Pore Shapes and Pore Geometry of Reservoir Rocks from μ-CT Imaging and Digital Image Analysis

Recent years have seen a growing interest in the characterization of the pore morphologies of reservoir rocks and how the spatial organization of pore geometry affects the macroscopic behaviour of rock-fluid systems. With the availability of highresolution 3D imaging, such as X-ray micro-computed tomography (μ-CT), the detailed quantification of particle shapes has been facilitated by progress in computer science. Here, we show how the shapes of irregular rock structures (pores) can be classified and quantified based on binary 3D images. The methodology requires the measurement of basic 3D particle descriptors (length, width and thickness) and a shape classification that involves the similarity of artificial objects, which is based on main pore network detachment and 3D sample size. A watershed algorithm was applied to preserve the pore morphology after separating the main pore networks, which is essential for the pore shape characterization. The results were validated for a variety of sandstones, either from distinct reservoirs or used as reference material for laboratory research. Furthermore, this study generalizes a practical way to correlate specific particle shapes, such as rods, blades, cuboids, plates and cubes, to characterize asymmetric particles of any material type with 3D image analysis. In this manuscript we would like to showcase results for a small variety of reservoir sandstones from the North German Basin area.