Abstract

The distribution of multiscale pores and fractures in coal and rock is an important basis for reflecting the capacity of fluid flow in coal seam seepage passages. Accurate extraction and qualitative and quantitative analysis of pore-fracture structures are helpful in revealing the flow characteristics of fluid in seepage channels. The relationship between pore and fracture connectivity can provide a scientific reference for optimizing coal seam water injection parameters. Therefore, to analyse the change in permeability caused by the variability in the coal pore-fracture network structure, a CT scanning technique was used to scan coal samples from the Leijia District, Fuxin. A total of 720 sets of original images were collected, a median filter was used to filter out the noise in the obtained images, and to form the basis of a model, the reconstruction and analysis of the three-dimensional pore-fracture morphology of coal samples were carried out. A pore-fracture network model of the coal body was extracted at different scales. Using the maximum sphere algorithm combined with the coordination number, the effect of different quantitative relationships between pore size and pore throat channel permeability was studied. Avizo software was used to simulate the flow path of fluid in the seepage channels. The change trend of the fluid velocity between different seepage channels was discussed. The results of the pore-fracture network models at different scales show that the pore-fracture structure is nonuniform and vertically connected, and the pores are connected at connecting points. The pore size distribution ranges from 104 μm to 9425 μm. The pore throat channel length distribution ranges from 4206 μm to 48073 μm. The size of the coordination number determines the connectivity and thus the porosity of the coal seam. The more connected pore channels there are, the larger the pore diameters and the stronger the percolation ability. During flow in the seepage channels of the coal, the velocity range is divided into a low-speed region, medium-speed region and high-speed region. The fluid seepage in the coal seam is driven by the following factors: pore connectivity > pore and pore throat dimensions > pore and pore throat structure distribution. Ultimately, the pore radius and pore connectivity directly affect the permeability of the coal seam.

Highlights

  • At present, water injection [1,2,3,4] into a coal seam is the most effective way to reduce dust but is not an ideal solution in the field, mainly because the pore-fracture structure of coal seams is very complex, and its morphological and structural characteristics determine the physical and chemical properties of the coal [5, 6]

  • The results showed that the specific surface area and pore volume results were quite different among the coal samples

  • The pore size analysis of the coal sample data shows that the number of micropores, transition pores and mesopores is 2763, 598 and 96, respectively, the contribution of micropores and transition pores to the total pore volume is 0.78% and 11.21%, and mesopores account for 88.01% of the total pore volume

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Summary

Introduction

Water injection [1,2,3,4] into a coal seam is the most effective way to reduce dust but is not an ideal solution in the field, mainly because the pore-fracture structure of coal seams is very complex, and its morphological and structural characteristics determine the physical and chemical properties of the coal [5, 6]. Nondestructive visual measurement of the pore-fracture structure in a coal seam can be realized, and a 3D network model of real pores can be obtained. Li et al [5] used CT scanning technology and electron microscope scanning technology, the fracture pore structure at different scales is studied, and the influence of pore characteristics on coal seam gas storage capacity is analyzed. Is used to simulate the flow path of a fluid in the seepage channel [36,37,38,39], and the trend of the variation in fluid velocity between different seepage channels is discussed to explore the mechanism of the microseepage of fluid in a coal body and provide guidance for coal seam water injection and dust control measures [40,41,42]

Coal sample collection
Experimental equipment and methods
Analysis of scan results
Median filtering of CT image noise
Comprehensive characterization of pore-fissure spaces at different scales
Quantitative analysis of pores and pore throats
Connectivity analysis and network characteristics of a porous rock
Matching analysis
Permeability simulation principle
Permeability simulation results
Conclusions
Full Text
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