Analyzing reservoir and overburden impacts on seismic and electromagnetic responses and the applicability of seismic/EM methods in deep water reservoir characterization Zhangshuan Hou, Department of Geology, University at Buffalo, SUNY This study evaluates the sensitivity of seismic and electromagnetic (EM) responses to hydrocarbon reservoir and overburden attributes. We found that: EM calculations are sensitive to several factors both in the reservoir and the overburden. Outside the reservoir, EM responses are most sensitive to seawater electrical conductivity, seawater depth and overburden sediment thickness. While among the parameters/properties in the reservoir, EM responses are most sensitive to gas saturations. Seismic data show strong responses to reservoir parameters, most notably to reservoir porosity. Regression analyses using generalized linear models can be used to provide a rank of the important factors affecting the seismic/EM responses, and therefore provide guidance on inverse modeling setup. Minimum Relative Entropy-based Bayesian stochastic inversion results suggest that estimations of reservoir parameters using high dimensional models can be rather difficult to do with great confidence. The more prior information available on the overburden unknowns, the closer the posterior estimation of the reservoir parameters will be to the actual values. Seismic methods are effective in estimating reservoir porosity, while EM has the potential for estimating reservoir saturations. The integration of both has the potential to accurately estimate reservoir parameters. Informative prior knowledge about the field site, efficient sampling techniques, reduction of the parameter space, and computing capability are all necessary components for successful geophysical characterization of a petroleum reservoir, given the high dimensionality and non-uniqueness of the inverse problem. We applied different techniques to address each of these issues. Field site cross-section Modeling domain Posterior estimates of 20 controlled parameters using Seismic/EM joint inversion Inversion flow chart