Facies classification at the well location is generally based on sedimentological models, however, the extension of the classification of an individual well into the entire reservoir model is contingent on the calibration of a rock physics model that links rock and fluid properties with geophysical measurements such as seismic velocities and/or electromagnetic-derived resistivities. The goal of this work is to present a workflow to define a geologically consistent facies classification at the well location, to accurately reconstruct this classification using elastic and electrical properties, and to extend the classification to the 3D reservoir model. The initial classification at the well location is obtained using traditional statistical methods applied to computed rock properties such as mineralogical volumes, porosity, density and permeability. The facies reconstruction based on elastic/electrical properties is obtained using a Bayesian approach that combines rock physics with statistical models. The workflow is illustrated through the application to the Rock Springs Uplift field, Wyoming, which hosts several potential CO 2 storage reservoirs.