The Magnetotellurics Inversion with a Tree Based Bayesian Framework

Abstract

Bayesian inversion offers a valuable means of estimating uncertainty, allowing us to evaluate the impact of inversion. However, tackling Bayesian inversion in high-dimensional spaces remains a crucial area of research. Building upon Hawkins’ work, we have developed a tree-based Bayesian inversion scheme specifically designed to address the challenges posed by the magnetotellurics inversion problem. By employing the cdf9/7 wavelet as our basis function, we conducted a numerical simulation of a low-resistance abnormal body, yielding highly accurate inversion results.