Abstract

Complex fracture networks (CFN) provide flow channels and significantly affect well performance in unconventional reservoirs. However, traditional rate transient analysis (RTA) models barely consider the effect of CFN on production performance. The impact of multi-phase flow on rate transient behaviors is still unclear especially under CFN. Neglecting these effects could cause incorrect rate transient response and erroneous estimation of well and fracture parameters. This paper investigates multi-phase rate transient behaviors considering CFN and tries to investigate in what situations the multi-phase models should be used to obtain more accurate results. First, an embedded discrete fracture model (EDFM) is generated instead of Local Grid Refinement method to overcome time-intensive computation. The model is coupled with reservoir models using non-neighboring connections (NNCs). Second, eight cases are designed using the EDFM technology to analyze effect of natural fractures, formation permeability, and relative permeability on rate transient behaviors. Third, Blasingame plot, log–log plot, and linear flow plot are used to analyze the differences of rate transient response between single-phase and multi-phase flow in reservoirs with CFN. For multi-phase flow, severe deviations can be observed on RTA plots compared with single-phase model. Combination of three RTA type curves can characterize the differences from early to late flow regimes and improve the interpretation accuracy as well as reduce the non-unicity. Finally, field data analysis in Permian Basin demonstrates that multi-phase RTA analysis are required for analyzing production and pressure data since single-phase RTA analysis will lead to big errors especially under high water cut during fracturing fluid flowback period, early production of unconventional gas wells or after waterflooding, or water huff-n-puff.

References

1.
Blasingame
,
T. A.
,
McCray
,
T. L.
, and
Lee
,
W. J.
,
1991
, “
Decline Curve Analysis for Variable Pressure Drop/Variable Flowrate Systems
,”
The SPE Gas Technology Symposium
,
Houston, TX
,
January
, Paper No. SPE-21513-MS.
2.
Anderson
,
D. M.
,
Nobakht
,
M.
,
Moghadam
,
S.
, and
Mattar
,
L.
,
2010
, “
Analysis of Production Data From Fractured Shale Gas Wells
,”
The SPE Unconventional Gas Conference
,
Pittsburgh, PA
,
February
, Paper No. SPE-131787-MS.
3.
Qin
,
J.
,
Cheng
,
S.
,
He
,
Y.
,
Wang
,
Y.
,
Feng
,
D.
,
Yang
,
Z.
,
Li
,
D.
, and
Yu
,
H.
,
2018
, “
Decline Curve Analysis of Fractured Horizontal Wells Through Segmented Fracture Model
,”
ASME J. Energy Resour. Technol.
,
141
(
1
), p.
012903
.
4.
Wang
,
Y.
,
Cheng
,
S.
,
Wei
,
C.
,
Zhang
,
K.
, and
Yu
,
H.
,
2021
, “
Gas Rate Decline Analysis for Boundary-Dominated Flow With Fractal Reservoir Properties Under Constant/Variable Bottom-Hole Pressure Conditions
,”
J. Nat. Gas Sci. Eng.
,
88
, p.
103823
.
5.
Behmanesh
,
H.
,
Mattar
,
L.
,
Thompson
,
J. M.
,
Anderson
,
D. M.
,
Nakaska
,
D. W.
, and
Clarkson
C. R.
,
2018
, “
Treatment of Rate-Transient Analysis During Boundary-Dominated Flow
,”
SPE J.
,
23
(
4
), pp.
1145
1165
.
6.
Shahamat
,
M. S.
, and
Clarkson
,
C. R.
,
2018
, “
Multiwell, Multiphase Flowing Material Balance
,”
SPE Reservoir Eval. Eng.
,
21
(
2
), pp.
445
461
.
7.
Eker
,
I.
,
Kurtoglu
,
B.
, and
Kazemi
,
H.
,
2014
, “
Multiphase Rate Transient Analysis in Unconventional Reservoirs: Theory and Applications
,”
The SPE/CSUR Unconventional Resources Conference – Canada
,
Calgary, AB, Canada
,
September
, Paper NO. SPE-171657-MS. .
8.
Uzun
,
I.
,
Kurtoglu
,
B.
, and
Kazemi
,
H.
,
2016
, “
Multiphase Rate-Transient Analysis in Unconventional Reservoirs: Theory and Application
,”
SPE Reservoir Eval. Eng.
