Full text loading...
-
Combining Genetic Algorithms, Gibbs Sampler, and Gradient-based Inversion to Estimate Uncertainty in 2D FWI
- Publisher: European Association of Geoscientists & Engineers
- Source: Conference Proceedings, 78th EAGE Conference and Exhibition 2016, May 2016, Volume 2016, p.1 - 5
Abstract
Generally, the local full-waveform inversion (LFWI) is solved in a deterministic framework, in which a single solution is produced, without quantifying its uncertainties. We propose a multi-step strategy for uncertainty estimation in FWI and we demonstrate its applicability to the acoustic 2D Marmousi model. To cast the LFWI in a probabilistic framework, we use a genetic algorithm driven optimization, combined with a Markov chain Monte Carlo method (Gibbs sampler). The so derived posterior probability distribution (PPD) defines a possible set of starting models for subsequent LFWI which, in turn, transforms the initial set of starting models in a new set of final models exhibiting narrower PPDs and containing the true model.