Abstract

It has recently been demonstrated that complex fracture networks (CFNs) especially activated natural fractures (ANF) play an important role in unconventional reservoir development. However, traditional rate transient analysis (RTA) methods barely investigate the impact of CFN or ANF. Furthermore, the influence of CFN on flow regime is still ambiguous. Failure to consider these effects could lead to misdiagnosis of flow regimes and underestimation of original oil in place (OOIP). A novel numerical RTA method is therefore presented herein to improve the quality of reserves assessment. A new methodology is introduced. Propagating hydraulic fractures (HFs) can generate different stress perturbations to allow natural fractures (NFs) to fail, forming various ANF patterns. An embedded discrete fracture model (EDFM) of ANF is stochastically generated instead of local grid refinement (LGR) method to overcome the time-intensive computation time. These models are coupled with reservoir models using non-neighboring connections (NNCs). Results show that except for simplified models used in previous studies subjected to the traditional concept of stimulated reservoir volume (SRV); in our study, the ANF region has been discussed to emphasis the impact of NF on simulation results. Henceforth, ANF could be only concentrated around the near-wellbore region, and it may also cover the whole simulation area. Obvious distinctions could be viewed for different kinds of ANF on diagnostic plots. Instead of SRV-dominated flow mentioned in previous studies, ANF-dominated flow developed in this work is shown to be more reasonable. Also, new flow regimes such as interference flow inside and outside activated natural fracture flow region (ANFR) are found. In summary, better evaluation of reservoir properties and reserves assessment such as OOIP are achieved based on our proposed model compared with conventional models. The novel RTA method considering CFN presented herein is an easy-to-apply numerical RTA technique that can be applied for reservoir and fracture characterization as well as OOIP assessment.

References

1.
Chu
,
H.
,
Liao
,
X.
,
Chen
,
Z.
, and
John Lee
,
W. J.
,
2020
, “
Rate-Transient Analysis of a Constant-Bottomhole-Pressure Multihorizontal Well Pad With a Semianalytical Single-Phase Method
,”
SPE J.
,
25
(
6
), pp.
3280
3299
.
2.
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
(
107479
), pp.
1
14
.
3.
Clarkson
,
C. R.
,
2013
, “
Production Data Analysis of Unconventional Gas Wells: Review of Theory and Best Practices
,”
Int. J. Coal Geol.
,
109–110
, pp.
101
146
.
4.
Fisher
,
M. K.
,
Wright
,
C. A.
,
Davidson
,
B. M.
,
Goodwin
,
A. K.
,
Fielder
,
E. O.
,
Buckler
,
W. S.
, and
Steinsberger
,
N. P.
,
2002
, “
Integrating Fracture Mapping Technologies to Optimize Stimulations in the Barnett Shale
,”
Proceedings of the SPE Annual Technical Conference and Exhibition
,
San Antonio, TX
,
Sept. 29
, SPE-77441-MS.
5.
Maxwell
,
S. C.
,
Urbancic
,
T. I.
,
Steinsberger
,
N.
, and
Zinno
,
R.
,
2002
, “
Microseismic Imaging of Hydraulic Fracture Complexity in the Barnett Shale
,”
Proceedings of the SPE Annual Technical Conference and Exhibition
,
San Antonio, TX
,
Sept. 29
, SPE-77440-MS.
6.
Fisher
,
M. K.
,
Heinze
,
J. R.
,
Harris
,
C. D.
,
Davidson
,
B. M.
,
Wright
,
C. A.
, and
Dunn
,
K. P.
,
2004
, “
Optimizing Horizontal Completion Techniques in the Barnett Shale Using Microseismic Fracture Mapping
,”
Proceedings of the SPE Annual Technical Conference and Exhibition
,
Houston, TX
,
Sept. 26
, SPE-90051-MS.
7.
Mayerhofer
,
M. J.
,
Lolon
,
E.
,
Warpinski
,
N. R.
,
Cipolla
,
C. L.
,
Walser
,
D. W.
, and
Rightmire
,
C. M.
,
2010
, “
What Is Stimulated Reservoir Volume?
,”
SPE Prod. Oper.
,
25
(
1
), pp.
89
98
.
8.
Anderson
,
D. M.
,
Nobakht
,
M.
,
Moghadam
,
S.
, and
Mattar
,
L.
,
2010
, “
Analysis of Production Data From Fractured Shale Gas Wells
,”
Proceedings of the SPE Unconventional Gas Conference
,
Pittsburgh, PA
,
Feb. 23
, SPE-131787-MS.
9.
Jia
,
P.
,
Cheng
,
L.
,
Clarkson
,
C. R.
, and
Williams-Kovacs
,
J. D.
,
2017
, “
Flow Behavior Analysis of Two-Phase (Gas/Water) Flowback and Early-Time Production From Hydraulically-Fractured Shale gas Wells Using a Hybrid Numerical/Analytical Model
,”
Int. J. Coal Geol.
,
182
, pp.
14
31
.
