Abstract
Conventional enhanced oil recovery (EOR) approaches are inefficient in unconventional reservoirs. This paper provides a novel approach to enhance oil recovery from unconventional oil reservoirs through synchronous inter-fracture injection and production (SiFIP) and asynchronous inter-fracture injection and production (AiFIP). The compartmental embedded discrete fracture model (cEDFM) is introduced to simulate complex fracture geometries to quantitatively evaluate the performance of SiFIP and AiFIP. EOR performances using multiple producing methods are investigated (i.e., depletion, fluid flood, fluid Huff and Puff, SiFIP, and AiFIP). Higher cumulative oil production rates can be achieved by AiFIP and SiFIP. AiFIP yields the highest oil recovery factor, two times higher than depletion. Compared with SiFIP, AiFIP may be a preferred method when CO2/water resources are short. The impacts of fracture and injection parameters on oil production are discussed. The feasible well completions for AiFIP and SiFIP are provided. AiFIP (CO2) achieves the best EOR performance among different producing methods. This paper demonstrates the feasibility of SiFIP and AiFIP to improve oil recovery. The proposed methods improve flooding performance by transforming fluid injection among wells to among hydraulic fractures from the same multi-fractured horizontal well (MFHW), which is a promising EOR approach in unconventional oil reservoirs. The proposed EOR method (AiFIP-CO2) can improve oil recovery and mitigate the emission of CO2 as well as reduce the waste of water resources.
References
1.
Holditch
, S. A.
, and Chianeli
, R. R.
, 2008
, “Factors That Will Influence Oil and Gas Supply and Demand in the 21st Century
,” MRS Bull.
, 33
(4
), pp. 317
–323
. 2.
EIA
, 2014
, “Shale Oil and Shale Gas Resources Are Globally Abundant
,” https://www.eia.gov/todayinenergy/detail.php?id=14431.3.
Soeder
, D.
, 2018
, “The Successful Development of Gas and Oil Resources From Shales in North America
,” J. Pet. Sci. Eng.
, 163
, pp. 399
–420
. 4.
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
. 5.
He
, Y.
, Cheng
, S.
, Li
, S.
, Qin
, J.
, and Hu
, L.
, 2017
, “A Semianalytical Methodology to Diagnose the Locations of Underperforming Hydraulic Fractures Through Pressure-Transient Analysis in Tight Gas Reservoir
,” SPE J.
, 22
(3
), pp. 924
–939
. 6.
McClure
, M. W.
, Babazadeh
, M.
, Shiozawa
, S.
, and Huang
, J.
, 2016
, “Fully Coupled Hydromechanical Simulation of Hydraulic Fracturing in 3D Discrete-Fracture Networks
,” SPE J.
, 21
(4
), pp. 1
–302
. 7.
Shelley
, R.
, Shah
, K.
, Davidson
, B.
, Sheludko
, S.
, and Nejad
, A.
, 2017
, “Improving Hydraulic Fracture Design; a Key to Achieving a Higher Level of Multi-fractured Horizontal Well Performance
,” SPE Hydraulic Fracturing Technology Conference and Exhibition
, The Woodlands, Texas
, Jan. 24–26
, SPE-184816.8.
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
,” SPE Eastern Regional Meeting
, Lexington, Kentucky
, Oct. 4–6
, SPE-187524-MS.9.
Tang
, J.
, Li
, J.
, Tang
, M.
, and Xiao
, L.
, 2019
, “Investigation of Multiple Hydraulic Fractures Evolution and Well Performance in Lacustrine Shale Oil Reservoirs Considering Stress Heterogeneity
,” Eng. Fract. Mech.
, 218
, p. 106569
. 10.
Guo
, T.
, Tang
, S.
, Liu
, S.
, Liu
, X.
, and Rui
, Z.
, 2020
, “Physical Simulation of Hydraulic Fracturing of Large-Sized Tight Sandstone Outcrops
,” SPE J.
