Comparison of Network Generation Techniques for Unconsolidated Porous Media

Abstract

First, we discuss network models and techniques for determining the pore-scale properties and characteris-While network models of porous materials have traditionally been tics; second, we describe the regular and random porous constructed using regular or disordered lattices, recent developments allow the direct modeling of more realistic structures such as sphere media systems used to validate and evaluate the techpackings, microtomographic images, or computer-simulated materi-niques we are proposing; third, we present the improveals. One of the obstacles in these newer approaches is the generation ments made to two network generation techniques of network structures that are physically representative of the real based on their known limitations; fourth, we validate systems. In this paper, we present and compare two different algothese algorithms using regular packings; and finally, we rithms to extract pore network parameters from three-dimensional evaluate and compare the network representations of images of unconsolidated porous media systems. The first approach, random packings generated by these techniques. which utilizes a pixelized image of the pore space, is an extension to unconsolidated systems of a medial-axis based approach (MA). The second approach uses a modified Delaunay tessellation (MDT) of the BACKGROUND grain locations. The two algorithms are validated using theoretical Early models developed to account for pore-scale packings with known properties and then the networks generated properties idealized the pore space as collections of from random packing are compared. For the regular packings, both capillary tubes and provided simple analytical solutions methods are able to provide the correct pore network structure, including the number, size, and location of inscribed pore bodies, the num-to predict continuum-scale properties such as permeber, size, and location of inscribed pore throats, and the connectivity. ability. However, these models failed to incorporate the Despite the good agreement for the regular packings, there were interconnectivity of the pore space. Thus the idea of differences in both the spatial mapping and statistical distributions in representing the pore space as a two-or three-dimennetwork properties for the random packings. The discrepancies are sional network emerged from the pioneering work by attributed to the pixelization at low resolution, non-uniqueness of the Fatt (1956a,b,c). Due to the complexity of the poreinscribed pore-body locations, and differences in merging processes space morphology, the pore bodies and throats are usuused in the algorithms, and serve to highlight the difficulty in creating ally represented by simplified shapes. Pore bodies have a unique network from a complex, continuum pore space.

Constriction size distributions of granular filters: a numerical study

“…Here, an extensive set of CSDs was calculated from data of 28 DEM simulations of varying coefficient of uniformity up to Cu = 6, PSD shape and relative density, using the numerical weighted Delaunay method proposed by Al-Raoush et al (2003) and Reboul (2008). The user-defined merging overlap parameter used to join adjacent Delaunay tetrahedra was varied from 0% to 100%.…”

“…In order to avoid over-segmentation of the void space, adjacent tetrahedra were merged using a criterion proposed by Al-Raoush et al (2003) and Reboul et al (2008). This can be explained by reference to a simple two-dimensional analogy of uniform particles on a square grid, as illustrated in Fig.…”

Modeling of Permeability of Porous Media With Mixed Wettabilities Based on Noncircular Capillaries

“…The virtual porous medium is computed by the discrete element method with grains falling freely (Fig. 4 (a)), and a pore-network is extracted from the computed porous medium with the modified Delaunay tessellation method proposed by AlRaoush et al [13] (Fig. 4 (b)).…”

Modeling of Fluid Intrusion Into Porous Media With Mixed Wettabilities Using Pore-Network

“…In this study, the modified Delaunaytessellation approach proposed by Al-Raoush et al [11] is employed to generate pore-networks. Delaunay tessellation is a widely used spatial segmentation method for generation of computational meshes used in numerical simulations.…”

“…But real porous media have more irregular structures regarding the coordinate number, pore size, and bond length. And so, several network extraction methods from pixelated images of pores and grains by X-ray tomography or a randomly packed spheres that are simulated by numerical models such as the discrete element method (DEM) have been developed [11], [12].…”