Experimental study of the radial multi-scale dynamic diffusion model for gas-bearing coal
Yanpeng Xu1, Xiao Chen1, Jiangong Yu2
1School of Safety Science and Engineering, Henan Polytechnic University, Jiaozuo, China
2Jiaozuo Rexel Disc Brake Co, Jiaozuo, China
Min. miner. depos. 2022, 16(4):80-86
Full text (PDF)
Purpose. The purpose of this paper is to solve the scientific problem that the classical diffusion model in columnar coal cores cannot accurately describe the whole process of gas diffusion.
Methods. The diffusion-percolation experiments were carried out using the laboratory’s homemade experimental equipment with standard ϕ 50mm×100 mm columnar raw coal cores under different air pressures.
Findings. The classical diffusion model was used to fit the experimental data. The experiment has found that the classical diffusion model of the columnar coal core can only partially describe the gas diffusion process. The longer the experimental time, the larger the error between the model and the experiment, and the analysis has found that the apparent diffusion coefficient shows decay changes with time. The dynamic diffusion coefficient concept is then proposed in order to con-struct a radial multi-scale dynamic prominent diffusion-percolation model for columnar coal cores. The theoretical curve of the new model nearly coincides with the experimental curve, and the new model can describe the gas diffusion-percolation process of columnar coal cores more accurately. The multi-scale dynamic diffusion-percolation model covers the classical diffusion model. It explains the mechanism of gas diffusion-percolation in multi-scale pores, i.e., at the beginning of the flow, gas flows out from the large external pores first, from the surface inwards. Over time, the pore size through which gas flows gradually becomes smaller, the diffusion resistance gradually increases, and the apparent diffusion coefficient slowly decreases.
Originality. This paper proposes a new multi-scale dynamic diffusion-percolation model to compare the old and new model analysis, as well as carefully studying the mechanism of gas flow in coal.
Practical implications. This research has important engineering significance for the accuracy of measuring the gas content of coal seams, as well as predicting coal and gas content.
Keywords: apparent diffusion coefficient, columnar coal core, multiscale, diffusion-percolation model
- Barrer, R.M. (1951). Diffusion in and through solids. London: Cambridge University Press, 464 p.
- Crank, J. (1975). The mathematic of diffusion. Oxford: Oxford University Press, 421 p.
- Ruckenstein, E., Vaidyanathan, S., & Youngquist, GR. (1971). Sorption by solids with bidisperse pore structures. Chemical Engineering Science, 26(9), 1305-1318. https://doi.org/10.1016/0009-2509(71)80051-9
- Yang, Q., & Wang, Y. (1986). Theory of methane diffusion from coal cuttings and its application. Journal of China Coal Society, (3), 87-94.
- Nie, B.S., Wang, E.Y., & Guo, Y.Y. (1999). Mathematical and physical model of gas diffusion through coal particles. Journal of Liaoning Technical University (Natural Science Edition), (6), 582.
- Guo, Y.Y., Wu, S.Y., & Wang, Y.M. (1997). Study on the measurement of coal particle gas diffusion and diffusion coefficient. Shanxi Mining Institute Learned Journal, (1), 17-21.
- Nie, B.S., Guo, Y.Y., & Wu, S.Y. (2001). Through coal particles and its analytical solution. Journal of China University of Mining & Technology, 30(1), 21-24.
- Zhang, L.L., Wei, J.P., & Wen, Z.H. (2020). Gas diffusion model of coal particle based on dynamic diffusion coefficient. Journal of China University of mining & Technology, 49(1), 62-68.
- Li, Z.Q., Liu, Y., & Xu, Y.P. (2016). Gas diffusion mechanism in multi-scale pores of coal particles and new diffusion model of dynamic diffusion coefficient. Journal of China Coal Society, 41(3), 633.
- Li, Z.Q, Wang, D.K., & Song, D.Y. (2015). Influence of temperature on dynamic diffusion coefficient of CH4 into coal particles by new diffusion model. Journal of China Coal Society, 40(5), 1055-1064.
- Pan, Z, Connell, L.D., Camilleri, M., & Connelly, L. (2010). Effect of matrix moisture on gas diffusion and flow in coal. Fuel, 89(11), 3207-3217. https://doi.org/10.1016/j.fuel.2010.05.038
- Tan, Y., Pan, Z., Liu, J., Kang, J., Zhou, Connell, L.D., & Yang, Y. (2018). Experimental study of impact of anisotropy and heterogeneity on gas flow in coal. Part I: Diffusion and adsorption. Fuel, 232(15), 444-453. https://doi.org/10.1016/j.fuel.2018.05.173
- Liu, J., Fokker, P.A., & Spiers, C.J. (2017). Coupling of swelling, internal stress evolution, and diffusion in coal matrix material during expo-sure to methane. Journal of Geophysical Research: Solid Earth, 122(2), 844-865. https://doi.org/10.1002/2016JB013322
- Li, Z.Q., C, Q., Li, Y.W., Duan, Z.P., & Song, D.Y. (2017). Research on gas diffusion model and experimental diffusion characteristic of cylindrical coal. Journal of China University of Mining & Technology, (465), 1033-1040.
- Li, Z.Q., Peng, J., Li, L., Qi, L., & Wai, L. (2021). Novel dynamic multiscale model of apparent diffusion permeability of methane through low-permeability coal seams. Energy Fuels, 35(9), 7844-857. https://doi.org/10.1021/acs.energyfuels.1c00324