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IntraSeismic: a coordinate-based learning approach to seismic inversion
Seismic imaging is the numerical process of creating a volumetric representation of the subsurface geological structures from elastic waves recorded at the surface of the Earth.
Posterior sampling with CNN-based, Plug-and-Play regularization with applications to Post-Stack Seismic Inversion
However, selecting appropriate prior information in a probabilistic inversion is crucial, yet non-trivial, as it influences the ability of a sampling-based inference in providing geological realism in the posterior samples.
A hybrid approach to seismic deblending: when physics meets self-supervision
Compressed sensing type regularization is then applied, where sparsity in some domain is assumed for the signal of interest.
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