Permeability upscaling in complex carbonate samples using textures of micro-computed tomography images

Abstract

ABSTRACT Developing a better characterization of fluid flow properties in carbonate reservoirs is a critical step for enhanced oil recovery applications in the oil industry. Indeed, carbonate reservoirs rocks are in general highly heterogeneous with variability revealed from submicron to centimeters. In several studies, Digital Rock Physics (DRP) was implemented as a technique which aims to help characterizing rock properties behavior at pore scale. This approach uses 3D X-ray micro tomography images to characterize pore network and also simulate rock properties from these images. Even though DRP is able to predict realistic rock properties in sandstone reservoirs it is still suffering from a lack of clear workflow in carbonate rocks. The main challenge is the upscaling of simulated properties from fine to coarse. In this paper, we propose a new upscaling method to characterize absolute permeability in carbonate core plugs samples using textures of Micro-Computed Tomography images. We propose to classify 3D micro-CT images of rock samples in terms of textures and predict the overall rock permeability. Finally, we discuss the advantages and limitations of this new approach. Overall the present work proposes an efficient and faster alternative DRP workflow for upscaling from pore-scale to core-scale.