,
19
(
4
), pp.
553
566
.
9.
Clarkson
,
C. R.
,
Yuan
,
B.
,
Zhang
,
Z.
,
Tabasinejad
,
F.
,
Behmanesh
,
H.
,
Hamdi
,
H.
,
Anderson
,
D.
,
Thompson
,
J.
, and
Lougheed
,
D.
,
2019
, “
Anomalous Diffusion or Classical Diffusion in an Anomalous Reservoir? Evaluation of the Impact of Multi-Phase Flow on Reservoir Signatures in Unconventional Reservoirs
,”
The SPE/AAPG/SEG Unconventional Resources Technology Conference
,
Denver, CO
,
July
, Papper No. URTEC-2019-85-MS. .
10.
Hamdi
,
H.
,
Behmanesh
,
H.
, and
Clarkson
,
C. R.
,
2019
, “
A Semi-Analytical Approach for Analysis of Wells Exhibiting Multi-Phase Transient Linear Flow: Application to Field Data
,”
The SPE Annual Technical Conference and Exhibition
,
Calgary, AB, Canada
,
September
, Paper No. SPE-196164-MS. .
11.
Zhang
,
M.
,
Becker
,
M. D.
, and
Ayala
,
L. F.
,
2016
, “
A Similarity Method Approach for Early-Transient Multiphase Flow Analysis of Liquid-Rich Unconventional Gas Reservoirs
,”
J. Nat. Gas Sci. Eng.
,
28
, pp.
572
586
.
12.
Nguyen
,
K.
,
Zhang
,
M.
,
Garcez
,
J.
, and
Ayala
,
L. F.
,
2020
, “
Multiphase Transient Analysis of Flowback and Early Production Data of Unconventional Gas Wells
,”
The SPE Annual Technical Conference and Exhibition
, SPE-201303-MS.
13.
Yarveicy
,
H.
,
Habibi
,
A.
,
Pegov
,
S.
,
Zolfaghari
,
A.
, and
Dehghanpour
,
H.
,
2018
, “
Enhancing Oil Recovery by Adding Surfactants in Fracturing Water: A Montney Case Study
,”
SPE Canada Unconventional Resources Conference
,
Calgary, AB, Canada, Mar. 2018
, SPE-189829-MS.
14.
Williams-Kovacs
,
J.
, and
Clarkson
,
C. R.
,
2013
, “
Modeling Two-Phase Flowback From Multi-Fractured Horizontal Tight Gas Wells Stimulated With Nitrogen Energized Frac Fluid
,”
The SPE Unconventional Resources Conference Canada
,
Calgary, AB, Canada
,
November
, Paper No. SPE-167231-MS.
15.
Williams-Kovacs
,
J.
, and
Clarkson
,
C. R.
,
2013
, “
Stochastic Modeling of Two-Phase Flowback of Multi-Fractured Horizontal Wells to Estimate Hydraulic Fracture Properties and Forecast Production
,”
The SPE Unconventional Resources Conference
,
The Woodlands, TX
,
April
, Paper No. SPE-164550-MS. .
16.
Williams-Kovacs
,
J. D.
, and
Clarkson
,
C. R.
,
2016
, “
A Modified Approach for Modeling Two-Phase Flowback From Multi-Fractured Horizontal Shale Gas Wells
,”
J. Nat. Gas Sci. Eng.
,
30
, pp.
127
147
.
17.
Clarkson
,
C. R.
, and
Qanbari
,
F.
,
2015
, “
Transient Flow Analysis and Partial Water Relative Permeability Curve Derivation for Low Permeability Undersaturated Coalbed Methane Wells
,”
Int. J. Coal Geol.
,
152
, pp.
110
124
.
18.
Clarkson
,
C. R.
, and
Salmachi
,
A.
,
2017
, “
Rate-Transient Analysis of an Undersaturated CBM Reservoir in Australia: Accounting for Effective Permeability Changes Above and Below Desorption Pressure
,”
J. Nat. Gas Sci. Eng.
,
40
, pp.
51
60
.
19.
Yang
,
R.
,
Huang
,
Z.
,
Li
,
G.
,
Yu
,
W.
,
Sepehrnoori
,
K.
,
Tian
,
S.
