Primary Drainage Relative Permeability in Hydrocarbon Reservoirs Interpreted Using Digital Rock Physics

摘要

We apply multi-scale interrogation of complex carbonate reservoir rocks from whole core – plug – micro – nano scale,and then work backwards to upscale and integrate the properties to an acceptable 3D representation. This is achieved through imaging at different resolutions: for each image an equivalent network model is constructed. The smaller-scale networks are upscaled to generate effective properties for input into a plug-scale network representation of the rock. We study 54 samples from three reservoir zones of a Lower Cretaceous reservoir. Using the Dunham rock classification scheme we see a range of rock types from grainstone to mudstone-dominated. For primary drainage,the higher quality grain-dominated samples show better connectivity and a higher oil relative permeability than the poorer quality rocks. However,for waterflooding the situation is reversed: the better quality rocks tend to be more oil-wet,with a large water relative permeability which leads to early breakthrough and a poor local displacement efficiency. In contrast,the mudstones are mixed-wet and more poorly connected,which impedes the movement of water,leading to a more favourable local recovery. This study demonstrates how employing the state-of-the-art in multi-scale imaging and modeling,the behavior of complex carbonates can be quantified and interpreted,allowing an assessment of recovery based on pore structure and facies type.