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  2. 地质与地球物理研究所
  3. 中国科学院地质与地球物理研究所
  4. 中国科学院油气资源研究重点实验室
A seismic random noise suppression method based on self-supervised deep learning and transfer learning

文献类型：期刊论文

作者Wu, Tianqi1,2; Meng, Xiaohong2; Liu, Hong1; Li, Wenda1
刊名ACTA GEOPHYSICA
出版日期2023-06-08
页码17
ISSN号1895-6572
关键词Seismic random noise Deep learning Self-supervised learning Transfer learning
DOI10.1007/s11600-023-01105-5
英文摘要Random noise suppression is an essential task in the seismic data processing. In recent years deep learning methods have achieved superior results in seismic data denoising. However, obtaining clean data from field seismic data for training is challenging. Therefore, supervised deep learning denoising methods can only use synthetic datasets or field datasets constructed by conventional seismic denoising methods for training. Aiming at this problem, we proposed a self-supervised deep learning seismic denoising method based on Neighbor2Neighbor. This method only requires sampling the noisy data twice to train the denoising network without clean data. For the characteristics of seismic data, we designed a vertical neighbor subsample to make Neighbor2Neighbor more suitable for seismic data. In addition, to further improve the denoising effect in field data, we introduced a transfer learning strategy in our method. Numerical experiments demonstrated that our method outperformed both the conventional denoising seismic method and the supervised learning seismic denoising method after transfer learning.
WOS关键词INTERPOLATION ; DOMAIN
资助项目National Natural Science Foundation of China[U20B2014] ; National Natural Science Foundation of China[41974161]
WOS研究方向Geochemistry & Geophysics
语种英语
出版者SPRINGER INT PUBL AG
WOS记录号WOS:001003136700001
资助机构National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China
源URL[http://ir.iggcas.ac.cn/handle/132A11/110984]  
专题地质与地球物理研究所_中国科学院油气资源研究重点实验室
通讯作者Meng, Xiaohong
作者单位1.Chinese Acad Sci, Inst Geol & Geophys, Key Lab Petr Resources Res, Beijing 100029, Peoples R China
2.China Univ Geosci, Sch Geophys & Informat Engn, Beijing 100083, Peoples R China
推荐引用方式
GB/T 7714		 Wu, Tianqi,Meng, Xiaohong,Liu, Hong,et al. A seismic random noise suppression method based on self-supervised deep learning and transfer learning[J]. ACTA GEOPHYSICA,2023:17.
APA Wu, Tianqi,Meng, Xiaohong,Liu, Hong,&Li, Wenda.(2023).A seismic random noise suppression method based on self-supervised deep learning and transfer learning.ACTA GEOPHYSICA,17.
MLA Wu, Tianqi,et al."A seismic random noise suppression method based on self-supervised deep learning and transfer learning".ACTA GEOPHYSICA (2023):17.

入库方式： OAI收割

来源：地质与地球物理研究所

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