LAPSE:2023.16880
Published Article

LAPSE:2023.16880
Optimization Algorithm of Effective Stress Coefficient for Permeability
March 3, 2023
Abstract
The effective stress coefficient for permeability is a significant index for characterizing the variation in permeability with effective stress. The realization of its accuracy is essential for studying the stress sensitivity of oil and gas reservoirs. The determination of the effective stress coefficient for permeability can be mainly evaluated using the cross-plotting or response surface method. Both methods preprocess experimental data and preset a specific function relation, resulting in deviation in the calculation results. To improve the calculation accuracy of the effective stress coefficient for permeability, a 3D surface fitting calculation method was proposed according to the linear effective stress law and continuity hypothesis. The statistical parameters of the aforementioned three methods were compared, and the results showed that the three-dimensional (3D) surface fitting method had the advantages of a high correlation coefficient, low root mean square error, and low residual error. The principal of using the 3D surface fitting method to calculate the effective stress coefficient of permeability was to evaluate the influence of two independent variables on a dependent variable by means of a 3D nonlinear regression. Therefore, the method could be applied to studying the relationship between other physical properties and effective stress.
The effective stress coefficient for permeability is a significant index for characterizing the variation in permeability with effective stress. The realization of its accuracy is essential for studying the stress sensitivity of oil and gas reservoirs. The determination of the effective stress coefficient for permeability can be mainly evaluated using the cross-plotting or response surface method. Both methods preprocess experimental data and preset a specific function relation, resulting in deviation in the calculation results. To improve the calculation accuracy of the effective stress coefficient for permeability, a 3D surface fitting calculation method was proposed according to the linear effective stress law and continuity hypothesis. The statistical parameters of the aforementioned three methods were compared, and the results showed that the three-dimensional (3D) surface fitting method had the advantages of a high correlation coefficient, low root mean square error, and low residual error. The principal of using the 3D surface fitting method to calculate the effective stress coefficient of permeability was to evaluate the influence of two independent variables on a dependent variable by means of a 3D nonlinear regression. Therefore, the method could be applied to studying the relationship between other physical properties and effective stress.
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Keywords
effective stress coefficient, rock permeability, sandstone, surface fitting
Subject
Suggested Citation
Zhang X, Liu J, Song J. Optimization Algorithm of Effective Stress Coefficient for Permeability. (2023). LAPSE:2023.16880
Author Affiliations
Zhang X: School of Geoscience and Technology, Southwest Petroleum University, Chengdu 610500, China; College of Engineering, Sichuan Normal University, Chengdu 610068, China [ORCID]
Liu J: School of Geoscience and Technology, Southwest Petroleum University, Chengdu 610500, China; Institute of Rock and Soil Mechanics, Chinese Academy of Sciences, Wuhan 430071, China [ORCID]
Song J: School of Geoscience and Technology, Southwest Petroleum University, Chengdu 610500, China
Liu J: School of Geoscience and Technology, Southwest Petroleum University, Chengdu 610500, China; Institute of Rock and Soil Mechanics, Chinese Academy of Sciences, Wuhan 430071, China [ORCID]
Song J: School of Geoscience and Technology, Southwest Petroleum University, Chengdu 610500, China
Journal Name
Energies
Volume
14
Issue
24
First Page
8345
Year
2021
Publication Date
2021-12-10
ISSN
1996-1073
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Original Submission
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PII: en14248345, Publication Type: Journal Article
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LAPSE:2023.16880
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https://doi.org/10.3390/en14248345
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Mar 3, 2023
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