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An integrated method of data-driven and mechanism models for formation evaluation with logs

Meng-Lu Kang Jun Zhou Juan Zhang Li-Zhi Xiao Guang-Zhi Liao Rong-Bo Shao Gang Luo

石油科学（英文版）2025，Vol.22Issue(3)：1110-1124,15.

石油科学（英文版）2025，Vol.22Issue(3)：1110-1124,15.DOI:10.1016/j.petsci.2025.01.004

An integrated method of data-driven and mechanism models for formation evaluation with logs

Meng-Lu Kang ¹Jun Zhou ¹Juan Zhang ¹Li-Zhi Xiao ¹Guang-Zhi Liao ¹Rong-Bo Shao ¹Gang Luo¹

作者信息

1. State Key Laboratory of Petroleum Resources and Engineering,China University of Petroleum(Beijing),Beijing,102249,China||College of Artificial Intelligence,China University of Petroleum(Beijing),Beijing,102249,China
折叠

摘要

关键词

Well log/Reservoir evaluation/Label scarcity/Mechanism model/Data-driven model/Physically informed model/Self-supervised learning/Machine learning

Key words

Well log/Reservoir evaluation/Label scarcity/Mechanism model/Data-driven model/Physically informed model/Self-supervised learning/Machine learning

引用本文复制引用

Meng-Lu Kang,Jun Zhou,Juan Zhang,Li-Zhi Xiao,Guang-Zhi Liao,Rong-Bo Shao,Gang Luo..An integrated method of data-driven and mechanism models for formation evaluation with logs[J].石油科学（英文版）,2025,22(3):1110-1124,15.

基金项目

This work was supported by National Key Research and Devel-opment Program(2019YFA0708301),National Natural Science Foundation of China(51974337),the Strategic Cooperation Projects of CNPC and CUPB(ZLZX2020-03),Science and Technology Inno-vation Fund of CNPC(2021DQ02-0403),Open Fund of Petroleum Exploration and Development Research Institute of CNPC(2022-KFKT-09). （2019YFA0708301）

石油科学（英文版）

ISSN：1672-5107

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