oa Reservoir Property Estimation in Carbonates

We present some key challenges in rock and fluid property prediction in carbonates. Most traditional rock physics models have been developed for siliciclastic rocks. Carbonates, which have a completely different mineralogy, pore structure and geometry, pose new challenges to us. We look into the applicability of traditional rock physics models on carbonate reservoirs. We analyze the effect of porosity, mineralogy, clay content, and fluids on the bulk and shear stiffness of carbonate rocks in a middle-eastern deep reservoir, composed predominantly of limestone with varying proportions of anhydrite, dolomite, and clay. We also analyze the effect of in-situ stresses on the elastic properties, with particular emphasis on pore-pressure. We demonstrate the ability to model the elastic properties (bulk and shear moduli) as functions of mineralogy, clay content, porosity, and pore-pressure. We use a stochastic rock physics framework to build a probabilistic forward model, based on and calibrated to well-log and drilling data. Using the joint probability distribution functions, we use a Bayesian inversion technique to estimate reservoir properties (porosity, clay content, and pore-pressure) from seismic inversion data (acoustic impedance, shear impedance, and density) along with the associated uncertainties.