10.
Jia
,
P.
,
Cheng
,
L.
,
Huang
,
S.
,
Xue
,
Y.
,
Clarkson
,
C. R.
,
Williams-Kovacs
,
J. D.
,
Wang
,
S.
, and
Wang
,
D.
,
2019
, “
Dynamic Coupling of Analytical Linear Flow Solution and Numerical Fracture Model for Simulating Early-Time Flowback of Fractured Tight oil Wells (Planar Fracture and Complex Fracture Network)
,”
J. Pet. Sci. Eng.
,
177
, pp.
1
23
.
11.
Wang
,
H.
,
2018
, “
Discrete Fracture Networks Modeling of Shale gas Production and Revisit Rate Transient Analysis in Heterogeneous Fractured Reservoirs
,”
J. Pet. Sci. Eng.
,
169
, pp.
796
812
.
12.
Mishra
,
S.
,
2014
, “
Exploring the Diagnostic Capability of RTA Type Curves
,”
Proceedings of the SPE Annual Technical Conference and Exhibition
,
Amsterdam, The Netherlands
,
Oct. 27
, SPE-173481-STU.
13.
Qin
,
J.
,
Cheng
,
S.
,
He
,
Y.
,
Wang
,
Y.
,
Feng
,
D.
,
Yang
,
Z.
,
Li
,
D.
, and
Yu
,
H.
,
2019
, “
Decline Curve Analysis of Fractured Horizontal Wells Through Segmented Fracture Model
,”
ASME J. Energy Resour. Technol.
,
141
(
1
), p.
012903
.
14.
Zhang
,
M.
, and
Ayala
,
L. F.
,
2018
, “
A General Boundary Integral Solution for Fluid Flow Analysis in Reservoirs With Complex Fracture Geometries
,”
ASME J. Energy Resour. Technol.
,
140
(
5
), p.
052907
.
15.
Sun
,
Q.
, and
Ayala
,
L. F.
,
2019
, “
Analysis of Multiphase Reservoir Production From Oil/Water Systems Using Rescaled Exponential Decline Models
,”
ASME J. Energy Resour. Technol.
,
141
(
8
), p.
082903
.
16.
Song
,
B.
,
Economides
,
M. J.
, and
Ehlig-Economides
,
C. A.
,
2011
, “
Design of Multiple Transverse Fracture Horizontal Wells in Shale Gas Reservoirs
,”
Proceedings of the SPE Hydraulic Fracturing Technology Conference
,
The Woodlands, TX
,
Jan. 24
, SPE-140555-MS.
17.
Clarkson
,
C. R.
, and
Beierle
,
J. J.
,
2011
, “
Integration of Microseismic and Other Post-Fracture Surveillance with Production Analysis: A Tight gas Study
,”
J. Nat. Gas Sci. Eng.
,
3
(
2
), pp.
382
401
.
18.
Artus
,
V.
,
Houze
,
O.
, and
Chen
,
C.-C.
,
2019
, “
Flow Regime-Based Decline Curve for Unconventional Reservoirs: Generalization to Anomalous Diffusion and Power Law Behavior
,”
Proceedings of the SPE/AAPG/SEG Unconventional Resources Technology Conference
,
Denver, CO
,
July 22
, URTEC-2019-293-MS.
19.
Chu
,
W.-C.
,
Pandya
,
N. D.
,
Flumerfelt
,
R. W.
, and
Chen
,
C.
,
2019
, “
Rate-Transient Analysis Based on the Power-Law Behavior for Permian Wells
,”
SPE Reservoir Eval. Eng.
,
22
(
4
), pp.
1360
1370
.
20.
Raghavan
,
R.
, and
Chen
,
C.-C.
,
2017
, “
Rate Decline, Power Laws, and Subdiffusion in Fractured Rocks
,”
SPE Reservoir Eval. Eng.
,
20
(
3
), pp.
738
751
.
21.
Raghavan
,
R.
, and
Chen
,
C.-C.
,
2017
, “
Addressing the Influence of a Heterogeneous Matrix on Well Performance in Fractured Rocks
,”
Transp. Porous Media
,
117
(
1
), pp.
69
102
.
22.
Raghavan
,
R.
, and
Chen
,
C.-C.
,
2018
, “
A Conceptual Structure to Evaluate Wells Producing Fractured Rocks of the Permian Basin
,”
Proceedings of the SPE Annual Technical Conference and Exhibition
,
Dallas, TX
,
Sept. 24
, SPE-191484-MS.
23.
Raghavan
,
R.
, and
Chen
,
C.-C.
,
2019
, “
Evaluation of Fractured Rocks Through Anomalous Diffusion
,”
Proceedings of the SPE Western Regional Meeting
,
San Jose, CA
,
Apr. 22
, SPE-195305-MS.
24.
Chu
,
W.-C.
,
Scott
,
K. D.
,
Flumerfelt
,
R.
,
Chen
,
C.
