采矿与安全工程学报 ›› 2012, Vol. 29 ›› Issue (1): 78-83.

• 论文 • 上一篇    下一篇

某深井矿山岩爆预测模式研究

  

  1. 1. 北京科技大学土木与环境工程学院,北京  100083;2. 中国矿业大学资源与安全工程学院,北京  100083
  • 收稿日期:2010-05-16 出版日期:2012-01-15 发布日期:2011-12-14
  • 作者简介:刘晓辉(1984-),男,四川省德阳市人,博士,从事微震监测技术及膏体充填方面的研究。 E-mail:xiaohuiliu28@yahoo.cn Tel:15811017384
  • 基金资助:

    教育部长江学者和创新团队发展计划项目(IRT0950);国家自然科学基金重点项目(50934002,51104011);中国博士后科学基金项目(201104053,20100480200);中央高校基本科研业务费项目(2011QZ01)

Study on Rock Burst Forecasting Prediction in A Deep Mine

  • Received:2010-05-16 Online:2012-01-15 Published:2011-12-14

摘要: 针对某深井矿山的微震监测信息,采用地震学原理进行震源参数量化计算,结合现场岩爆记录,对井下地压活动与微震参数时空变化的响应规律进行了研究。结果表明:一定时间域内微震参数的空间变化反映了岩体的应力分布状态,可做为岩爆危险区识别的依据;一定空间域内微震参数的时间变化与岩体破裂过程紧密相关,震源参数随时间突增、骤减等异常变化表征岩体不同的变形阶段。基于研究结果,提出以应变硬化结束应变软化开始的时间点作为岩爆预警点,构建了该矿岩爆预测的一般模式,实际应用效果较好,为类似矿山的岩爆预测提供了借鉴意义。

关键词: 岩爆, 微震监测, 岩爆预测, 微震参数, 时空分布

Abstract: In this paper,according to the microseismic monitoring information in a deep mine,the principle of seismology was adopted to make a quantization calculation of microseismic parameters,combined with the rock burst records in underground,the response pattern between the ground pressure activities and temporal-spatial variation of microseismic parameters was further studied.The results show that the spatial variation of microseismic parameters in a time domain reflects the stress distribution in rock mass,which can provide basis to identify the rock burst danger areas.The temporal variation of parameters in a certain area is closely related with the rock failure process,and the abnormal changes of microseismic parameters with time such as sharp increasing,quickly decreasing can characterize the different deformation stages of rock mass.Based on the research results,the point at which the seismic hardening process of rock mass ends and the strain softening process begins can be used as the pre-warning point of rock burst.Finally,a general prediction model for rock burst in the mine is constructed,and has shown good effects in practice,which also provides reference significance for rock burst prediction in similar mines.

Key words:  , rock burst;microseismic monitoring;rock burst prediction;microseismic parameters;temporal and spatial distribution