, 26
(1
), pp. 372
–393
. 11.
Liu
, X.
, Sun
, H.
, Lv
, A.
, and Fan
, D.
, 2020
, “Gas-Water Two Phased Productivity Analysis of Tight Gas Reservoir Based on Fracturing Fluid Flowback Data
,” J. Northeast Pet. Univ.
, 44
(2
), pp. 103
–112
.12.
U.S. Energy Information Administration
, 2021
, Annual Energy Outlook.
, U.S. Energy Information Administration
, Washington, DC
.13.
Singh
, H.
, and Cai
, J.
, 2018
, “Screening Improved Recovery Methods in Tight-Oil Formations by Injecting and Producing Through Fractures
,” Int. J. Heat Mass Transfer
, 116
, pp. 977
–993
. 14.
Gordon
, D.
, Sautin
, Y.
, and Wang
, T.
, 2014
, “China's Oil Future
,” https://carnegieendowment.org/2014/05/06/china-s-oil-future-pub-55437.15.
Rystad Energy
, 2014
, Shale Companies Have Proven More Efficient but Not More Productive
, Rystad Energy
, Oslo, Norway
.16.
Gaswirth
, S. B.
, and Marra
, K. R.
, 2015
, “Geological Survey 2013 Assessment of Undiscovered Resources in the Bakken and Three Forks Formations of the U.S Williston Basin Province
,” AAPG Bull.
, 99
(4
), pp. 639
–660
. 17.
Delaihdem
, D. K.
, 2013
, “Decline Curve Analysis and Enhanced Shale Oil Recovery Based on Eagle Ford Shale Data
,” M.S. thesis
, University of Alaska Fairbanks
, Alaska
.18.
Wachtmeister
, H.
, Lund
, L.
, Aleklett
, K.
, and Höök
, M.
, 2017
, “Production Decline Curves of Tight Oil Wells in Eagle Ford Shale
,” Nat. Resour. Res.
, 26
(3
), pp. 365
–377
. 19.
Calderon
, A. J.
, and Pekney
, N. J.
, 2020
, “Optimization of Enhanced Oil Recovery Operations in Unconventional Reservoirs
,” Appl. Energy
, 258
, p. 114072
. 20.
Huang
, J.
, Jin
, T.
, Barrufet
, M. A.
, and Killough
, J.
, 2020
, “Evaluation of CO2 Injection Into Shale Gas Reservoirs Considering Dispersed Distribution of Kerogen
,” Appl. Energy
, 260
, p. 114285
. 21.
Wang
, Z.
, Liu
, X.
, Luo
, H.
, Peng
, B.
, and Rui
, R.
, 2021
, “Foaming Properties and Foam Structure of Produced Liquid in Alkali/Surfactant/Polymer Flooding Production
,” ASME J. Energy Resour. Technol.
, 143
(10
), pp. 1
–25
. 22.
Du
, F.
, and Nojabaei
, B.
, 2020
, “A Black-Oil Approach to Model Produced Gas Injection in Both Conventional and Tight Oil-Rich Reservoirs to Enhance Oil Recovery
,” Fuel
, 263
, p. 116680
. 23.
Zhong
, H.
, Yang
, T.
, Yin
, H.
, Lu
, J.
, and Fu
, C.
, 2020
, “Role of Alkali Type in Chemical Loss and ASP-Flooding Enhanced Oil Recovery in Sandstone Formations
,” SPE Reservoir Eval. Eng.
, 23
(2
), pp. 431
–445
. 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.
Wei
, B.
, Song
, T.
, Gao
, Y.
, Xiang
, H.
, Xu
, X.
, Kadet
, V.
, Bai
, J.
, and Zhai
, Z.
, 2020
, “Effectiveness and Sensitivity Analysis of Solution Gas Re-injection in Baikouquan Tight Formation, Mahu Sag for Enhanced Oil Recovery
,” Petroleum
, 6
(3
), pp. 253
–263
. 26.
