Experimental Validation of Pore-Level Calculations of Static and Dynamic Petrophysical Properties of Clastic Rocks

Abstract

Abstract We present an integrated approach to calculate fundamental macroscopic static and dynamic properties of porous media, including absolute permeability, formation factor, relative permeability, capillary pressure, and resistivity index. The calculations are based on high-resolution three-dimensional (3D) digital images of actual clastic rocks acquired with X-ray computed tomography (CT). Pore-level simulations of single-phase fluid flow and electrical conduction are performed using the lattice-Boltzmann method and diffusion random walks, respectively. Two-phase immiscible fluids are geometrically distributed into the pore space of the synthetic rock using a simple percolation algorithm while enforcing capillary equilibrium. These simulations serve to calculate effective medium properties of macroscopic rock behavior that can be used to improve both the interpretation of well-log measurements and the prediction of multiphase flow properties. To test and validate our pore-scale model, we consider three micro-CT images of quartzose sandstones with different petrophysical properties to perform both laboratory measurements and pore-level calculations. The calculated permeability is in good agreement with the corresponding laboratory measurements for clean sands, while it differs for the shaly-sand sample. For both cases, the computed formation factor is consistent with laboratory measurements. For the case of two-phase simulations of water-wet conditions, the derived capillary pressure, relative permeability and resistivity index closely agree with experimental measurements when immovable fluid saturations of oil and water are taken into account. Our simulations show that calculations performed on a small rock sample may not always be representative of heterogeneous rock formations. We also find that the amount of clay-bound water should be accounted for in pore-level petrophysical studies, especially for rocks containing a significant amount of clay minerals. Higher image resolution than available is needed to accurately quantify macroscopic petrophysical properties of such complex rock samples.