采矿与安全工程学报 ›› 2012, Vol. 29 ›› Issue (5): 685-693.

• 论文 • 上一篇    下一篇

矿山微地震活动特征的概率分析方法研究

  

  1. 1.北京科技大学土木与环境工程学院,北京  100083;
    2.中国石油勘探开发研究院地球物理研究所,北京  100083
  • 收稿日期:2012-05-15 出版日期:2012-09-15 发布日期:2012-09-05
  • 作者简介:缪华祥(1962-),男,江苏省常州市人,高级工程师,博士,从事矿山微地震监测方面的研究。 E-mail:mhuaxiang@163.com Tel:13901167040
  • 基金资助:

    国家自然科学基金项目(40674017,50774012);
    国家重点基础研究发展计划(973)项目(2010CB226803)

Probability Analysis of Microseismic Activity in Underground Mining

  • Received:2012-05-15 Online:2012-09-15 Published:2012-09-05

摘要: 为了研究矿山微地震活动的随机特征,提出了用于描述矿山微地震活动随机特征的三个统计量:微地震能量分布率、微地震发生率和微地震空间分布率,基于概率论和数理统计原理,研究了三个统计量的概率计算方法。通过对某矿山微地震实际数据的计算发现:该矿区微地震能量分布率的概率密度曲线类似于正态分布;微地震发生率的概率密度曲线类似于泊松分布;微地震空间分布率的概率密度曲线虽然呈现多种形式,但微地震事件大部分在固定工作面前方、工作面两侧边缘和煤层顶底板位置处,反映了在岩体特性突变位置处,发生微地震的概率较大。因此利用这三个统计量及其概率密度分布特征,可以从时间-空间-能量的角度,描述矿山微地震活动特征,对矿山微地震监测技术的基础研究和应用具有一定的意义。

关键词: 微地震, 活动性, 概率密度, 特征分析

Abstract: To characterize the stochastic features of microseismic activities in coal mining, three statistical variables, including distribution rate of microseismic energy, occurrence rate of microseismic events, and spatial distribution of events, were proposed in this paper. In addition, the methods to analyze probabilities of these variables were also established based on the  probability theory and mathematical statistical principle. The calculation results of the field microseismic data in one mine show thatthe probability density of microseismic energy presents the normal distribution;, the probability density of microseismic occurrence is similar to Poso distribution, while the probability density of microseismic spatial distribution presents multi-patterns. Meanwhile, although no certain patter is revealed from the spatial distribution, most microseismic events are occurred in the front and two sides of the working face, as well as the top and bottom of the coal seam, which means the occurrence probability of microseismic events is higher in the mutation location of rock mass characteristics. The field application proves that these three statistical variables and the corresponding probability density distributions can be well used to characterize the microseismic activities in time, spatial and energy, which may significantly improve the fundamental research in microseismic monitoring and its application in coal mining.

Key words: microseismic, activity, probability density, characteristic analysis