Anisotropy of coal pore connectivity: Experiments based on low-field nuclear magnetic resonance and low-temperature nitrogen adsorption

ABSTRACT As an unconventional reservoir, coal is characterized by the development of micro/nanometer pores and significant pore differences in different bedding directions. Pore heterogeneity and anisotropy can affect the recovery of resources and the interpretation of seismic data. To date, research on coal anisotropy focuses mainly on the heterogeneity of pore distribution. Nonetheless, there are relatively few studies and a lack of comprehensive knowledge regarding pore connectivity differences within the same macrolithotype of coal in different bedding directions. We develop a novel method for studying the anisotropy of pore connectivity in coal. This method uses epoxy resin to seal the different surfaces of cubic coal samples, combined with refined pore characterization techniques, to conduct anisotropy studies at different pore scales. These include differences in pore connectivity in different bedding directions and the anisotropic characteristics of micron/nanoscale pores. The results indicate that the pores in various bedding directions differ considerably in their type and distribution modes. There is a wide range of pore types in the bedding-parallel direction, and the pores have regular variations. In contrast, the pore type is single in the bedding-normal direction, the pore distribution lacks an obvious pattern, and the pore complexity is higher. The anisotropy of the seepage pores is stronger than that of the adsorption pores, which is the main reason for the anisotropy of the reservoir properties. Based on an anisotropic study of coal pore connectivity, we can target the design of resource recovery processes to improve resource recovery. In directions with low permeability, measures such as water injection can be taken to enhance permeability. The pore size and connectivity in different bedding directions can also be considered by introducing anisotropic parameters to optimize the permeability anisotropy model and provide better guidance for resource recovery.