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An anisotropic pore-network model to estimate the shale gas permeability

The permeability of shale is a significant and important design parameter for shale gas extraction. The shale gas permeability is usually obtained based on Darcy flow using standard laboratory permeability tests done on core samples, that do not account for different transport mechanisms at high pre...

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Autores principales: Zhang, Di, Zhang, Xinghao, Guo, Haohao, Lin, Dantong, Meegoda, Jay N., Hu, Liming
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8041813/
https://www.ncbi.nlm.nih.gov/pubmed/33846392
http://dx.doi.org/10.1038/s41598-021-86829-4
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author Zhang, Di
Zhang, Xinghao
Guo, Haohao
Lin, Dantong
Meegoda, Jay N.
Hu, Liming
author_facet Zhang, Di
Zhang, Xinghao
Guo, Haohao
Lin, Dantong
Meegoda, Jay N.
Hu, Liming
author_sort Zhang, Di
collection PubMed
description The permeability of shale is a significant and important design parameter for shale gas extraction. The shale gas permeability is usually obtained based on Darcy flow using standard laboratory permeability tests done on core samples, that do not account for different transport mechanisms at high pressures and anisotropic effects in shales due to nano-scale pore structure. In this study, the permeability of shale is predicted using a pore network model. The characteristics of pore structure can be described by specific parameters, including porosity, pore body and pore throat sizes and distributions and coordination numbers. The anisotropy was incorporated into the model using a coordination number ratio, and an algorithm that was developed for connections of pores in the shale formation. By predicting hydraulic connectivity and comparing it with several high-pressure permeability tests, the proposed three-dimensional pore network model was verified. Results show that the prediction from the anisotropic pore network model is closer to the test results than that based on the isotropic pore network model. The predicted permeability values from numerical simulation using anisotropic pore network model for four shales from Qaidam Basin, China are quite similar to those measured from laboratory tests. This study confirmed that the developed anisotropic three-dimensional pore network model could reasonably represent the natural gas flow in the actual shale formation so that it can be used as a prediction tool.
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spelling pubmed-80418132021-04-13 An anisotropic pore-network model to estimate the shale gas permeability Zhang, Di Zhang, Xinghao Guo, Haohao Lin, Dantong Meegoda, Jay N. Hu, Liming Sci Rep Article The permeability of shale is a significant and important design parameter for shale gas extraction. The shale gas permeability is usually obtained based on Darcy flow using standard laboratory permeability tests done on core samples, that do not account for different transport mechanisms at high pressures and anisotropic effects in shales due to nano-scale pore structure. In this study, the permeability of shale is predicted using a pore network model. The characteristics of pore structure can be described by specific parameters, including porosity, pore body and pore throat sizes and distributions and coordination numbers. The anisotropy was incorporated into the model using a coordination number ratio, and an algorithm that was developed for connections of pores in the shale formation. By predicting hydraulic connectivity and comparing it with several high-pressure permeability tests, the proposed three-dimensional pore network model was verified. Results show that the prediction from the anisotropic pore network model is closer to the test results than that based on the isotropic pore network model. The predicted permeability values from numerical simulation using anisotropic pore network model for four shales from Qaidam Basin, China are quite similar to those measured from laboratory tests. This study confirmed that the developed anisotropic three-dimensional pore network model could reasonably represent the natural gas flow in the actual shale formation so that it can be used as a prediction tool. Nature Publishing Group UK 2021-04-12 /pmc/articles/PMC8041813/ /pubmed/33846392 http://dx.doi.org/10.1038/s41598-021-86829-4 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Zhang, Di
Zhang, Xinghao
Guo, Haohao
Lin, Dantong
Meegoda, Jay N.
Hu, Liming
An anisotropic pore-network model to estimate the shale gas permeability
title An anisotropic pore-network model to estimate the shale gas permeability
title_full An anisotropic pore-network model to estimate the shale gas permeability
title_fullStr An anisotropic pore-network model to estimate the shale gas permeability
title_full_unstemmed An anisotropic pore-network model to estimate the shale gas permeability
title_short An anisotropic pore-network model to estimate the shale gas permeability
title_sort anisotropic pore-network model to estimate the shale gas permeability
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8041813/
https://www.ncbi.nlm.nih.gov/pubmed/33846392
http://dx.doi.org/10.1038/s41598-021-86829-4
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