SPATIAL STATISTICAL ANALYSIS OF THE POROUS MEDIUM EXTRACTED FROM VIRTUAL PACKED GRAINS WITH RANDOM SIZES

Abstract

ABSTRACT: Hydraulic properties such as water retention properties and permeability, which are macro characteristics of porous media, are determined in a bottom-up manner by pore properties including pore shape, pore-size distribution, and pore connectivity. Hydraulic properties could be reproduced from local physical phenomena such as capillarity in the pores using a pore-network model. Spatial distribution of pores could affect these hydraulic properties. In this research, global and local Moran’s indexes, which are spatial statistics, are used to analyze the spatial distribution of pores in porous media packed with both single-size and various-size grains, to find the global spatial autocorrelation in the pore distribution. The obtained results show that regardless of the grain-size distribution, almost all the global Moran’s indexes are just below 0.5, which indicates there are some clusters with respect to the pore-size distribution. From the local Moran’s indexes, it was found that the numbers of significant PBs in HH category at the 5% statistically significant level are obviously higher than LH, LL and HL regions, which indicates that large PBs tend to distribute around large PBs. All of these imply that hydraulic properties of porous media could be affected by the spatial structure of pores.