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arXiv · 2401.06230

WISE: full-Waveform variational Inference via Subsurface Extensions

Ziyi Yin·Rafael Orozco·Mathias Louboutin·Felix J. Herrmann
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Abstract

We introduce a probabilistic technique for full-waveform inversion, employing variational inference and conditional normalizing flows to quantify uncertainty in migration-velocity models and its impact on imaging. Our approach integrates generative artificial intelligence with physics-informed common-image gathers, reducing reliance on accurate initial velocity models. Considered case studies demonstrate its efficacy producing realizations of migration-velocity models conditioned by the data. These models are used to quantify amplitude and positioning effects during subsequent imaging.

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BibTeXRIS

Ziyi Yin, Rafael Orozco, Mathias Louboutin, Felix J. Herrmann. 2023-12-11. WISE: full-Waveform variational Inference via Subsurface Extensions. https://doi.org/10.1190/geo2023-0744.1

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