Bayesian inversion with Markov chains—II. The one-dimensional DC multilayer case |
| |
Authors: | Jean-Jacques Schott,Michel Roussignol,Michel Menvielle,& Flavien R. Nomenjahanary |
| |
Affiliation: | Ecole et Observatoire des Sciences de la Terre, 5, rue Descartes,;F-67084 Strasbourg Cedex, France, Equipe d'Analyse et de Mathématiques Appliquées, Universitéde Marne la Vallée, 5, Boulevard Descartes,;F-77454 Marne la Valée Cedex 2, France, CETP, 4 avenue de Neptune,;F-94107 Saint-Maur Cedex, France. E-mail: , UniversitéParis Sud, Bât. 504, F-91405 Orsay Cedex, France;, Geophysical Institute and Observatory, PO Box 3843, Antananarivo;(101), Madagascar |
| |
Abstract: | In this paper, we will report on the application of Bayesian inference to DC resistivity inversion for 1-D multilayer models. The posterior probability distribution is explored through a Markov process based upon a Gibbs's sampler. The process would lead to unrealistic estimates without additional prior information, which takes the form of a second Markov chain where the transition kernel corresponds to a smoothness constraint. The outcomes are posterior marginal probabilites for each parameter, as well as, if required, joint probabilities for pairs of parameters. We will discuss the main properties of the method in the light of a theoretical example and illustrate its capabilities with some field examples taken from various contexts. |
| |
Keywords: | electrical resistivity inversion layered media Monte Carlo Markov chain. |
|
|