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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