The Quadratic Wasserstein Metric With Squaring Scaling For Seismic Velocity Inversion

TL;DR

This paper explores the use of the quadratic Wasserstein metric with squaring scaling for seismic velocity inversion, addressing issues of convexity and data suitability, and demonstrates its effectiveness through numerical experiments.

Contribution

It introduces a new combined approach using squaring scaling and the quadratic Wasserstein metric for seismic velocity inversion, improving accuracy and efficiency.

Findings

The method enhances inversion accuracy.

It effectively handles data noise and shift issues.

Numerical experiments validate its efficiency.

Abstract

The quadratic Wasserstein metric has shown its power in measuring the difference between probability densities, which benefits optimization objective function with better convexity and is insensitive to data noise. Nevertheless, it is always an important question to make the seismic signals suitable for comparison using the quadratic Wasserstein metric. The squaring scaling is worth exploring since it guarantees the convexity caused by data shift. However, as mentioned in [Commun. Inf. Syst., 2019, 19:95-145], the squaring scaling may lose uniqueness and result in more local minima to the misfit function. In our previous work [J. Comput. Phys., 2018, 373:188-209], the quadratic Wasserstein metric with squaring scaling was successfully applied to the earthquake location problem. But it only discussed the inverse problem with few degrees of freedom. In this work, we will present a more in-depth study on the combination of squaring scaling technique and the quadratic Wasserstein metric. By discarding some inapplicable data, picking seismic phases, and developing a new normalization method, we successfully invert the seismic velocity structure based on the squaring scaling technique and the quadratic Wasserstein metric. The numerical experiments suggest that this newly proposed method is an efficient approach to obtain more accurate inversion results.