Physics-Guided Data-Driven Seismic Inversion: Recent progress and future opportunities in full-waveform inversion
Author:
Affiliation:
1. Staff Scientist, Los Alamos National Laboratory, Los Alamos, NM, USA
2. Technical Staff, Los Alamos National Laboratory, Los Alamos, NM, USA
3. Theoretical Division, Los Alamos National Laboratory, Los Alamos, NM, USA
Funder
Los Alamos National Laboratory Laboratory-Directed Research and Development program
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Applied Mathematics,Electrical and Electronic Engineering,Signal Processing
Link
http://xplorestaging.ieee.org/ielx7/79/10004746/10004771.pdf?arnumber=10004771
Reference72 articles.
1. Deep Learning for Geophysics: Current and Future Trends
2. Seismic Inversion by Hybrid Machine Learning
3. Deep Learning Techniques for Inverse Problems in Imaging
4. Adaptive Feedback Convolutional‐Neural‐Network‐Based High‐Resolution Reflection‐Waveform Inversion
5. Physics-informed machine learning
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