Abstract：In order to explore the gas occurrence law of Qinglong Mine in Guizhou Province and predict the gas content of the unmined coal seam in the mining area. Taking 16 coal seam of Qinglong Mine as an example, the influence of various factors on gas content of 16 coal seam is discussed from the aspects of coal seam thickness, roof mudstone thickness, coal seam buried depth and structural index. The weight analysis of factors affecting coal seam gas content is realized by grey correlation method. The prediction model of gas content in Qinglong mining area was established by multiple linear regression. The results show that the gas content of 16 coal seam in Qinglong Mine is positively correlated with the depth of coal seam, the thickness of mudstone and coal seam, and negatively correlated with the structural index. The dominant factors affecting gas content are coal seam thickness and coal seam buried depth, and the correlation between influencing factors and gas content is coal seam thickness > floor buried depth≈structural index > roof mudstone thickness; it is found that the multiple regression prediction model can be used to predict the gas content of unexploited coal seams in the study area with the correlation coefficient R2=0.843.
朱俊卿. 青龙矿瓦斯赋存规律及含量预测模型的构建[J]. 煤炭与化工, 2022, 45(1): 112-116，120..
Zhu Junqing. Construction of gas occurrence law and content prediction model in Qinglong Mine. CCI, 2022, 45(1): 112-116，120..
