Self-Supervised Deep Learning for Nonlinear Seismic Full Waveform Inversion-Reference-Cited by-同舟云学术

Self-Supervised Deep Learning for Nonlinear Seismic Full Waveform Inversion

Published:2022 Issue: Volume:60 Page:1-18
ISSN:0196-2892
Container-title:IEEE Transactions on Geoscience and Remote Sensing
language:
Short-container-title:IEEE Trans. Geosci. Remote Sensing

Author:

Gao Zhaoqi¹^ORCID,Yang Wei¹,Li Chuang¹^ORCID,Li Feipeng¹^ORCID,Wang Qingzhen²,Ding Jicai²,Gao Jinghuai¹^ORCID,Xu Zongben³

Affiliation:

1. School of Information and Communications Engineering and the National Engineering Laboratory for Offshore Oil Exploration, Xi’an Jiaotong University, Xi’an, Shaanxi, China

2. CNOOC Research Institute Ltd., Beijing, China

3. School of Mathematics and Statistics, Xi’an Jiaotong University, Xi’an, Shaanxi, China

Funder

National Key Research and Development Program of the Ministry of Science and Technology of China

Fundamental Research Funds for the Central Universities

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Earth and Planetary Sciences,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/36/9633014/09775158.pdf?arnumber=9775158

Reference34 articles.

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4. A review of the adjoint-state method for computing the gradient of a functional with geophysical applications

5. Passive-source multitaper-spectral method based low-frequency data reconstruction for active seismic sources

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