Uncertainty quantification using Bayesian inversion applied to the DC resistivity problem

Autor: Backes, K., Börner, R., Scheunert, M., Sprungk, B., Ernst, O., Spitzer, K.
Jazyk: angličtina
Rok vydání: 2022
Zdroj: Protokoll über das 29. Schmucker-Weidelt-Kolloquium für Elektromagnetische Tiefenforschung: virtuell, 29. September-1. Oktober 2021
Popis: A geophysical investigation of a subsurface is an ambiguous endeavor. In the geoelectrical field inversion results are inconclusive because of the equivalence principle. Thus, results need to be quantified and reviewed. One way to verify an inversion outcome is by quantifying uncertainties, that arise from imperfect input data. The Bayesian approach considers every parameter as a random number descripted by a probability distribution. Therefore, the outcome of the Bayesian inversion is not just one model, but a variety of possible models. This work emphasizes the benefits of multiple model outcomes and strives to examine given data more extensively.
Databáze: OpenAIRE