Inversion of controlled-source electromagnetic data using a model-based approach

摘要

A two-and-half dimensional model-based inversion algorithm for the reconstruction of geometry and conductivity of unknown regions using marine controlled-source electromagnetic (CSEM) data is presented. In the model-based inversion, the inversion domain is described by the so-called regional conductivity model and both geometry and material parameters associated with this model are reconstructed in the inversion process. This 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 priori derived from a pixel-based inversion method. By incorporating this a priori information, the number of unknown parameters to be retrieved becomes significantly reduced. The inversion method is 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. The model-based inversion method is validated by using several numerical examples including the inversion of the Troll field data. These results show that the model-based inversion method can quantitatively reconstruct the shapes and conductivities of reservoirs.