Gregory A. Newman

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We provide a framework for preconditioning nonlinear three-dimensional electromagnetic inverse scattering problems using nonlinear conjugate gradient (NLCG) and limited memory (LM) quasi-Newton methods. Key to our approach is the use of an approximate adjoint method that allows for an economical approximation of the Hessian that is updated at each inversion(More)
Accurately estimating reservoir parameters from geo-physical data is vitally important in hydrocarbon exploration and production. We have developed a new joint-inversion algorithm to estimate reservoir parameters directly, using both seismic amplitude variation with angle of incidence ͑AVA͒ data and marine controlled-source electromagnetic ͑CSEM͒ data.(More)
Large-scale controlled-source electromagnetic (CSEM) three-dimensional (3D) geophysical imaging is now receiving considerable attention for electrical-conductivity mapping of potential offshore oil and gas reservoirs. To cope with the typically large computational requirements of the 3D CSEM imaging problem, our strategies exploit computational parallelism(More)
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