Study on the linkages between microstructure and permeability of porous media using pore network and BP neural network

In applying porous media air bearings (PMABs), designing the pore microstructure of porous media to obtain the desired permeability is challenging. The key parameters in this design are to map the pore microstructure characteristics to permeability and adapt to manufacturing process with the characteristics. For this purpose, a framework is proposed to characterize pore microstructure with morphology descriptor and predict permeability. 3D digital images of porous media are obtained using X-ray micro-computed tomography and various image construction techniques. The complex pore microstructure of porous media is represented with a pore network. Permeability is calculated based on the pore network. Sixteen pore microstructure morphology descriptors are initially calculated to characterize pore microstructure. A back-propagation neural network (BPNN) is built to learn the correlation between morphology descriptors and permeability. Pearson correlation coefficient (PCC) and feature importance scores of morphology descriptors are obtained based on the dataset and trained BPNN. The results demonstrate that the prediction performance of BPNN is excellent. The following six morphology descriptors (porosity, coordination number, average pore diameter, average throat diameter, average pore throat ratio, average throat length) are reserved to characterize pore microstructure. Finally, two types of pore microstructure are designed with the help of knowledge obtained by this research.

3D pore microstructures and computer simulation: Effective permeabilities and capillary pressure during drainage in Opalinus Clay

The 3D reconstruction of the pore space in Opalinus Clay is faced with the difficulty that high-resolution imaging methods reach their limits at the nanometer-sized pores in this material. Until now it has not been possible to image the whole pore space with pore sizes that span two orders of magnitude. Therefore, it has not been possible to predict the transport properties of this material with the help computer simulations that require 3D pore structures as input. Following the concept of self-similarity, a digital pore microstructure was constructed from a real but incomplete pore microstructure. The constructed pore structure has the same pore size spectrum as measured in the laboratory. Computer simulations were used to predict capillary pressure curves during drainage, which also agree with laboratory data. It is predicted, that two-phase transport properties such as the evolution of effective permeability as well as capillary pressures during drainage depend both on transport directions, which should be considered for Opalinus Clay when assessing its suitability as host rock for nuclear waste. This directional dependence is controlled on the pore scale by a geometric anisotropy in the pore space.