Analysis of Microstructure and Low Permeability with 3D Digital Rock Modeling

The sandstone microstructure and permeability are important parameters for quantitative evaluation of groundwater/oil/gas resources and prediction of flow rates of water/oil/gas. In this study, we applied seven low-permeability sandstone samples obtained from North China to research the microstructu...

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Main Authors: Jinsui Wu, Min Xing, Shangxian Yin, Ciyuan Zhang, Xuexi Chen, Sihai Yi, Huiqing Lian, Dongyu Xie
Format: Article
Language:English
Published: Wiley 2022-01-01
Series:Geofluids
Online Access:http://dx.doi.org/10.1155/2022/2462652
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author Jinsui Wu
Min Xing
Shangxian Yin
Ciyuan Zhang
Xuexi Chen
Sihai Yi
Huiqing Lian
Dongyu Xie
author_facet Jinsui Wu
Min Xing
Shangxian Yin
Ciyuan Zhang
Xuexi Chen
Sihai Yi
Huiqing Lian
Dongyu Xie
author_sort Jinsui Wu
collection DOAJ
description The sandstone microstructure and permeability are important parameters for quantitative evaluation of groundwater/oil/gas resources and prediction of flow rates of water/oil/gas. In this study, we applied seven low-permeability sandstone samples obtained from North China to research the microstructure and permeability based on digital core technology. Rock images were collected by X-ray microcomputed tomography (μCT), and then software (Avizo) was applied to analyze the microstructure and calculate the parameters such as porosity, connected porosity, average equivalent diameter, tortuosity, and shape factor. By introducing the shape factor into the Kozeny–Carman equation, we modified the Kozeny–Carman equation and found that the modified equation is a function of porosity, diameter of particles, tortuosity, and particle shape factor.
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id doaj-art-c3045e9d2f5f4f908abd96a789d0bc7b
institution DOAJ
issn 1468-8123
language English
publishDate 2022-01-01
publisher Wiley
record_format Article
series Geofluids
spelling doaj-art-c3045e9d2f5f4f908abd96a789d0bc7b2025-08-20T03:23:15ZengWileyGeofluids1468-81232022-01-01202210.1155/2022/2462652Analysis of Microstructure and Low Permeability with 3D Digital Rock ModelingJinsui Wu0Min Xing1Shangxian Yin2Ciyuan Zhang3Xuexi Chen4Sihai Yi5Huiqing Lian6Dongyu Xie7State Key Laboratory of Oil and Gas Reservoir Geology and ExploitationDepartment of Safety EngineeringDepartment of Safety EngineeringDepartment of Safety EngineeringDepartment of Safety EngineeringDepartment of Safety EngineeringDepartment of Safety EngineeringDepartment of Safety EngineeringThe sandstone microstructure and permeability are important parameters for quantitative evaluation of groundwater/oil/gas resources and prediction of flow rates of water/oil/gas. In this study, we applied seven low-permeability sandstone samples obtained from North China to research the microstructure and permeability based on digital core technology. Rock images were collected by X-ray microcomputed tomography (μCT), and then software (Avizo) was applied to analyze the microstructure and calculate the parameters such as porosity, connected porosity, average equivalent diameter, tortuosity, and shape factor. By introducing the shape factor into the Kozeny–Carman equation, we modified the Kozeny–Carman equation and found that the modified equation is a function of porosity, diameter of particles, tortuosity, and particle shape factor.http://dx.doi.org/10.1155/2022/2462652
spellingShingle Jinsui Wu
Min Xing
Shangxian Yin
Ciyuan Zhang
Xuexi Chen
Sihai Yi
Huiqing Lian
Dongyu Xie
Analysis of Microstructure and Low Permeability with 3D Digital Rock Modeling
Geofluids
title Analysis of Microstructure and Low Permeability with 3D Digital Rock Modeling
title_full Analysis of Microstructure and Low Permeability with 3D Digital Rock Modeling
title_fullStr Analysis of Microstructure and Low Permeability with 3D Digital Rock Modeling
title_full_unstemmed Analysis of Microstructure and Low Permeability with 3D Digital Rock Modeling
title_short Analysis of Microstructure and Low Permeability with 3D Digital Rock Modeling
title_sort analysis of microstructure and low permeability with 3d digital rock modeling
url http://dx.doi.org/10.1155/2022/2462652
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