Title | Deep Learning for Seismic Inverse Problems: Toward the Acceleration of Geophysical Analysis Workflows |
Publication Type | Journal Article |
Year of Publication | 2021 |
Authors | Adler, A, Araya-Polo, M, Poggio, T |
Journal | IEEE Signal Processing Magazine |
Volume | 38 |
Issue | 2 |
Pagination | 89 - 119 |
Date Published | 03/2021 |
ISSN | 1053-5888 |
Abstract | 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. |
URL | https://ieeexplore.ieee.org/abstract/document/9363496 |
DOI | 10.1109/MSP.2020.3037429 |
Short Title | IEEE Signal Process. Mag. |
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