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arXiv · 2603.16393

Robust Physics-Guided Diffusion for Full-Waveform Inversion

Jishen Peng·Enze Jiang·Zheng Ma·Xiongbin Yan
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Abstract

We develop a robust physics-guided diffusion framework for full-waveform inversion that combines a score-based generative prior with likelihood guidance computed through wave-equation simulations. We adopt a transport-based data-consistency potential (Wasserstein-2), incorporating wavefield enhancement via bounded weighting and observation-dependent normalization, thereby improving robustness to amplitude imbalance and time/phase misalignment. On the inference side, we introduce a preconditioned guided reverse-diffusion scheme that adapts the guidance strength and spatial scaling throughout the reverse-time dynamics, yielding a more stable and effective data-consistency guidance step than standard diffusion posterior sampling (DPS). Numerical experiments on OpenFWI datasets demonstrate improved reconstruction quality over deterministic optimization baselines and standard DPS under comparable computational budgets.

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BibTeXRIS

Jishen Peng, Enze Jiang, Zheng Ma, Xiongbin Yan. 2026-03-17. Robust Physics-Guided Diffusion for Full-Waveform Inversion. https://arxiv.org/abs/2603.16393

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