舒龙勇, 朱南南, 陈结, 安赛, 张慧杰. 煤与瓦斯突出危险精准辨识理论方法与技术探索[J]. 煤炭学报, 2020, 45(5). DOI: 10.13225/j.cnki.jccs.DY20.0529
引用本文: 舒龙勇, 朱南南, 陈结, 安赛, 张慧杰. 煤与瓦斯突出危险精准辨识理论方法与技术探索[J]. 煤炭学报, 2020, 45(5). DOI: 10.13225/j.cnki.jccs.DY20.0529
SHU Longyong, ZHU Nannan, CHEN Jie, AN Sai, ZHANG Huijie. Theoretical method and technology of precision identification for coal and gas outburst hazard[J]. Journal of China Coal Society, 2020, 45(5). DOI: 10.13225/j.cnki.jccs.DY20.0529
Citation: SHU Longyong, ZHU Nannan, CHEN Jie, AN Sai, ZHANG Huijie. Theoretical method and technology of precision identification for coal and gas outburst hazard[J]. Journal of China Coal Society, 2020, 45(5). DOI: 10.13225/j.cnki.jccs.DY20.0529

煤与瓦斯突出危险精准辨识理论方法与技术探索

Theoretical method and technology of precision identification for coal and gas outburst hazard

  • 摘要: 针对我国煤与瓦斯突出频发、突出事故呈现新特征、突出预测方法和指标体系有待完善等现实问题,为了更好地指导突出预测与防治工作,以煤与瓦斯突出关键结构体致灾机理为指导,基于突出发生位置必须具备特殊的地质结构环境这一基本认识,提出了煤与瓦斯突出危险“层层递进-精准辨识”的理论方法,具体包括3个层次:采用物探和钻探相结合的手段,超前探测采掘工作面周围存在的异常地质结构;采用微震和瓦斯涌出实时监测相结合的方法,动态分析采掘扰动条件下采掘工作面前方煤体结构、地应力和瓦斯大小变化特征;采用随钻测定相关特征参数和预测指标的方法,进一步验证超前探测和实时监测的辨识结果。 探索性工程试验表明:“超前探测地质结构异常-实时监测煤体突出危险性-随钻测定煤层瓦斯大小”相结合的突出危险辨识技术能够综合反映采掘工作面周围地质结构、煤体结构、地应力和瓦斯大小变化特征,促进了突出预测工作由点预测向面预测、由间断式向连续式、由接触式向接触-非接触式相结合的转变。 通过进一步发展物探和钻探相结合的精细探测技术,引入大数据分析和机器学习算法等训练综合判识模型,开发以“超前探测异常地质结构,实时监测采掘工作面微震信号和瓦斯涌出时序变化特征,随钻测定各种特征参数和预测指标”为核心的综合预警系统,实现突出灾害多元信息综合监测与智能预警,更好地服务于煤与瓦斯突出防治工作。

     

    Abstract: There are many practical problems for coal and gas outburst in China,such as the frequent occurrence,the new features which has emerged,and the prediction method and index system which need to be improved. In order to better guide the prediction and prevention of coal and gas outburst,the theoretical method of “ Layers of progressive- Precision identification” for coal and gas outburst hazard is proposed,which includes three levels,under the guidance of key structural body theory of coal and gas outburst,and based on the basic understanding that the outburst location must have the special geological structure environment. The abnormal geological structure around the mining face is detected in advance by the method of geophysical prospecting and drilling. Based on the real-time monitoring of micro- seism and gas emission,the change of coal structure,crustal stress and gas in front of the mining face are dynamically analyzed under the condition of mining disturbance. The identification results of the advanced detection and real-time monitoring are further verified by the measured relevant feature parameters and prediction indexes of coal and gas out- burst while drilling. Exploratory engineering tests show that the identification method of outburst hazard,which includes “Advanced detection of abnormal geological structure-real-time monitoring of coal and gas outburst hazard-Measure- ment of coal seam gas while drilling”,can comprehensively indicate the geological structure,coal structure,crustal stress and gas around the mining face,which promotes the transformation of coal and gas outburst prediction from point prediction to face prediction,from discontinuous prediction to continuous prediction,and from contact prediction to contact and non-contact combined prediction. The fine detection technology which includes geophysical prospecting and drilling needs further development. Big data analysis and machine learning algorithm are introduced to train com- prehensive judgment model. A comprehensive early-warning system is developed with the core of “Advanced detection of abnormal geological structure-real-time monitoring of micro-seismic signal and time series of gas emission in mining face-Measurement of various feature parameters and prediction indexes while drilling”. It is expected to realize com- prehensive monitoring of multivariate information and intelligent early warning for outburst hazard,which will better serve the prevention and control of coal and gas outburst.

     

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