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EILnet: An intelligent model for the segmentation of multiple fracture types in karst carbonate reservoirs using electrical image logs

Zhuolin Li Guoyin Zhang Xiangbo Zhang Xin Zhang Yuchen Long Yanan Sun Chengyan Lin

Natural Gas Industry B2025，Vol.12Issue(2)：P.158-173,16.

Natural Gas Industry B2025，Vol.12Issue(2)：P.158-173,16.DOI:10.1016/j.ngib.2025.03.002

EILnet: An intelligent model for the segmentation of multiple fracture types in karst carbonate reservoirs using electrical image logs

Zhuolin Li ¹Guoyin Zhang ¹Xiangbo Zhang ¹Xin Zhang ¹Yuchen Long ²Yanan Sun ¹Chengyan Lin¹

作者信息

1. State Key Laboratory of Deep Oil and Gas,China University of Petroleum(East China),Qingdao 266580,PR China School of Geosciences,China University of Petroleum(East China),Qingdao 266580,PR China
2. Fushan Oilfield Project Department,PetroChina Southern Petroleum Exploration&Development Corporation,Haikou 570100,PR China
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摘要

关键词

Karst fracture identification/Deep learning/Semantic segmentation/Electrical image logs/Image processing

分类

天文与地球科学

引用本文复制引用

Zhuolin Li,Guoyin Zhang,Xiangbo Zhang,Xin Zhang,Yuchen Long,Yanan Sun,Chengyan Lin..EILnet: An intelligent model for the segmentation of multiple fracture types in karst carbonate reservoirs using electrical image logs[J].Natural Gas Industry B,2025,12(2):P.158-173,16.

基金项目

the National Natural Science Foundation of China(42472194,42302153,and 42002144) （42472194,42302153,and 42002144）

the Fundamental Research Funds for the Central Univer-sities(22CX06002A). （22CX06002A）

Natural Gas Industry B

ISSN：2352-8540

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