,
Song
,
X.
, and
Sheng
,
M.
,
2016
, “
An Innovative Approach to Model Two-Phase Flowback of Shale Gas Wells With Complex Fracture Networks
,”
The SPE Annual Technical Conference and Exhibition
,
Dubai, UAE
,
September
, Paper No. SPE-181766-MS.
20.
Yu
,
W.
,
Wu
,
K.
,
Zuo
,
L.
,
Tan
,
X.
, and
Weijermars
,
R.
,
2016
, “
Physical Models for Inter-Well Interference in Shale Reservoirs: Relative Impacts of Fracture Hits and Matrix Permeability
,”
The SPE/AAPG/SEG Unconventional Resources Technology Conference
,
San Antonio, TX
,
August
, Paper No. URTEC-2457663-MS. .
21.
Jia
,
P.
,
Ma
,
M.
,
Cheng
,
L.
, and
Clarkson
,
C.R.
,
2020
, “
A Semi-Analytical Model for Capturing Dynamic Behavior of Hydraulic Fractures During Flowback Period in Tight oil Reservoir
,”
Energy Sci. Eng.
,
8
(
10
), pp.
3415
3440
.
22.
Wu
,
Y.
,
Cheng
,
L.
,
Ma
,
L.
,
Huang
,
S.
,
Fang
,
S.
,
Killough
,
J. E.
,
Jia
,
P.
, and
Wang
,
S.
,
2021
, “
A Transient Two-Phase Flow Model for Production Prediction of Tight Gas Wells With Fracturing Fluid-Induced Formation Damage
,”
J. Pet. Sci. Eng.
,
199
, p.
108351
.
23.
Tang
,
H.
,
Sun
,
Z.
,
He
,
Y.
,
Chai
,
Z.
,
Hasan
,
A. R.
, and
Killough
,
J.
,
2019
, “
Investigating the Pressure Characteristics and Production Performance of Liquid-Loaded Horizontal Wells in Unconventional gas Reservoirs
,”
J. Pet. Sci. Eng.
,
176
, pp.
456
465
.
24.
He
,
Y.
,
Qin
,
J.
,
Cheng
,
S.
, and
Chen
,
J.
,
2020
, “
Estimation of Fracture Production and Water Breakthrough Locations of Multi-Stage Fractured Horizontal Wells Combining Pressure-Transient Analysis and Electrical Resistance Tomography
,”
J. Pet. Sci. Eng.
,
194
, p.
107479
.
25.
Warpinski
,
N. R.
,
Mayerhofer
,
M. J.
,
Vincent
,
M. C.
,
Cipolla
,
C. L.
, and
Lolon
,
E. P.
,
2009
, “
Stimulating Unconventional Reservoirs: Maximizing Network Growth While Optimizing Fracture Conductivity
,”
J. Can. Pet. Technol.
,
48
(
10
), pp.
39
51
.
26.
Moinfar
,
A.
,
Varavei
,
A.
,
Sepehrnoori
,
K.
, and
Johns
,
R. T.
,
2013
, “
Development of a Coupled Dual Continuum and Discrete Fracture Model for the Simulation of Unconventional Reservoirs
,”
The SPE Reservoir Simulation Symposium
,
Feb. 18–20
, SPE-163647-MS.
27.
Niu
,
G.
,
Sun
,
J.
,
Parsegov
,
S.
, and
Schechter
,
D.
,
2017
, “
Integration of Core Analysis, Pumping Schedule and Microseismicity to Reduce Uncertainties of Production Performance of Complex Fracture Networks for Multi-Stage Hydraulically Fractured Reservoirs
,”
The SPE Eastern Regional Meeting
,
Lexington, KY
,
Oct. 4–6
, SPE-187524-MS.
28.
Cipolla
,
C.
,
Motiee
,
M.
, and
Kechemir
,
A.
,
2018
, “
Integrating Microseismic, Geomechanics, Hydraulic Fracture Modeling, and Reservoir Simulation to Characterize Parent Well Depletion and Infill Well Performance in the Bakken
,”
The SPE/AAPG/SEG Unconventional Resources Technology Conference
,
Houston, TX
,
July 23–25
, URTEC-2899721-MS.
29.
Wu
,
Y.
,
Cheng
,
L.
