Efficient 2D Bayesian Inversion of Borehole Resistivity Measurements

Assessment of uncertainty of borehole resistivity measurements is important to quantify the accuracy of hydrocarbon reserves and production forecasts. We develop an efficient Bayesian inversion method for the quantitative interpretation of general borehole resistivity measurements. It enables the estimation of resistivity properties together with their uncertainties in conjunction with arbitrary sets of a priori, information about the measurements and/or the unknowns. The inversion method can process either raw voltage measurements (raw electrical conductivities) or apparent resistivities acquired with induction or laterolog instruments. Two field cases of application verify the accuracy and stability of the new Bayesian inversion method.