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Identification and distribution patterns of the ultra-deep small-scale strike-slip faults based on convolutional neural network in Tarim Basin,NW China

Hao Li Jun Han Cheng Huang Lian-Bo Zeng Bo Lin Ying-Tao Yao Yi-Chen Song

石油科学（英文版）2025，Vol.22Issue(8)：3152-3167,16.

石油科学（英文版）2025，Vol.22Issue(8)：3152-3167,16.DOI:10.1016/j.petsci.2025.06.008

Identification and distribution patterns of the ultra-deep small-scale strike-slip faults based on convolutional neural network in Tarim Basin,NW China

Hao Li ¹Jun Han ²Cheng Huang ²Lian-Bo Zeng ¹Bo Lin ²Ying-Tao Yao ¹Yi-Chen Song¹

作者信息

1. State Key Laboratory of Petroleum Resources and Engineering,China University of Petroleum(Beijing),Beijing,102249,China||College of Geosciences,China University of Petroleum(Beijing),Beijing,102249,China
2. SINOPEC Northwest Oilfield Company,Urumqi,830011,Xinjiang,China
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摘要

关键词

Small-scale strike-slip faults/Convolutional neural network/Fault label/Isolated fracture-vug system/Distribution patterns

Key words

Small-scale strike-slip faults/Convolutional neural network/Fault label/Isolated fracture-vug system/Distribution patterns

引用本文复制引用

Hao Li,Jun Han,Cheng Huang,Lian-Bo Zeng,Bo Lin,Ying-Tao Yao,Yi-Chen Song..Identification and distribution patterns of the ultra-deep small-scale strike-slip faults based on convolutional neural network in Tarim Basin,NW China[J].石油科学（英文版）,2025,22(8):3152-3167,16.

基金项目

This paper is supported by the National Natural Science Foun-dation of China(No.U21B2062).The author highly appreciates the information and support provided by the Exploration and Devel-opment Research Institute of Northwest Oilfield Branch Company,SINOPEC.We appreciate the editor and several anonymous re-viewers for their constructive comments,which have significantly contributed to this article's improvement. （No.U21B2062）

石油科学（英文版）

ISSN：1672-5107

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