Numerical investigation of flue gas injection enhanced underground coal seam gas drainage

Abstract

Coal seam with low permeability is widely distributed in China. Injection of flue gas (N2:CO2 = 0.85:0.15) is an effective approach to improve coal seam gas drainage efficiency. This process relates complex responses among ternary gases (CH4, CO2, and N2) competitive sorption on coals, gas diffusion, gas‐water migration by means of two‐phase flow, and coal deformation. In this paper, an improved hydraulic‐mechanical model coupling above interactions is established for flue gas injection enhanced gas drainage. This model is used to simulate flue gas enhanced drainage by finite element method. The sensitivity analyses of key factors are made to recovery a better understanding on the processes controlling flue gas enhanced drainage. Results show that the flue gas enhanced drainage can indeed improve the efficiency of gas extraction and reduce the gas pressure to the required value in a shorter duration. Due to the competitive adsorption and gas sweeping effect of injected flue gas, CH4 is driven toward drainage borehole, and CH4 pressure and content near the injection borehole decrease faster than that near the drainage borehole. The peak CH4 pressure laterally moves from the injection borehole to the drainage borehole. Higher injection pressure, initial permeability, and smaller sorption affinity ratios may lead to greater CH4 production rate at early drainage stage, but smaller CH4 production rate at late stage. The factors controlling the behavior of flue gas enhanced drainage are initial permeability, injection pressure, and sorption affinity ratios in order. This work offers useful framework to investigate important technical challenges associated with enhanced mine gas drainage, as well as unconventional gas development.

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“…BA-ELM. Suppose that the number of bat population N � 200, initial pulse rate r 0 � 0.1, pulse rate enhancement coefficient gamma c � 0.9, pulse emission frequency λ∈[0, 2], loudness attenuation coefficient α � 0.9, loudness range A∈ [1,2], and iteration number L � 200. e first 80 groups of sample data were used to train ELM neural network. By comparing the operation performance of the neural network with different types of activation function and different number of hidden-layer neurons, the appropriate type of activation function and number of hidden-layer nodes were determined.…”

“…With depletion of shallow coal resources, the mining depth of coal mines in China increases. e coupling effect of great in situ stress and high gas pressure in deep coal seam increases the risk of gas outbursts [1][2][3][4][5]. e residual gas content is an important parameter for gas outburst prediction.…”

Numerical study on enhancing coalbed methane recovery by injecting N2/CO2 mixtures and its geological significance

“…The strain and displacement components of REV satisfy the Cauchy geometric equation, and the tensor symbol is expressed as 42 :…”

Experimental investigation on dynamic strength and energy dissipation characteristics of gas outburst‐prone coal

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