,
G.
,
Jiang
,
R.
, and
Pan
,
S.
,
2019
, “
A Novel Method to Characterise Time-Variation of Reservoir Properties: Experimental Study, Simulator Development and Its Application in Bohai Bay Oilfield
,”
SPE/IATMI Asia Pacific Oil & Gas Conference and Exhibition
,
Bali, Indonesia
,
Oct. 29–31
,
Paper No. SPE-196282-MS
, p.
9
.
30.
Sun
,
K.
,
Liu
,
H.
,
Wang
,
Y.
,
Ge
,
L.
,
Gao
,
J.
, and
Du
,
W.
,
2020
, “
Novel Method for Inverted Five-Spot Reservoir Simulation at High Water-Cut Stage Based on Time-Varying Relative Permeability Curves
,”
ACS Omega
,
5
(
22
), pp.
13312
13323
.
31.
Zhang
,
Y.
, and
Yang
,
D.
,
2014
, “
Estimation of Relative Permeability and Capillary Pressure for Tight Formations by Assimilating Field Production Data
,”
Inverse Probl. Sci. Eng.
,
22
(
7
), pp.
1150
1175
.
32.
Zhang
,
Y.
, and
Yang
,
D.
,
2013
, “
Simultaneous Estimation of Relative Permeability and Capillary Pressure for Tight Formations Using Ensemble-Based History Matching Method
,”
Comput. Fluids
,
71
(
1
), pp.
446
460
.
33.
Wang
,
S.
,
Cheng
,
L.
,
Huang
,
S.
,
Xue
,
Y.
,
Bai
,
M.
,
Wu
,
Y.
,
Jia
,
P.
,
Sun
,
Z.
, and
Wang
,
J.
,
2019
, “
A Semi-analytical Method for Modeling Two-Phase Flow Behavior in Fractured Carbonate Oil Reservoirs
,”
ASME J. Energy Resour. Technol.
,
141
(
7
), p.
072902
.
34.
Seales
,
M. B.
,
2020
, “
Multiphase Flow in Highly Fractured Shale Gas Reservoirs: Review of Fundamental Concepts for Numerical Simulation
,”
ASME J. Energy Resour. Technol.
,
142
(
10
), p.
100801
.
35.
Jiang
,
R.
,
Liu
,
X.
,
Cui
,
Y.
,
Wang
,
X.
,
Gao
,
Y.
,
Mao
,
N.
, and
Yan
,
X.
,
2020
, “
Production Performance Analysis for Multi-Branched Horizontal Wells in Composite Coal Bed Methane Reservoir Considering Stress Sensitivity
,”
ASME J. Energy Resour. Technol.
,
142
(
7
), p.
073001
.
36.
Zhang
,
M.
, and
Ayala
,
L. F.
,
2019
, “
A Similarity-Based Semi-Analytical Solution for Recovery Performance Assessment of Unconventional Oil and Gas Reservoirs With Interfacial-Tension-Dependent Capillary Pressure Effects
,”
ASME J. Energy Resour. Technol.
,
142
(
4
), p.
042905
.
37.
Papi
,
A.
,
Mohebbi
,
A.
, and
Eshraghi
,
S. E.
,
2018
, “
Numerical Simulation of the Impact of Natural Fracture on Fluid Composition Variation Through a Porous Medium
,”
ASME J. Energy Resour. Technol.
,
141
(
4
), p.
042901
.
You do not currently have access to this content.