| 基于灰熵法的深部煤层瓦斯含量影响因素分析及预测 |
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| 引用本文： | 周鑫隆,汤静,石必明,吕辰.基于灰熵法的深部煤层瓦斯含量影响因素分析及预测[J].煤田地质与勘探,2016,44(2):19. |
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| 作者姓名： | 周鑫隆 汤静 石必明 吕辰 |
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| 基金项目： | 宁波工程学院校级科研项目（2015002） |
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| 摘 要： | 为了提高深部煤层瓦斯含量的预测精度，提出了采用灰熵分析法对瓦斯含量影响因素进行研究，以潘三矿深部11-2煤层为例，根据灰熵关联度的大小选取不同的影响因素分别建立了GM（1，3）、GM（1，4）和GM（1，5）预测模型，依据精度检验结果选择精度更高的瓦斯预测模型。研究结果表明，影响潘三矿深部11-2煤层瓦斯含量的因素重要程度从大到小依次为:主断层距离、煤层埋深、煤厚、顶板砂泥比、煤层倾角。由此建立的3个模型的预测精度都在合格以上，其中GM（1，4）模型预测精度达到了1级，平均相对误差为5.063 6%，可采用该模型对11-2煤层瓦斯含量进行预测，为深部煤与瓦斯安全高效开采提供可靠依据。
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| 关 键 词： | 瓦斯含量 灰熵分析法 预测精度 GM(1 N)模型 |
| 收稿时间： | 2015-08-12 |
Analysis and forecast of influential factors of gas content in deep coal seam on the basis of the grey entropy |
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| Abstract: | In order to improve the forecast precision of gas content in deep coal seam, taking deep coal seam No.11-2 in Pansan coal mine as example, grey entropy is proposed to research influencing factors of gas content. The GM(1,3), GM(1,4) and GM(1,5) gas content forecasting models are established to select an appropriate model with the highest forecasting precision according to the size of different influencing factors of grey entropy relation degree. The results show that the influencing factors of gas content in deep coal seam No.11-2 are in decreasing order the main fault distance, the buried depth of coal seam, coal seam thickness, the ratio of the sandstone and mudstone in coal seam roof and dip. The forecast precision of GM models is higher than the qualified level. What's more, the precision of GM(1,4) model reaches the first grade and average relative error is 5.0636%. In conclusion, GM(1,4) model can be adopted to accurately forecast gas content in deep coal seam No.11-2, which provides reliable references for safe and high-efficiency coal mining. |
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