A Bayesian inversion methodology for identification of large-scale subsurface
structures (strata) from controlled source electromagnetic data is developed. The Bayesian
inverse problem is solved by sampling from the posterior probability distribution, using the
ensemble Kalman filter. Prior knowledge is incorporated in the methodology by utilizing
structural prior information from, for example, interpreted seismic data. A model-based,
composite parametrization of the electric conductivity distribution is applied to represent