Petrophysical properties prediction of deep dolomite reservoir considering pore structure

Prediction of petrophysical properties of deep dolomite reservoir using elastic parameter data is challenging and of great uncertainty. Changes in the petrophysical properties generally induce perturbations in elastic properties. Rock-physics model, which plays a role as a bridge between petrophysical properties and elastic properties, determines the accuracy of inversion for petrophysical properties using elastic properties. Different pore structures lead to variations of rock-physics relationships, and in dolomite reservoir, the influence of pore structure on elastic properties is larger than that of petrophysical properties. We first propose a statistical rock-physics model, in which we consider the effect of pore structure on the nonlinear rock-physical relationship between petrophysical properties and elastic properties of dolomite reservoirs. Then, we propose a Bayesian inversion approach of using elastic properties to predict petrophysical properties and use weight factors to address the difference in accuracy of the input elastic properties in the Bayesian inversion framework. Examples illustrate the proposed approach may produce petrophysical properties of high accuracy for deep dolomite reservoirs.