A Two-and-Half-Dimensional Model-Based Inversion Algorithm for the Controlled- Source Electromagnetic Data

Abstract

Abstract The model-based inversion method for the reconstruction of geometry and conductivity of unknown regions or bodies using marine controlled-source electromagnetic (CSEM) data is presented. The method has the advantage of using a priori information such as the background conductivity distribution, structural information extracted from seismic and/or gravity measurements, and/or inversion results a priorily derived from a pixel-based inversion method. By incorporating this a priori information, the number of unknown parameters to be retrieved becomes significantly reduced. In this paper, we develop the model-based inversion method by adopting the regularized Gauss-Newton minimization scheme. The robustness of the inversion is enhanced by adopting nonlinear constraints and applying a quadratic line search algorithm to the optimization process. We also introduce the adjoint formulation to calculate the Jacobian matrix with respect to the geometrical parameters. We compare the inversion results obtained by the model-based inversion method with those obtained from the pixel-based inversion method.