Uncertainty analysis for the integration of seismic and controlled source electro-magnetic data

We study the appraisal problem for the joint inversion of seismic and controlled source electro-magnetic (CSEM) data and utilize rock-physics models to integrate these two disparate data sets. The appraisal problem is solved by adopting a Bayesian model and we incorporate four representative sources of uncertainty. These are uncertainties in 1) seismic wave velocity, 2) electric conductivity, 3) seismic data and 4) CSEM data. The uncertainties in porosity and water saturation are quantified by a posterior random sampling in the model space of porosity and water saturation in a marine one-dimensional structure. We study the relative contributions from the four individual sources of uncertainty by performing several statistical experiments. The uncertainties in the seismic wave velocity and electric conductivity play a more significant role on the variation of posterior uncertainty than do the seismic and CSEM data noise. The numerical simulations also show that the uncertainty in porosity is most affected by the uncertainty in the seismic wave velocity and that the uncertainty in water saturation is most influenced by the uncertainty in electric conductivity. The framework of the uncertainty analysis presented in this study can be utilized to effectively reduce the uncertainty of the porosity and water saturation derived from the integration of seismic and CSEM data.