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Single-Factor Comprehensive Reservoir Quality Classification Evaluation—Taking the Hala’alat Mountains at the Northwestern Margin of the Junggar Basin as an Example

[Image: see text] In the process of petroleum geology exploration and development, reservoir quality evaluation is an essential component. However, conventional reservoir quality evaluation methods are no longer able to provide accurate and comprehensive assessments for all types of reservoirs. Ther...

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Autores principales: Pu, Qiongyao, Xie, Jun, Li, XinShuai, Zhang, YuanPei, Hu, Xiao, Hao, Xiaofan, Zhang, Fengrui, Zhao, Zhengquan, Cao, Jianfeng, Li, Yan, Gao, Renjie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2023
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10568729/
https://www.ncbi.nlm.nih.gov/pubmed/37841167
http://dx.doi.org/10.1021/acsomega.3c04449
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author Pu, Qiongyao
Xie, Jun
Li, XinShuai
Zhang, YuanPei
Hu, Xiao
Hao, Xiaofan
Zhang, Fengrui
Zhao, Zhengquan
Cao, Jianfeng
Li, Yan
Gao, Renjie
author_facet Pu, Qiongyao
Xie, Jun
Li, XinShuai
Zhang, YuanPei
Hu, Xiao
Hao, Xiaofan
Zhang, Fengrui
Zhao, Zhengquan
Cao, Jianfeng
Li, Yan
Gao, Renjie
author_sort Pu, Qiongyao
collection PubMed
description [Image: see text] In the process of petroleum geology exploration and development, reservoir quality evaluation is an essential component. However, conventional reservoir quality evaluation methods are no longer able to provide accurate and comprehensive assessments for all types of reservoirs. Therefore, the comprehensive evaluation of reservoir quality using multiple single factors is of significant importance in improving the level of reservoir quality assessment and enhancing the effectiveness of oil and gas exploration techniques. Conventional reservoir quality evaluation methods can assess only the quality of individual reservoir properties, resulting in limited classification outcomes. Taking the Cretaceous formations in the southern margin of the Hala’alat Mountain in the Junggar Basin as the research object, preliminary classification criteria were established based on the principles of formation coefficient, storage coefficient, and flow unit index. Combining experimental data such as core observation, thin-section identification, pore permeability analysis, and scanning electron microscopy, a comprehensive set of reservoir quality classification and evaluation criteria were developed. Furthermore, the corresponding reservoir classification evaluation maps were generated to illustrate the spatial distribution of reservoir quality. The study reveals that the area can be classified into four types of reservoirs, namely, Class I, Class II, Class III, and Class IV, corresponding to the best reservoir, relatively good reservoir, relatively poor reservoir, and poor reservoir, respectively. Among them, the second (K(1)q(2)) and third (K(1)q(3)) members of the Cretaceous Qingshuihe Formation, as well as the first (K(1)h(1)) and third (K(1)h(3)) members of the Cretaceous Hutubi Formation, exhibit the best reservoir quality as Class II. On the other hand, the second member of the Cretaceous Hutubi Formation (K(1)h(2)) exhibits the best reservoir quality as Class III, with relatively poorer reservoir quality overall. The research findings of this study can provide an important theoretical basis for oil and gas exploration and development in the region.
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spelling pubmed-105687292023-10-13 Single-Factor Comprehensive Reservoir Quality Classification Evaluation—Taking the Hala’alat Mountains at the Northwestern Margin of the Junggar Basin as an Example Pu, Qiongyao Xie, Jun Li, XinShuai Zhang, YuanPei Hu, Xiao Hao, Xiaofan Zhang, Fengrui Zhao, Zhengquan Cao, Jianfeng Li, Yan Gao, Renjie ACS Omega [Image: see text] In the process of petroleum geology exploration and development, reservoir quality evaluation is an essential component. However, conventional reservoir quality evaluation methods are no longer able to provide accurate and comprehensive assessments for all types of reservoirs. Therefore, the comprehensive evaluation of reservoir quality using multiple single factors is of significant importance in improving the level of reservoir quality assessment and enhancing the effectiveness of oil and gas exploration techniques. Conventional reservoir quality evaluation methods can assess only the quality of individual reservoir properties, resulting in limited classification outcomes. Taking the Cretaceous formations in the southern margin of the Hala’alat Mountain in the Junggar Basin as the research object, preliminary classification criteria were established based on the principles of formation coefficient, storage coefficient, and flow unit index. Combining experimental data such as core observation, thin-section identification, pore permeability analysis, and scanning electron microscopy, a comprehensive set of reservoir quality classification and evaluation criteria were developed. Furthermore, the corresponding reservoir classification evaluation maps were generated to illustrate the spatial distribution of reservoir quality. The study reveals that the area can be classified into four types of reservoirs, namely, Class I, Class II, Class III, and Class IV, corresponding to the best reservoir, relatively good reservoir, relatively poor reservoir, and poor reservoir, respectively. Among them, the second (K(1)q(2)) and third (K(1)q(3)) members of the Cretaceous Qingshuihe Formation, as well as the first (K(1)h(1)) and third (K(1)h(3)) members of the Cretaceous Hutubi Formation, exhibit the best reservoir quality as Class II. On the other hand, the second member of the Cretaceous Hutubi Formation (K(1)h(2)) exhibits the best reservoir quality as Class III, with relatively poorer reservoir quality overall. The research findings of this study can provide an important theoretical basis for oil and gas exploration and development in the region. American Chemical Society 2023-09-28 /pmc/articles/PMC10568729/ /pubmed/37841167 http://dx.doi.org/10.1021/acsomega.3c04449 Text en © 2023 The Authors. Published by American Chemical Society https://creativecommons.org/licenses/by-nc-nd/4.0/Permits non-commercial access and re-use, provided that author attribution and integrity are maintained; but does not permit creation of adaptations or other derivative works (https://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Pu, Qiongyao
Xie, Jun
Li, XinShuai
Zhang, YuanPei
Hu, Xiao
Hao, Xiaofan
Zhang, Fengrui
Zhao, Zhengquan
Cao, Jianfeng
Li, Yan
Gao, Renjie
Single-Factor Comprehensive Reservoir Quality Classification Evaluation—Taking the Hala’alat Mountains at the Northwestern Margin of the Junggar Basin as an Example
title Single-Factor Comprehensive Reservoir Quality Classification Evaluation—Taking the Hala’alat Mountains at the Northwestern Margin of the Junggar Basin as an Example
title_full Single-Factor Comprehensive Reservoir Quality Classification Evaluation—Taking the Hala’alat Mountains at the Northwestern Margin of the Junggar Basin as an Example
title_fullStr Single-Factor Comprehensive Reservoir Quality Classification Evaluation—Taking the Hala’alat Mountains at the Northwestern Margin of the Junggar Basin as an Example
title_full_unstemmed Single-Factor Comprehensive Reservoir Quality Classification Evaluation—Taking the Hala’alat Mountains at the Northwestern Margin of the Junggar Basin as an Example
title_short Single-Factor Comprehensive Reservoir Quality Classification Evaluation—Taking the Hala’alat Mountains at the Northwestern Margin of the Junggar Basin as an Example
title_sort single-factor comprehensive reservoir quality classification evaluation—taking the hala’alat mountains at the northwestern margin of the junggar basin as an example
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10568729/
https://www.ncbi.nlm.nih.gov/pubmed/37841167
http://dx.doi.org/10.1021/acsomega.3c04449
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