Efficient and Accurate Full-Waveform Inversion with Total Variation Constraint

TL;DR

This paper introduces a fast, accurate algorithm for full-waveform inversion that incorporates a total variation constraint, improving subsurface property reconstruction from seismic data with reduced computational cost.

Contribution

It presents a novel primal-dual splitting algorithm for FWI with TV constraints, eliminating inner loops and approximations to enhance efficiency and accuracy.

Findings

Effective reconstruction of subsurface properties demonstrated on SEG/EAGE models.

Significant reduction in computational cost compared to conventional methods.

High accuracy in modeling piecewise smooth subsurface structures.

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 data. 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 and Overthrust Models. The source code will be available at https://www.mdi.c.titech.ac.jp/publications/fwiwtv.