Selecting velocity models using Bayesian Information Criterion

TL;DR

This paper introduces a Bayesian Information Criterion-based method for selecting elasticity parameters in seismic models by optimizing signal trajectories and media parameters to fit observed data.

Contribution

It proposes a novel two-step optimization strategy using BIC for better elasticity parameter selection in seismic modeling.

Findings

Effective in matching seismic data with multilayered models.

Provides a systematic approach for velocity model selection.

Improves accuracy of seismic parameter estimation.

Abstract

We present a strategy for selecting the values of elasticity parameters by comparing walk-away vertical seismic profiling data with a multilayered model in the context of Bayesian Information Criterion. We consider $P$-wave traveltimes and assume elliptical velocity dependence. The Bayesian Information Criterion approach requires two steps of optimization. In the first step, we find the signal trajectory and, in the second step, we find media parameters by minimizing the misfit between the model and data.