Physics-guided self-supervised learning for low frequency data prediction in FWI
Author:
Affiliation:
1. Advanced Geophysical Technology Inc.
2. University of Houston
Publisher
Society of Exploration Geophysicists
Link
https://library.seg.org/doi/pdf/10.1190/segam2020-3423396.1
Reference11 articles.
1. Fast Image Recovery Using Variable Splitting and Constrained Optimization
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4. Retrieving Low Wavenumber Information in FWI: An Overview of the Cycle-Skipping Phenomenon and Solutions
5. Hu, W., Y. Jin, X. Wu, and J. Chen, 2019a, A progressive deep transfer learning approach to cycle-skipping mitigation in FWI: 89th Annual International Meeting, SEG, Expanded Abstracts, 2348–2352, doi: 10.1190/segam2019-3216030.1.
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