Inner-Loop-Free Total-Variation-Constrained Full-Waveform Inversion

Abstract

This paper proposes a computationally efficient algorithm to address the Full-Waveform Inversion (FWI) problem with a Total Variation (TV) constraint, designed to accurately reconstruct subsurface properties from seismic signal. FWI, as an ill-posed inverse problem, requires effective regularizations or constraints to ensure accurate and stable solutions. Among these, the TV constraint is widely known as a powerful prior for modeling the piecewise smooth structure of subsurface properties. However, solving the optimization problem is challenging because of the nonlinear observation process combined with the non-smoothness of the TV constraint. Conventional methods rely on inner loops and/or approximations, which lead to high computational cost and/or inappropriate solutions. To address these limitations, we develop a novel algorithm based on a primal-dual splitting method, achieving computational efficiency by eliminating inner loops and ensuring high accuracy by avoiding approximations.We also demonstrate the effectiveness of the proposed method through experiments using the SEG/EAGE Salt Model. The source code will be available at https://www.mdi.comp.isct.ac.jp/publications/fwiwtv.

arXiv commentSubmitted to IEEE Signal Processing Letters. The source code is available at https://github.com/MDI-ScienceTokyo/Inner-Loop-Free_Total-Variation-Constrained_Full-Waveform_Inversion. The project page is https://www.mdi.comp.isct.ac.jp/publications/fwiwtv