Publication Name: AEGC 2021
Authors: Daniel Blatter, Anandaroop Ray, Kerry Key
Date Published: September 2021
Number of Pages: 3
Abstract:
Bayesian inversion of Magnetotelluric (MT) data produces crucial uncertainty information on inferred subsurface resistivity. Due to their high computational cost, however, Bayesian inverse methods have largely been restricted to 1D resistivity models. We successfully demonstrate a nonlinear 2D, trans-dimensional Bayesian inversion of MT data.