Starting from a grayscale microCT scan of a reservoir rock sample,we applied image processing techniques to extract the geometry of the porous network and performed a morphological analysis on it.Morphological figures-of-merit such as surface-to-volume ratio and fractal dimension were obtained for several rock samples and the distinction between isolated and connected porosity was achieved through the application of such computational algorithms.It was shown that those figures-of-merit are strongly affected by image noise,resolution and segmentation scheme.By combining those geometrical and morphological features with fluid flow simulations at the microscale,we can provide insights on the effect of the fluid-rock interaction on the flow properties.This work is part of a larger research agenda,that entails building a multi-scale Enhanced Oil Recovery(EOR)simulation platform that captures the physics of nanoscale rock-fluid and fluid-fluid interactions and propagates its dominant characteristics beyond the mesoscale,so that it can be used as a testbed for screening and tailoring EOR additives.