Coupling of pipe network modelling and domain decomposition for flow in mineralised coal cores

Permeability of coal is highly dependent on the effective stress, which is found to decrease exponentially as effective stress increases. To study coal permeability at in-situ conditions, high pressure X-ray micro-CT imaging is performed. However, fractures are highly compressed at in-situ conditions, some of fracture apertures are below the resolution of images, which cannot be segmented properly for direct flow simulation. In this work, we utilise two sets of micro-CT images under ambient and high pressure conditions. The ambient micro-CT images are used to extract fracture pipe network model (FPNM), while the high-pressure greyscale images are used for measuring aperture sizes that are below image resolution. Minerals, which commonly occur in fractured coal samples, are additionally analysed and included in the FPNM. Domain decomposition is also applied during the construction of FPNM, to enhance the capability and efficiency of model extraction. It is found that domain decomposition can greatly reduce the computational cost while keeping the accuracy of permeability estimation. Permeability values with and without mineralisation are compared between improved FPNM and direct simulation, for verification purposes. Lastly, we use the modelling framework to estimate the permeability of a coal sample at in-situ condition. This improved FPNM modelling framework can improve the simulation efficiency of fluid transport processes within fractured media, which is central to many energy, geoscience and water resources applications.

Automated summary

The study investigates the permeability of coal under in-situ conditions using high pressure X-ray micro-CT imaging, and constructs an improved coal permeability model by utilizing domain decomposition and image segmentation methods.