, and
Zuber
,
M. D.
,
2020
, “
A New Technique for Quantifying Pressure Interference in Fractured Horizontal Shale Wells
,”
SPE Reservoir Eval. Eng.
,
23
(
1
), pp.
143
157
.
25.
Tian
,
C.
, and
Horne
,
R.
,
2017
, “
Recurrent Neural Networks for Permanent Downhole Gauge Data Analysis
,”
Proceedings of the SPE Annual Technical Conference and Exhibition
,
San Antonio, TX
,
Oct. 9
, SPE-187181-MS.
26.
Tian
,
C.
, and
Horne
,
R.
,
2019
, “
Applying Machine-Learning Techniques To Interpret Flow-Rate, Pressure, and Temperature Data From Permanent Downhole Gauges
,”
SPE Reservoir Eval. Eng.
,
22
(
2
), pp.
386
401
.
27.
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
,”
J. Unconv. Oil Gas Resour.
,
15
, pp.
134
145
.
28.
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
,”
Proceedings of the SPE Unconventional Resources Conference-USA
,
The Woodlands, TX
,
Apr. 10
, SPE-164550-MS.
29.
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
,”
Proceedings of the SPE Unconventional Resources Conference Canada
,
Calgary, Alberta, Canada
,
Nov. 5
, SPE-167231-MS.
30.
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
(
4
), pp.
750
758
.
31.
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
(
2
), pp.
289
303
.
32.
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
.
33.
Jiang
,
J.
,
Shao
,
Y.
, and
Younis
,
R. M.
,
2014
, “
Development of a Multi-Continuum Multi-Component Model for Enhanced Gas Recovery and CO2 Storage in Fractured Shale Gas Reservoirs
,”
Proceedings of the SPE Improved Oil Recovery Symposium
,
Tulsa, OK
,
Apr. 12
, SPE-169114-MS.
34.
Ding
,
D. Y.
,
Farah
,
N.
,
Bourbiaux
,
B.
,
Wu
,
Y.-S.-S.
, and
Mestiri
,
I.
,
2018
, “
Simulation of Matrix/Fracture Interaction in Low-Permeability Fractured Unconventional Reservoirs
,”
SPE J.
,
23
(
4
), pp.
1389
1411
.
35.
Ţene
,
M.
,
Bosma
,
S. B.
,
Al Kobaisi
,
M. S.
, and
Hajibeygi
,
H.
,
2017
, “
Projection-Based Embedded Discrete Fracture Model (pEDFM)
,”
Adv. Water Resour.
,
105
, pp.
205
216
.
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
,”
Proceedings of the SPE Annual Technical Conference and Exhibition
,
Dallas, TX
,
Sept. 24
, SPE-191395-MS.
37.
Eltahan
,
E.
,
Yu
,
W.
,
Sepehrnoori
,
K.
,
Kerr
,
E.
,
Miao
,
J.
, and
Ambrose
,
R.
,
2019
, “
Modeling Naturally and Hydraulically Fractured Reservoirs with Artificial Intelligence and Assisted History Matching Methods Using Physics-Based Simulators
,”
Proceedings of the SPE Western Regional Meeting
,
San Jose, CA
,
Apr. 22
, SPE-195269-MS.
38.
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
,”
Proceedings of the SPE/AAPG/SEG Unconventional Resources Technology Conference
,
Denver, Co
,
July 31
, URTEC-2019-659-MS.
39.
Tripoppoom
,
S.
,
Ma
,
X.
,
Yong
,
R.
,
Wu
,
J.
,
Yu
,
W.
,
Sepehrnoori
,
K.
,
Miao
,
J.
, and
Li
,
N.
,
2020
, “
Assisted History Matching in Shale gas Well Using Multiple-Proxy-Based Markov Chain Monte Carlo Algorithm: The Comparison of K-Nearest Neighbors and Neural Networks as Proxy Model
,”
Fuel
,
262
, p.
116563
.
40.
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
,”
Proceedings of the International Petroleum Technology Conference
,
Beijing, China
,
Mar. 22
, IPTC-19468-MS.
41.
Fiallos
,
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
,”
Proceedings of the SPE Oklahoma City Oil and Gas Symposium
,
Oklahoma City, Oklahoma
,
Apr. 8
, SPE-195240-MS.
42.
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
,”
Proceedings of the SPE/AAPG/SEG Unconventional Resources Technology Conference
,
Denver, CO
,
July 31
, URTEC-2019-552-MS.
43.
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
.
44.
He
,
Y.
,
Qiao
,
Y.
,
Qin
,
J.
,
Tang
,
Y.
,
Wang
,
Y.
, and
Chai
,
Z.
,
2022
, “
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
.
45.
Blasingame
,
T. A.
,
Mccray
,
T. L.
, and
Lee
,
W. J.
,
1991
, “
Decline Curve Analysis for Variable Pressure Drop/Variable Flowrate Systems
,”
Proceedings of the SPE Gas Technology Symposium
,
Houston, TX
,
Jan. 22
, SPE-21513-MS.
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