Suppr超能文献

微震监测在煤与瓦斯突出危险性中的研究。

Investigation of coal and gas outburst risk by microseismic monitoring.

机构信息

Laboratory of Educational Ministry for High Efficient Mining and Safety in Mental Mine, University of Science and Technology Beijing, Beijing, China.

School of Civil and Resources Engineering, University of Science and Technology Beijing, Beijing, China.

出版信息

PLoS One. 2019 May 23;14(5):e0216464. doi: 10.1371/journal.pone.0216464. eCollection 2019.

Abstract

In order to improve the monitoring and prediction of coal and gas outburst, this paper proposes a new method for dynamic regional prediction of coal and gas outburst using microseismic (MS) monitoring. The theoretical basis of this method is presented. An index evaluation system was established and applied, based on which field tests were carried out in a coal mine. The results show that seismic monitoring with frequency and energy indexes can obtain good results for mining disturbance intensity monitoring and geological structure detection; the regional stress distribution detected by seismic wave tomography is consistent with the theoretical stress field, making its use of great significance for optimizing coal and gas outburst drilling parameters and improving overall tunneling efficiency. This approach overcomes the limitations of traditional methods in the temporal and spatial dimensions and realizes dynamic and continuous monitoring of coal and gas outburst-prone areas.

摘要

为了提高煤与瓦斯突出的监测和预测水平,本文提出了一种利用微震(MS)监测进行煤与瓦斯突出动态区域预测的新方法。本文介绍了该方法的理论基础,建立并应用了指标评价体系,在此基础上在煤矿进行了现场试验。结果表明,利用频率和能量指标进行地震监测,可以很好地监测开采扰动强度和地质构造探测;地震波层析成像检测到的区域应力分布与理论应力场一致,这对优化煤与瓦斯突出钻进参数和提高整体掘进效率具有重要意义。该方法克服了传统方法在时间和空间维度上的局限性,实现了煤与瓦斯突出危险区域的动态连续监测。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e212/6532864/89df13340944/pone.0216464.g001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验