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Pore Structure Characterization Based on the Panxi Coal Molecular Model

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Abstract

With increasing years of mining in the Panxi mine, coal seam pressure is increasing and safety hazards are becoming greater. In this paper, experimental and modeling studies were conducted on molecular-scale pores in Panxi bituminous coal. Reconstructing the pores of coal from a molecular perspective was realized, providing a methodological basis for the study of the microscopic properties of Panxi coal. The molecular model of the Panxi coal was established by ultimate analysis, solid-state CP/MAS 13C nuclear magnetic resonance, and X-ray photoelectron spectroscopy. Based on the Monte Carlo method, a pore structure model of the Panxi coal sample was constructed with 100 coal molecules. Visual and quantitative characterizations of molecular-scale pores of different sizes in the model were achieved using Avizo software. The characterization results of the model were in good agreement with the experimental results of CO2 adsorption. The structural parameters of the molecular-scale pores were calculated and analyzed. The average coordination number of the pores was 2.31, indicating good pore connectivity. The pore-throat radius ratios (ratio of pore radius to average radius of throat connected to pore) were mainly in the range of 1.25–2.25, indicating that the molecular-scale pore space of the coal sample was relatively uniform. The proposed method of molecular-scale pores reconstruction and characterization can be applied to the study of coal microscopic properties such as adsorption, permeation, and mechanics.

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Acknowledgments

This work is financially supported by the Fundamental Research Funds for the Central Universities (No. 2022YJSAQ21), National Natural Science Foundation of China (No. U1704242), and the Yue Qi Distinguished Scholar Project, China University of Mining & Technology, Beijing; the authors are grateful for their support.

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Authors and Affiliations

  1. School of Emergency Management and Safety Engineering, China University of Mining and Technology, Beijing, 100083, China

    Junqing Meng, Shuo Zhang, Zihao Cao & Chen Wang

  2. State Key Laboratory of Coal Resources and Safe Mining, China University of Mining and Technology, Beijing, 100083, China

    Junqing Meng, Shuo Zhang, Zihao Cao & Chen Wang

  3. Beijing Key Laboratory for Precise Mining of Intergrown Energy and Resources, China University of Mining and Technology, Beijing, 100083, China

    Junqing Meng

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  1. Junqing Meng
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Correspondence to Junqing Meng.

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Appendix: Detailed Process for Quantitative Analysis and Visualization of Model

Appendix: Detailed Process for Quantitative Analysis and Visualization of Model

The specific process of quantitative analysis and visualization of pores using Avizo software is shown in Figure 

Figure 15
figure 15

Process of quantitative analysis and visualization of pores

Full size image

15.

The “Generate Molecular Surfaces” command was selected to generate the pore surface of the model. Surface Type was set to SES; Quality was set to correct; Number of Points per A2 was set to 2. For this model, the probe radius is set in the range of 0.05–0.5 nm, and both too large and too small are out of the model pore size range. In this paper, we analyzed the two cases of probe radius setting 0.14 nm and 0.16 nm.

The “Scan Surface to Volume” command was selected to convert the pore surface into a solid model. Dimensions were set to 451. Solid slices of the model were obtained in this step.

The slice file was imported into Avizo and the “Auto Thresholding” command was selected to perform threshold segmentation to identify the pores. Type was set to Auto Threshold Low; Interpretation was set to 3D; Mode was selected as min–max; Criterion was set to factorization.

The “Axis Connectivity” command was selected to detect the connectivity of the pores. Neighborhood was set to 26; Orientation was selected to Z-axis.

The “Separate Objects” command was selected to separate the pore space for the subsequent generation of the pore network model. Method was set to Chamfer-Conservative; Marker Extent was selected as 2; Out Type was selected as connected object; Algorithm Mode was set to repeatable. The results of the segmented pores were obtained in this step. This result can be used to generate a pore network model.

The “Generate Pore Network Model” command was selected to generate the pore network model. The “Pore Network Model View” command can be selected to display the pore network model. The parameters of this command are set according to the needs of the display, and the adjustment of the parameters only affects the appearance of the display, not the pore parameters. While generating the pore network model, the pore parameters are automatically calculated and can be viewed in the Avizo browser. These parameters include pore size, number of pores, pore coordination number, pore coordinates, etc. The data can be imported into Excel for statistical purposes to obtain a pore parameter distribution.

The “Distribution Analysis” command was selected to analyze the pore network model. Property in X was set to EqRadius; Property in Y was set to Area and Volume; Number of Bins was set to 50. The data were imported into Excel and processed to obtain the pore size distribution, cumulative specific surface area, and cumulative pore volume maps.

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Meng, J., Zhang, S., Cao, Z. et al. Pore Structure Characterization Based on the Panxi Coal Molecular Model. Nat Resour Res 31, 2731–2747 (2022). https://doi.org/10.1007/s11053-022-10085-0

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