Uncertainty-aware Frequency-domain Acoustic Full Waveform Inversion Using Gaussian Random Fields and Ensemble Kalman Inversion

Yunduo Li; Yijie Zhang; Xueyu Zhu; Jinghuai Gao

doi:10.48550/arxiv.2505.08335

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Uncertainty-aware Frequency-domain Acoustic Full Waveform Inversion Using Gaussian Random Fields and Ensemble Kalman Inversion

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Uncertainty-aware Frequency-domain Acoustic Full Waveform Inversion Using Gaussian Random Fields and Ensemble Kalman Inversion

Yunduo Li, Yijie Zhang, Xueyu Zhu and Jinghuai Gao

ArXiV.org

Cornell University

05/13/2025

DOI: 10.48550/arxiv.2505.08335

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https://doi.org/10.48550/arxiv.2505.08335View

Preprint (Author's original)This preprint has not been evaluated by subject experts through peer review. Preprints may undergo extensive changes and/or become peer-reviewed journal articles. Open Access

Abstract

In recent years, uncertainty-aware full waveform inversion (FWI) has received increasing attention, with a growing emphasis on producing informative uncertainty estimates alongside inversion results. Bayesian inference methods--particularly Monte Carlo-based approaches--have been widely employed to quantify uncertainty. However, these techniques often require extensive posterior sampling, resulting in high computational costs. To address this challenge and enable efficient uncertainty quantification in FWI, we introduce an uncertainty-aware FWI framework--EKI-GRFs-FWI--that integrates Gaussian random fields (GRFs) with the ensemble Kalman inversion (EKI) algorithm. This approach jointly infers subsurface velocity fields and provides reliable uncertainty estimates in a computationally efficient manner. The EKI algorithm leverages a derivative-free update mechanism and employs effective stopping criteria to ensure rapid convergence, making it suitable for large-scale inverse problems. Meanwhile, GRFs incorporate prior knowledge of spatial smoothness and correlation length scales, enabling the generation of physically plausible initial ensembles for EKI. Numerical results demonstrate that EKI-GRFs-FWI yields reasonably accurate velocity reconstructions while delivering informative uncertainty estimates.

Physics - Geophysics

Details

Title: Subtitle: Uncertainty-aware Frequency-domain Acoustic Full Waveform Inversion Using Gaussian Random Fields and Ensemble Kalman Inversion
Creators: Yunduo Li
Yijie Zhang
Xueyu Zhu
Jinghuai Gao
Resource Type: Preprint
Publication Details: ArXiV.org
DOI: 10.48550/arxiv.2505.08335
ISSN: 2331-8422
Publisher: Cornell University; Ithaca, New York
Language: English
Date posted: 05/13/2025
Academic Unit: Mathematics
Record Identifier: 9984822963502771

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