Experimental study of the radial multi-scale dynamic diffusion model for gas-bearing coal

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.