LAPSE:2023.23460v1
Published Article

LAPSE:2023.23460v1
Effect of Complex Natural Fractures on Economic Well Spacing Optimization in Shale Gas Reservoir with Gas-Water Two-Phase Flow
March 27, 2023
Abstract
At present, investigation of the effects of natural fractures on optimal well spacing of shale gas reservoirs from an economic perspective has been lacking. Traditional frameworks of fracture characterization, such as local grid refinement, make it unfeasible and inaccurate to study these effects of high-density natural fractures with complex geometries on well spacing. In this study, the non-intrusive EDFM (embedded discrete fracture model) method was presented to characterize fractures fast and accurately. The non-intrusiveness of EDFM removed the necessity of accessing the codes behind reservoir simulators, which meant it could simply create associated keywords that would correspondingly modify these fracture properties in separate files without information regarding the source codes. By implementing this powerful technology, a field-scale shale gas reservoir model was set up, including two-phase flow. The effective properties of hydraulic fractures were determined from the history matching process, and the results were entered into the well spacing optimization workflow. Different scenarios of natural fracture (NF) distributions and well spacing were designed, and the final economic analysis for each case was explored based on simulated productions. As a result, one of the findings of this study was that optimal well spacing tended to increase if more natural fractures were presented in the reservoir.
At present, investigation of the effects of natural fractures on optimal well spacing of shale gas reservoirs from an economic perspective has been lacking. Traditional frameworks of fracture characterization, such as local grid refinement, make it unfeasible and inaccurate to study these effects of high-density natural fractures with complex geometries on well spacing. In this study, the non-intrusive EDFM (embedded discrete fracture model) method was presented to characterize fractures fast and accurately. The non-intrusiveness of EDFM removed the necessity of accessing the codes behind reservoir simulators, which meant it could simply create associated keywords that would correspondingly modify these fracture properties in separate files without information regarding the source codes. By implementing this powerful technology, a field-scale shale gas reservoir model was set up, including two-phase flow. The effective properties of hydraulic fractures were determined from the history matching process, and the results were entered into the well spacing optimization workflow. Different scenarios of natural fracture (NF) distributions and well spacing were designed, and the final economic analysis for each case was explored based on simulated productions. As a result, one of the findings of this study was that optimal well spacing tended to increase if more natural fractures were presented in the reservoir.
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Keywords
embedded discrete fracture model, natural fractures, shale gas, well interference, well spacing optimization
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Suggested Citation
Chang C, Li Y, Li X, Liu C, Fiallos-Torres M, Yu W. Effect of Complex Natural Fractures on Economic Well Spacing Optimization in Shale Gas Reservoir with Gas-Water Two-Phase Flow. (2023). LAPSE:2023.23460v1
Author Affiliations
Chang C: State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation, Southwest Petroleum University, Xindu 637001, China
Li Y: State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation, Southwest Petroleum University, Xindu 637001, China
Li X: State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation, Southwest Petroleum University, Xindu 637001, China
Liu C: Hildebrand Department of Petroleum and Geosystems Engineering, The University of Texas at Austin, Austin, TX 78712, USA
Fiallos-Torres M: Hildebrand Department of Petroleum and Geosystems Engineering, The University of Texas at Austin, Austin, TX 78712, USA; Sim Tech LLC., Houston, TX 77494, USA
Yu W: Hildebrand Department of Petroleum and Geosystems Engineering, The University of Texas at Austin, Austin, TX 78712, USA; Sim Tech LLC., Houston, TX 77494, USA [ORCID]
Li Y: State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation, Southwest Petroleum University, Xindu 637001, China
Li X: State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation, Southwest Petroleum University, Xindu 637001, China
Liu C: Hildebrand Department of Petroleum and Geosystems Engineering, The University of Texas at Austin, Austin, TX 78712, USA
Fiallos-Torres M: Hildebrand Department of Petroleum and Geosystems Engineering, The University of Texas at Austin, Austin, TX 78712, USA; Sim Tech LLC., Houston, TX 77494, USA
Yu W: Hildebrand Department of Petroleum and Geosystems Engineering, The University of Texas at Austin, Austin, TX 78712, USA; Sim Tech LLC., Houston, TX 77494, USA [ORCID]
Journal Name
Energies
Volume
13
Issue
11
Article Number
E2853
Year
2020
Publication Date
2020-06-03
ISSN
1996-1073
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PII: en13112853, Publication Type: Journal Article
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LAPSE:2023.23460v1
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https://doi.org/10.3390/en13112853
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