WISE: full-Waveform variational Inference via Subsurface Extensions
- URL: http://arxiv.org/abs/2401.06230v1
- Date: Mon, 11 Dec 2023 00:58:33 GMT
- Title: WISE: full-Waveform variational Inference via Subsurface Extensions
- Authors: Ziyi Yin and Rafael Orozco and Mathias Louboutin and Felix J. Herrmann
- Abstract summary: We introduce a probabilistic technique for full-waveform inversion, employing variational inference and conditional normalizing flows.
Our approach integrates generative artificial intelligence with physics-informed common-image gathers, reducing reliance on accurate initial velocity models.
- Score: 1.4747234049753455
- License: http://creativecommons.org/licenses/by/4.0/
- 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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