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Deep Learning for Seismic Inverse Problems: Toward the Acceleration of Geophysical Analysis Workflows

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sword-2021-12-09T19:15:49.original.xml (130 B)
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Author(s)
Adler, A
•
Araya-Polo, M
•
Poggio, T
Date Issued
March 1, 2021
Journal
IEEE Signal Processing Magazine
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
Adler, A, Araya-Polo, M and Poggio, T. 2021. "Deep Learning for Seismic Inverse Problems: Toward the Acceleration of Geophysical Analysis Workflows." IEEE Signal Processing Magazine, 38 (2).
Version
Author's final manuscript
Abstract
© 1991-2012 IEEE. Seismic inversion is a fundamental tool in geophysical analysis, providing a window into Earth. In particular, it enables the reconstruction of large-scale subsurface Earth models for hydrocarbon exploration, mining, earthquake analysis, shallow hazard assessment, and other geophysical tasks.
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Creative Commons Attribution-Noncommercial-Share Alike
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DOI of Published Version
10.1109/MSP.2020.3037429
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