Fractal Analysis and Classification of Pore Structures of High-Rank Coal in Qinshui Basin, China

Difei Zhao (), Yinghai Guo, Geoff Wang, Xin Guan, Xueqing Zhou and Jing Liu
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Difei Zhao: Artificial Intelligence Research Institute, China University of Mining and Technology, Xuzhou 221116, China
Yinghai Guo: Key Laboratory of Coalbed Methane Resources and Reservoir Formation Process, China University of Mining and Technology, Ministry of Education, Xuzhou 221008, China
Geoff Wang: School of Chemical Engineering, University of Queensland, Brisbane, QLD 4072, Australia
Xin Guan: School of Safety Engineering, China University of Mining and Technology, Xuzhou 221116, China
Xueqing Zhou: Institute of Deep-Sea Science and Engineering, Chinese Academy of Sciences, Sanya 572000, China
Jing Liu: School of Resources and Geosciences, China University of Mining and Technology, Xuzhou 221116, China

Energies, 2022, vol. 15, issue 18, 1-22

Abstract: The influence of high-rank coal’s pore characteristics on the physical properties, gas-bearing properties, and exploitation of coal reservoirs is becoming more and more prominent. How to establish the classification to describe the pore networks combining quantitative and qualitative characteristics has emerged as a major problem, which may offer a scientific foundation to deepen the understanding of this issue. In this research, the structure and fractal characteristics of reservoir pores were determined after analyzing 20 high-rank coal samples from Xinjing Coal Mine in the Qinshui Basin with the application of the high-pressure mercury intrusion method (HPMI) and argon ion polishing–field emission scanning electron microscopy (AIP–FESEM). The results show that the tested coal samples were bipolar distributed, with transitional pores and micropores dominating the pore volume, followed by macropores. The Menger sponge fractal models manifested two or three distinct straight-line segments with demarcation points of 65 nm and 1000 nm. A natural classification with three major pore types of diffusion pores (D-pores), seepage pores (S-pores), and pico pores (P-pores), demarcated by pore size intervals of 65 nm and 1 nm and seven sub-types, was established to relate pores to pore networks based on these fractal characteristics and the kinetic characteristics of methane molecules. This classification scheme can characterize the relationship between pore types and the corresponding major occurrence and transport mechanisms of the gas. In addition, P-pores and D-pores are predominately nanoscale OM pores with three major genetic types of organic constituent interparticle pores (5–200 nm), metamorphic pores (<5 nm), and intermorphic pores (<5 nm). S-pores are more complex in origin and shape features, and the major types include outgas pores, plant tissue residual pores, mineral-related pores, and microfractures. The mean radius (Pa), total pore volume (Vt), apparent porosity (Φ), and volume ratio of macro- and mesopores were positively correlated with the fractal dimension D1 of S-pores (>65 nm). Since fractal analysis is a more comprehensive characterization of reservoir structure and quantitatively reflects the pore structure, undulating state, and roughness of the inner surface, fractal parameters can be used as an important index to describe the pore structure characteristics of high-rank coal reservoirs.

Keywords: pore structure; coal; fractal; classification; coalbed methane; microstructure (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
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