Network models that represent the void space of a rock by a lattice of pores connected by throats can predict relative permeability once the pore geometry and wettability are known. Micro-computerized-tomography scanning provides a three-dimensional image of the pore space. However, these images cannot be directly input into network models. In this paper a modified maximal ball algorithm, extending the work of Silin and Patzek [D. Silin and T. Patzek, Physica A 371, 336 (2006)], is developed to extract simplified networks of pores and throats with parametrized geometry and interconnectivity from images of the pore space. The parameters of the pore networks, such as coordination number, and pore and throat size distributions are computed and compared to benchmark data from networks extracted by other methods, experimental data, and direct computation of permeability and formation factor on the underlying images. Good agreement is reached in most cases allowing networks derived from a wide variety of rock types to be used for predictive modeling.

Pore-network extraction from micro-computerized-tomography images

In the last 3 years there has been a huge increase in the use of pore-scale modeling to study multiphase flow and transport in porous media. Starting from single pore models of fluid arrangements, computations of relative permeability, interfacial area, dissolution rate and many other physical properties have been made. Combined with a realistic description of the pore space, predictive modeling of a variety of processes, including waterflood relative permeability and mass transfer coefficients, is now possible. This review highlights some of the major advances, with an emphasis on models of wettability and three-phase flow.

Flow in porous media — pore-network models and multiphase flow

Detailed physics, predictive capabilities and macroscopic consequences for pore-network models of multiphase flow.

A new robust algorithm analyzing the geometry and connectivity of the pore space of sedimentary rock is based on fundamental concepts of mathematical morphology. The algorithm distinguishes between the “pore bodies” and “pore throats,” and establishes their respective volumes and connectivity. The proposed algorithm also produces a stick-and-ball diagram of the rock pore space. The tests on a pack of equal spheres, for which the results are verifiable, confirm its stability. The impact of image resolution on the algorithm output is investigated on the images of computer-generated pore space. One of distinctive features of our approach is that no image thinning is applied. Instead, the information about the skeleton is stored through the maximal inscribed balls or spheres (MIS) associated with each voxel. These maximal balls retain information about the entire pore space. Comparison with the results obtained by a thinning procedure preserving some topological properties of the pore space shows that our method produces more realistic estimates of the number and shapes of pore bodies and pore throats, and the pore coordination numbers. The distribution of maximal inscribed spheres makes possible simulation of mercury injection and computation of the corresponding dimensionless capillary pressure curve. It turns out that the calculated capillary pressure curve is a robust descriptor of the pore space geometry and, in particular, can be used to determine the quality of computer-based rock reconstruction.

Pore space morphology analysis using maximal inscribed spheres

https://www.research.manchester.ac.uk/portal/files/37188690/CONHYD_3228_accepted.pdf

Z.R. Liang

Papers

A reconstruction technique for three-dimensional porous media using image analysis and Fourier transforms

Prediction of Permeability from the Skeleton of Three-Dimensional Pore Structure

Modelling two-phase equilibrium in three-dimensional porous microstructures

Prediction of Permeability from the Skeleton of 3-D Pore Structure