,
Killough
,
J.
,
Huang
,
S.
,
Fang
,
S.
,
Jia
,
P.
,
Cao
,
R.
, and
Xue
,
Y.
,
2021
, “
Integrated Characterization of the Fracture Network in Fractured Shale Gas Reservoirs—Stochastic Fracture Modeling, Simulation and Assisted History Matching
,”
J. Pet. Sci. Eng.
,
205
, p.
108886
.
30.
Gupta
,
I.
,
Rai
,
C.
,
Devegowda
,
D.
, and
Sondergeld
,
C. H.
,
2021
, “
Fracture Hits in Unconventional Reservoirs: A Critical Review
,”
SPE J.
,
26
(
01
), pp.
412
434
.
31.
Clarkson
,
C. R.
,
Qanbari
,
F.
, and
Williams-Kovacs
,
J. D.
,
2016
, “
Semi-Analytical Model for Matching Flowback and Early-Time Production of Multi-Fractured Horizontal Tight Oil Wells
,”
Presented at the SPE/AAPG/SEGUnconventional Resources Technology Conference
,
San Antonio, TX
, Paper No. URTEC-2460083-MS.
32.
Lee
,
S. H.
,
Lough
,
M. F.
, and
Jensen
,
C. L.
,
2001
, “
Hierarchical Modeling of Flow in Naturally Fractured Formations With Multiple Length Scales
,”
Water Resour. Res.
,
37
(
3
), pp.
443
455
.
33.
Li
,
L.
, and
Lee
,
S. H.
,
2008
, “
Efficient Field-Scale Simulation of Black Oil in a Naturally Fractured Reservoir Through Discrete Fracture Networks and Homogenized Media
,”
SPE Reservoir Eval. Eng.
,
11
(
04
), pp.
750
758
.
34.
Moinfar
,
A.
,
Varavei
,
A.
,
Sepehrnoori
,
K.
, and
Johns
,
R. T.
,
2014
, “
Development of an Efficient Embedded Discrete Fracture Model for 3D Compositional Reservoir Simulation in Fractured Reservoirs
,”
SPE J.
,
19
(
02
), pp.
289
303
.
35.
Xu
,
Y.
,
Cavalcante
,
J. S. A.
,
Yu
,
W.
, and
Sepehrnoori
,
K.
,
2017
, “
Discrete-Fracture Modeling of Complex Hydraulic-Fracture Geometries in Reservoir Simulators
,”
SPE Reservoir Eval. Eng.
,
20
(
2
), pp.
403
422
.
36.
Chai
,
Z.
,
Tang
,
H.
,
He
,
Y.
,
Killough
,
J.
, and
Wang
,
Y.
,
2018
, “
Uncertainty Quantification of the Fracture Network With a Novel Fractured Reservoir Forward Model
,”
The SPE Annual Technical Conference and Exhibition
,
Dallas, TX
,
September
, Paper No. SPE-191395-MS.
37.
Huang
,
J.
,
Jin
,
T.
,
Chai
,
Z.
,
Barrufet
,
M. A.
, and
Killough
,
J.
,
2019
, “
Compositional Simulation of Fractured Shale Reservoir With Distribution of Nanopores Using Coupled Multi-Porosity and EDFM Method
,”
J. Pet. Sci. Eng.
,
179
, pp.
1078
1089
.
38.
Xu
,
Y.
,
Yu
,
W.
, and
Sepehrnoori
,
K.
,
2019
, “
Modeling Dynamic Behaviors of Complex Fractures in Conventional Reservoir Simulators
,”
SPE Reservoir Eval. Eng.
,
22
(
3
), pp.
1110
1130
.
39.
Yu
,
W.
,
Xu
,
Y.
,
Weijermars
,
R.
,
Wu
,
K.
, and
Sepehrnoori
,
K.
,
2018
, “
A Numerical Model for Simulating Pressure Response of Well Interference and Well Performance in Tight Oil Reservoirs With Complex–Fracture Geometries Using the Fast Embedded–Discrete–Fracture–Model Method
,”
SPE Reservoir Eval. Eng.
,
21
(
2
), pp.
489
502
.
40.
Yu
,
W.
,
Wu
,
K.
,
Liu
,
M.
,
Sepehrnoori
,
K.
