微震集聚度:微震时空演化五维指标的概念、算法和应用

Microseismic clustering degree: concept, algorithm and application of five-dimensional index of microseismic spatiotemporal evolution

  • 摘要: 微震数据监测已成为矿井安全判识、预警的重要手段,但是基于微震的时空演化机制及其与岩层活动的相关性仍然亟待解决。当前微震分析多采用多个指标分别或者综合评价,但是不同指标间的联系较弱,多个指标可能存在冗余,单个指标则可能存在不足,导致判识结果关联性较弱甚至相悖。工作面海量的、能量各异的微震事件都是由岩层破裂和回转运动引起,许多微小事件是由同一个岩层破坏衍生的,故而微震事件之间存在一定的关联性。因此,基于内涵丰富的指标来研究微震时空演化有着至关重要的意义。基于此提出了一个包含空间3个维度、能量1个维度以及时间1个维度,共5个维度的微震时空演化指标:微震集聚度,该指标表明岩层破断回转时往往伴随着较大的微震能量或者是空间聚集程度和时序集中度。推导了包含能量、空间、时序3个因素下的微震集聚度计算公式,并进行了推广性验证。进一步采用该公式计算了亭南307工作面初次来压和周期来压期间的微震事件的微震集聚度,并分析了较大微震集聚度的事件所在层位的分布规律。研究结果表明直接顶的微震事件频次较大,但其大部分事件的微震集聚度大小不如基本顶,较大微震集聚度的事件更能反应矿山压力变化规律。初次来压和周期来压前后基本顶微震集聚度均呈现先上升后下降的规律。该指标突破了能量频次、空间频次等单一性分析,可以在一定程度上降低直接顶和基本顶中微小微震影响,更加直观地揭示了矿压显现的整体规律。微震集聚度具有一个指标多个维度的特征,不仅可以在矿山进行应用,还可以推广到隧道、水电站、金属矿等所有应用微震的岩土领域,具有重要的现场意义。

     

    Abstract: Microseismic monitoring has become an important means of mine safety identification and early warning, but the spatiotemporal evolution mechanism based on microseismic and its correlation with rock activity still need to be solved urgently. At present, microseismic analysis mostly uses multiple indicators or comprehensive evaluation. However, the connection between different indicators is weak, resulting in a weak correlation or even contrary to the identification results. The massive microseismic events with different energy in the working face are all caused by rock fracture and rotary motion. Many small events are derived from the same source, so there is a certain correlation between microseismic events. Therefore, it is of great significance to study the microseismic spatiotemporal evolution of based on the microseismic index with rich connotations. Based on this, a microseismic spatial-temporal evolution index is proposed, which includes three dimensions of space, one dimension of energy and one dimension of time, a total of five dimensions: microseismic clustering degree. This index indicates that the rock stratum is often accompanied by large microseismic energy or spatial aggregation degree and time clustering when it breaks and rotates. The calculation formula of microseismic clustering degree under three factors including energy, space and time series is derived, and the generalization verification is carried out. Furthermore, the formula is used to calculate the microseismic clustering degree of microseismic events during the initial mine pressure and periodic mine pressure of the TingNan 307 working face, and the distribution law of the layer where the events with larger microseismic clustering degree are located is analyzed. The results show that the frequency of microseismic events in the immediate roof is larger, but the clustering degree of most events is not as large as that of the main roof. Events with high microseismic clustering degree can better reflect the variation law of mine pressure. Before and after the initial pressure and periodic pressure, the microseismic clustering degree of the main roof increased first and then decreased. This index breaks through the single analysis of energy frequency and spatial frequency, which can reduce the influence of microseismic in caving zone, and more intuitively reveal the overall law of mine pressure appearance. Microseismic clustering degree has the characteristics of one index containing multiple dimensions. It can not only be applied in mines, but also be extended to all geotechnical fields such as tunnels, hydropower stations, and metal mines, which have important field significance.

     

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