Joint inversion for Vp, Vp/Vs of the San Fransico Bay Area using ADTomo

TL;DR

This paper introduces a novel joint inversion method combining fast sweeping and deep learning for seismic tomography in the San Francisco Bay Area, yielding more accurate and higher-resolution P wave and S wave velocity models.

Contribution

It develops a new joint inversion approach that improves velocity ratio accuracy and resolution using advanced phase picking and optimization techniques.

Findings

More reliable P wave to S wave velocity ratio obtained

Higher resolution P wave velocity models achieved

Velocity anomalies align with geological maps

Abstract

This article presents a new seismological tomography method based on the fast sweeping method and advanced seismic phase picking techniques to study the complex geological structures of the San Francisco Bay Area. By calculating the eikonal equation using the fast-sweeping method, this study obtains travel time information and gradient data under a given velocity structure. With an automatic differentiation algorithm to calculate gradients of the loss function and the L-BFGS algorithm to achieve optimization, the velocity model is iteratively adjusted to minimize the loss function. The P wave to S wave velocity ratio obtained through joint inversion is more reliable than the velocity ratio obtained directly by dividing the P wave and S wave velocity models. Compared to traditional inversion, the velocity ratio here does not require the same P wave and S wave travel path, thus improving the accuracy of the velocity ratio. The method was applied to the San Francisco Bay Area, a region with complex geological structures and significant seismic activities. This region, a focal point of research interest, also provides abundant seismic data for this study. We use deep learning methods to automatically pick seismic phases, acquiring abundant P wave and S wave travel time information. This project obtains the S wave velocity structure and P wave to S wave velocity ratio results for the first time. Compared to previous inversion results, the P wave velocity model here demonstrates higher resolution and better geological correspondence. High and low velocity anomalies also align well with geological maps, providing reasonable explanations in terms of lithology.