A data augmentation method for lacustrine shale lithofacies classification based on a conditional diffusion probabilistic model:A case study from the Dongying Depression,Bohai Bay Basin,ChinaOA
A data augmentation method for lacustrine shale lithofacies classification based on a conditional diffusion probabilistic model:A case study from the Dongying Depression,Bohai Bay Basin,China
Gui-Ang Li;Cheng-Yan Lin;Chun-Mei Dong;Li-Hua Ren;Peng-Jie Ma;Yu-Qi Wu;Guo-Yin Zhang;Xin-Yu Du;Zi-Ru Zhao
State Key Laboratory of Deep Oil and Gas,China University of Petroleum(East China),Qingdao,266580,Shandong,China||School of Geosciences,China University of Petroleum(East China),Qingdao,266580,Shandong,China||Shandong Provincial Key Laboratory of Reservoir Geology,China University of Petroleum(East China),Qingdao,266580,Shandong,ChinaState Key Laboratory of Deep Oil and Gas,China University of Petroleum(East China),Qingdao,266580,Shandong,China||School of Geosciences,China University of Petroleum(East China),Qingdao,266580,Shandong,China||Shandong Provincial Key Laboratory of Reservoir Geology,China University of Petroleum(East China),Qingdao,266580,Shandong,ChinaState Key Laboratory of Deep Oil and Gas,China University of Petroleum(East China),Qingdao,266580,Shandong,China||School of Geosciences,China University of Petroleum(East China),Qingdao,266580,Shandong,China||Shandong Provincial Key Laboratory of Reservoir Geology,China University of Petroleum(East China),Qingdao,266580,Shandong,ChinaState Key Laboratory of Deep Oil and Gas,China University of Petroleum(East China),Qingdao,266580,Shandong,China||School of Geosciences,China University of Petroleum(East China),Qingdao,266580,Shandong,China||Shandong Provincial Key Laboratory of Reservoir Geology,China University of Petroleum(East China),Qingdao,266580,Shandong,ChinaSanya Offshore Oil & Gas Research Institute,Northeast Petroleum University,Sanya,572025,Hainan,ChinaState Key Laboratory of Deep Oil and Gas,China University of Petroleum(East China),Qingdao,266580,Shandong,China||School of Geosciences,China University of Petroleum(East China),Qingdao,266580,Shandong,China||Shandong Provincial Key Laboratory of Reservoir Geology,China University of Petroleum(East China),Qingdao,266580,Shandong,ChinaState Key Laboratory of Deep Oil and Gas,China University of Petroleum(East China),Qingdao,266580,Shandong,China||School of Geosciences,China University of Petroleum(East China),Qingdao,266580,Shandong,China||Shandong Provincial Key Laboratory of Reservoir Geology,China University of Petroleum(East China),Qingdao,266580,Shandong,ChinaWuxi Research Institute of Petroleum Geology,Petroleum Exploration and Production Research Institute,SINOPEC,Wuxi,214126,Jiangsu,ChinaState Key Laboratory of Deep Oil and Gas,China University of Petroleum(East China),Qingdao,266580,Shandong,China||School of Geosciences,China University of Petroleum(East China),Qingdao,266580,Shandong,China||Shandong Provincial Key Laboratory of Reservoir Geology,China University of Petroleum(East China),Qingdao,266580,Shandong,China
Lacustrine shaleLithofacies predictionConditional diffusion probabilistic modelData augmentationClass imbalance
Lacustrine shaleLithofacies predictionConditional diffusion probabilistic modelData augmentationClass imbalance
《石油科学（英文版）》 2026 (6)
3017-3036,20
This work is funded by the National Natural Science Foundation of China(Nos.42372156422021464210215342472194),the Key R&D Program of Shandong Province,China(Grant No.2022CXPT048),and the Research Contract"Comprehensive Eval-uation and Prediction of Shale Oil Development Sweet Spots"(Contract No.30200018-19-ZC0613-0116).We acknowledge the Exploration and Development Research Institute of Shengli Oil-field Company,SINOPEC,for providing core samples,well-log data,and geological data for this study.Special thanks are extended to the editor and anonymous reviewers for their constructive com-ments and suggestions.
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