SEMINARIS DE LA FACULTAT DE GEOLOGIA I L'INSTITUT DE CIÈNCIES DE LA TERRA 'JAUME ALMERA'

Dr.Niklas Linde (Centre de Recherches en Environment Terrestre, Faculté des Géosciences et de l'environment, Université de Lausanne, França)

Hora: 12:00
Lloc: Sala d'actes de l'Institut de Ciències de la Terra Jaume Almera

Probabilistic inversion methods based on Markov chain Monte Carlo (MCMC) simulation are well suited to quantify parameter and model uncertainty of nonlinear inverse problems. Yet,
application of such methods to CPU-intensive forward models can be a daunting task, particularly if the parameter space is high dimensional. Here, we present a two-dimensional (2D) pixel-based MCMC inversion of plane-wave electromagnetic (EM) data. Using synthetic data, we investigate how model parameter uncertainty depends on model structure constraints using different norms of the likelihood function and the model constraints, and study the added benefits of joint inversion of EM and electrical resistivity tomography (ERT) data. Our results demonstrate that model structure constraints are a necessity to stabilize the MCMC inversion results of a highly-discretized model. These constraints decrease model parameter uncertainty and facilitate model interpretation.