Irregularly seismic data interpolation based on deep learning with integrated channel-spatial attention mechanismOA
Irregularly seismic data interpolation based on deep learning with integrated channel-spatial attention mechanism
Chao Ma;Jian-Ping Huang;Zi-Xuan Qiao;San-Fu Li;Wen-Sheng Duan;Gang-Lin Lei
State Key Laboratory of Deep Oil and Gas,School of Geosciences,China University of Petroleum(East China),Qingdao,266580,Shandong,ChinaState Key Laboratory of Deep Oil and Gas,School of Geosciences,China University of Petroleum(East China),Qingdao,266580,Shandong,ChinaState Key Laboratory of Deep Oil and Gas,School of Geosciences,China University of Petroleum(East China),Qingdao,266580,Shandong,ChinaInstitute of Geophysical Exploration,Geophysical-China Oilfield Services Limit,Zhanjiang,524057,Guangdong,ChinaTarim Oilfield Branch,CNPC,Korla,841000,Xinjiang,ChinaTarim Oilfield Branch,CNPC,Korla,841000,Xinjiang,China
Seismic dataDeep learningIrregular samplingChannel-spatial attention mechanismInterpolation
Seismic dataDeep learningIrregular samplingChannel-spatial attention mechanismInterpolation
《石油科学（英文版）》 2026 (3)
1182-1196,15
We thank four anonymous reviewers and editor Meng-Jiao Zhou for their comments that helped us to improve the manuscript.This study is supported by the National Natural Science Foundation of China(Grant No.42374164),the High Precision Imaging Study of Small-scale and High-angle Structures in the Western Ordos Basin(Grant No.2024D2ZZ01),the Imaging Study of Q Least Squares Migration(Grant No.671024115010),the Research on Image Deconvolution Technology Based on Regularization(Grant No.202418018212),the Research on the masked autoencoder method based on vit Network(Grant No.30200020-24-ZC0613-0044)and the Taishan Scholars Research Program of Shandong Province.
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