Liu
, S.
, Zhang
, L.
, Zhang
, K.
, Zhou
, J.
, He
, H.
, and Hou
, Z.
, 2019
, “A Simplified and Efficient Method for Water Flooding Production Index Calculations in Low Permeable Fractured Reservoir
,” ASME J. Energy Resour. Technol.
, 141
(11
), p. 112905
. 27.
Tang
, Y.
, Liao
, S.
, Lei
, X.
, Yu
, G.
, and Kang
, X.
, 2019
, “Study on Improving the Sweep Efficiency of CO2 Flooding in Low Permeability Fractured Reservoirs in Huang-3 Block
,” Reservoir Eval. Dev.
, 9
(3
), pp. 9
–13
.28.
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
. 29.
Yu
, W.
, Zhang
, Y.
, Varavei
, A.
, Sepehrnoori
, K.
, and Miao
, J.
, 2019
, “Compositional Simulation of CO2 Huff-n-Puff in Eagle Ford Tight Oil Reservoirs With CO2 Molecular Diffusion, Nanopore Confinement, and Complex Natural Fractures
,” SPE Reservoir Eval. Eng.
, 22
(2
), pp. 492
–508
. 30.
Dombrowski
, R. J.
, Fonseca
, E. R.
, Karanikas
, J. M.
, and Fonseca
, E. R.
, 2015
, “Fluid Injection in Light Tight Oil Reservoirs
,” U.S. Patent No. 9127544.31.
Zhu
, P.
, Balhoff
, M.
, and Mohanty
, K.
, 2017
, “Compositional Modeling of Fracture-to-Fracture Miscible Gas Injection in an Oil-Rich Shale
,” J. Pet. Sci. Eng.
, 152
, pp. 628
–638
. 32.
Yu
, H.
, Yang
, Z.
, Luo
, L.
, Liu
, J.
, Cheng
, S.
, Qu
, X.
, Lei
, Q.
, and Liu
, J.
, 2019
, “Application of Cumulative-in-Situ-Injection-Production Technology to Supplement Hydrocarbon Recovery among Fractured Tight Oil Reservoirs: A Case Study in Changing Oilfield, China
,” Fuel
, 242
, pp. 804
–808
. 33.
Cheng
, S.
, Wang
, Y.
, Lang
, H.
, Yu
, H.
, Zhu
, C.
, and Yang
, B.
, 2017
, “Feasibility of Inter-fracture Injection and Production for the Same Multistage Fractured Horizontal Well in Tight Oil Reservoir
,” Acta Pet. Sin.
, 38
(12
), pp. 1411
–1419
.34.
Azzolina
, N.
, Peck
, W.
, and Hamling
, J.
, 2016
, “How Green is My Oil? A Detailed Look at Greenhouse Gas Accounting for CO2-Enhanced Oil Recovery (CO2-EOR) Sites
,” Int. J. Greenhouse Gas Control
, 51
, pp. 369
–379
. 35.
Jiang
, J.
, Rui
, Z.
, Hazlett
, R.
, and Lu
, J.
, 2019
, “An Integrated Technical-Economic Model for Evaluating CO2 Enhanced Oil Recovery Development
,” Appl. Energy
, 247
, pp. 190
–211
. 36.
Ekechukwu
, G. K.
, Falode
, O.
, and Orodu
, O. D.
, 2020
, “Improved Method for the Estimation of Minimum Miscibility Pressure for Pure and Impure CO2–Crude Oil Systems Using Gaussian Process Machine Learning Approach
,” ASME J. Energy Resour. Technol.
, 142
(12
), p. 12303
. 37.
Yan
, B.
, Wang
, Y.
, and Killough
, J. E.
, 2016
, “Beyond Dual-Porosity Modeling for the Simulation of Complex Flow Mechanisms in Shale Reservoirs
,” Comput. Geosci.
