Quantitative characterization of pore-fracture structure of medium and high-rank coal based on micro-CT technology

ABSTRACTCoal is a natural and complex porous medium, which contains pore-fracture structures of different scales. The pore-fracture structures of coal directly affect the characteristics of gas storage and migration. In this paper, high-resolution X-ray CT scanning technology is used to quantitatively characterize the pore-fracture structure of medium and high-rank coals. First, the porosity inversion method is used to determine the optimal threshold segmentation of pores and fracture in medium and high-rank coals. Then, the pore and fracture model of representative element volume (REV) was extracted and established to characterize the area porosity, pore surface area, and shape factor of the two coals, and the relationship between pore surface area and shape factor was investigated. Finally, an equivalent pore network model (PNM) of connected pore topology was established, and pore-throat parameters are statistically analyzed, including pore volume, pore radius, throat radius, throat length, and coordination number. The results show that the average pore diameter and average surface area of macropores in medium-rank coals are larger than those of high-rank coals, and high-rank coals have fewer isolated pores. With the increase of coal rank, the length and radius of the throat gradually decrease, which indicates that the throat of the medium-rank coal has a higher degree of development, and the gas seepage ability in the throat is stronger. The outcome of this study is of great significance for comprehensively understanding the pore-fracture structure of coal in micro-scale.KEYWORDS: Pore-fracture structureCT 3D reconstructionmicro-CT technologyrepresentative elementary volume (REV)pore-throat parametersmedium and high-rank coal AcknowledgementsThe work was financially supported by National Natural Science Foundation of China (51874178), Science and Technology Innovation and Entrepreneurship Fund Special Project of Tiandi Technology Co. Ltd. (2020-TD-MS003) and Beijing Natural Science Foundation (2214071)Disclosure statementNo potential conflict of interest was reported by the authors.Data Availability StatementThe data that supports the findings of this study are available within the article.