Table of Contents
Algorithms, Volume 13, Issue 6 (June 2020) – 24 articles
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Cover Story (view full-size image) Geophysical inversion can estimate the spatial distributions of physical subsurface properties, [...] Read more. Geophysical inversion can estimate the spatial distributions of physical subsurface properties, such as electrical conductivity (EC), from non-invasive surface measurements. The geophysical inverse problem is virtually always ill-posed and the resulting subsurface models of the physical property are non-unique. To reduce non-uniqueness, it is beneficial to consider multiple measurements simultaneously in so-called joint inversions. Using vertical electrical sounding and frequency-domain electromagnetic data, the uncertainty of an EC subsurface model can be quantified using Bayesian inversion. We demonstrate the Kalman ensemble generator for Bayesian joint inversion. The Kalman ensemble generator provides an efficient alternative to standard Markov chain Monte Carlo approaches. View this paper