, 20
(1
), pp. 69
–91
. 38.
Warren
, J. E.
, and Root
, P. J.
, 1963
, “The Behavior of Naturally Fractured Reservoirs
,” SPE J.
, 3
(3
), pp. 245
–255
.39.
Hinkley
, R.
, Gu
, Z.
, Wong
, T.
, and Camilleri
, D.
, 2013
, “Multi-porosity Simulation of Unconventional Reservoirs
,” SPE Unconventional Resources Conference Canada
, Calgary, Alberta
, Nov. 5–7
, SPE-167146-MS.40.
Pruess
, K.
, and Narasimhan
, T. N.
, 1985
, “A Practical Method for Modeling Fluid and Heat Flow in Fractured Porous Media
,” SPE J.
, 25
(1
), pp. 14
–26
. 41.
Wu
, Y.
, and Pruess
, K.
, 1988
, “A Multiple-Porosity Method for Simulation of Naturally Fractured Petroleum Reservoirs
,” SPE Reservoir Eng.
, 1
(3
), pp. 327
–336
. 42.
Ouillon
, G.
, Castaing
, C.
, and Sornette
, D.
, 1996
, “Hierarchical Geometry of Faulting
,” J. Geophys. Res.: Solid Earth
, 101
(B3
), pp. 5477
–5487
. 43.
Karimi-Fard
, M.
, and Firoozabadi
, A.
, 2003
, “Numerical Simulation of Water Injection in Fractured Media Using the Discrete-Fracture Model and the Galerkin Method
,” SPE Reservoir Eval. Eng.
, 6
(2
), pp. 117
–126
. 44.
Gale
, J. F.
, Laubach
, S. E.
, and Olson
, J. E.
, 2014
, “Natural Fractures in Shale: A Review and New Observations
,” AAPG Bull.
, 98
(11
), pp. 2165
–2216
. 45.
Heinemann
, Z. E.
, Brand
, C.
, Munka
, M.
, and Chen
, Y. M.
, 1989
, “Modeling Reservoir Geometry With Irregular Grids
,” SPE Reservoir Eng.
, 6
(2
), pp. 225
–232
. 46.
Lee
, S. H.
, Jensen
, C. L.
, and Lough
, M. F.
, 2000
, “Efficient Finite-Difference Model for Flow in a Reservoir With Multiple Length-Scale Fractures
,” SPE J.
, 5
(3
), pp. 268
–275
. 47.
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
. 48.
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
. 49.
Xu
, Y.
, and Sepehrnoori
, K.
, 2019
, “Development of an Embedded Discrete Fracture Model for Field-Scale Reservoir Simulation With Complex Corner-Point Grids
,” SPE J.
, 24
(4
), pp. 1552
–1575
. 50.
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
. 51.
Jiang
, J.
, and Younis
, R. M.
, 2016
, “Hybrid Coupled Discrete-Fracture/Matrix and Multicontinuum Models for Unconventional-Reservoir Simulation
,” SPE J.
, 21
(3
), pp. 1009
–1027
. 52.
Ţene
, M.
, Bosma
, S. B. M.
, Al Kobaisi
, M. S.
, and Hajibeygi
, H.
, 2017
, “Projection-Based Embedded Discrete Fracture Model (pEDFM)
,” Adv. Water Resour.
, 105
, pp. 205
–216
. 53.
Chai
, Z.
, Yan
, B.
, Killough
, J. E.
, and Wang
, Y.
, 2018
, “An Efficient Method for Fractured Shale Reservoir History Matching: The Embedded Discrete Fracture Multi-Continuum Approach
,” J. Pet. Sci. Eng.
, 160
, pp. 170
–181
. 54.
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
,” SPE Annual Technical Conference and Exhibition
, Dallas, TX
, Sept. 24–26
, SPE-191395-MS.Copyright © 2021 by ASME
You do not currently have access to this content.