, and
Miao
,
J.
,
2018
, “
Production Forecasting for Shale Gas Reservoirs With Nanopores and Complex Fracture Geometries Using an Innovative Non-Intrusive EDFM Method
,”
The SPE Annual Technical Conference and Exhibition
,
Dallas, TX
,
Sept. 2018
, SPE-191666-MS.
41.
Fiallos
,
M. X.
,
Yu
,
W.
,
Ganjdanesh
,
R.
,
Kerr
,
E.
,
Sepehrnoori
,
K.
,
Miao
,
J.
, and
Ambrose
,
R.
,
2019
, “
Modeling Interwell Interference Due to Complex Fracture Hits in Eagle Ford Using EDFM
,”
The International Petroleum Technology Conference
,
Beijing, China
.
42.
Guo
,
X.
,
Wu
,
K.
,
An
,
C.
,
Tang
,
J.
, and
Killough
,
J.
,
2019
, “
Numerical Investigation of Effects of Subsequent Parent Well Injection on Interwell Fracturing Interference Using Reservoir-Geomechanics-Fracturing Modeling
,”
SPE J.
,
24
(
4
), pp.
1884
1902
.
43.
He
,
Y.
,
Qiao
,
Y.
,
Qin
,
J.
,
Tang
,
Y.
,
Wang
,
Y.
, and
Chai
,
Z.
,
2021
, “
A Novel Method to Enhance Oil Recovery by Inter-Fracture Injection and Production Through the Same Multi-Fractured Horizontal Well
,”
ASME J. Energy Resour. Technol.
,
144
(
4
), p.
043005
.
44.
Fiallos Torres
,
M. X.
,
Yu
,
W.
,
Ganjdanesh
,
R.
,
Kerr
,
E.
,
Sepehrnoori
,
K.
,
Miao
,
J.
, and
Ambrose
,
R.
,
2019
, “
Modeling Interwell Fracture Interference and Huff-N-Puff Pressure Containment in Eagle Ford Using EDFM
,”
SPE Oklahoma City Oil and Gas Symposium
,
Oklahoma City, OK
,
Apr. 2019
, SPE-195240-MS.
45.
He
,
Y.
,
Cheng
,
S.
,
Sun
,
Z.
,
Chai
,
Z.
, and
Rui
,
Z.
,
2020
, “
Improving Oil Recovery Through Fracture Injection and Production of Multiple Fractured Horizontal Wells
,”
ASME J. Energy Resour. Technol.
,
142
(
5
), p.
053002
.
46.
Tripoppoom
,
S.
,
Yu
,
W.
,
Sepehrnoori
,
K.
, and
Miao
,
J.
,
2019
, “
Application of Assisted History Matching Workflow to Shale Gas Well Using EDFM and Neural Network-Markov Chain Monte Carlo Algorithm
,”
The SPE/AAPG/SEG Unconventional Resources Technology Conference
,
Denver, CO
,
July
, Paper No. URTEC-2019-659-MS.
47.
Li
,
Q.
,
Yong
,
R.
,
Wu
,
J.
, and
Miao
,
J.
,
2021
, “
An Integrated Assisted History Matching and Embedded Discrete Fracture Model Workflow for Well Spacing Optimization in Shale Gas Reservoirs
,”
ASME J. Energy Resour. Technol.
,
143
(
7
), p.
073004
.
48.
de Araujo Cavalcante Filho
,
J.
,
Shakiba
,
M.
,
Moinfar
,
A.
, and
Sepehrnoori
,
K.
,
2015
, “
Implementation of a Preprocessor for Embedded Discrete Fracture Modeling in an IMPEC Compositional Reservoir Simulator
,”
The SPE Reservoir Simulation Symposium
,
Houston, TX
,
February
, Paper No. SPE-173289-MS. .
49.
Yu
,
W.
,
Wu
,
K.
,
Zuo
,
L.
,
Miao
,
J.
, and
Sepehrnoori
,
K.
,
2019
, “
Embedded Discrete Fracture Model Assisted Study of Gas Transport Mechanisms and Drainage Area for Fractured Shale Gas Reservoirs
,”
The SPE/AAPG/SEG Unconventional Resources Technology Conference
,
Denver, CO
,
July
, Paper No. URTEC-2019-552-MS.
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