Monitoring and statistical analysis of mine subsidence at three metal mines in China
Monitoring and statistical analysis of mine subsidence at three metal mines in China
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我国三个金属矿山矿井沉陷监测与统计分析
DOI：
10.1007/s10064-018-1367-6
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发表时间：
2019-09-01
影响因子：
4.2
通讯作者：
Xu, Jiamo
中科院分区：
文献类型：
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作者：
Hui, Xin;Ma, Fengshan;Xu, Jiamo
煤矿塌陷是我国的一种区域性地质灾害。为了评价幂律是否描述了矿井沉陷的频率-规模统计，对于地震和洪水，我们研究了中国三个金属矿山（金川镍矿，三山岛金矿，井儿泉镍矿）的矿井沉陷的频率-规模统计。这些地雷的数据集包括1，088、345和101个全球定位系统监测点，监测期分别为14.5、4和3.5年。虽然这些矿山有不同的地质和水文环境，采矿方法和应力场，他们的非累积频率大小分布的沉降和隆起事件可以用幂律来描述。这三个矿井的沉降幂律指数范围为1.20 - 1.67、1.49 - 1.94和1.01 - 1.17，平均值分别为1.46、1.76和1.09。每个矿的幂律标度分别在2至455 mm、2至566 mm和2至277 mm的范围内有效;标度与幂律指数呈正相关。具有不同时间尺度的沉降事件的频率-大小统计显示出相同的幂律依赖性。隆升事件的幂律行为与沉降事件相似。本文讨论了这种幂律行为及其内在机制、影响幂律指数的因素以及正常沉降事件和极端沉降事件之间的阈值。我们认为，矿山塌陷事件的幂律分布反映了塌陷系统的尺度不变性。这对沉降灾害评价和沉降事件预测具有重要的实际应用价值。
Mine subsidence is a regional geological hazard in China. To evaluate whether a power law describes the frequency-size statistics of mine subsidence, as for earthquakes and floods, we studied the frequency-size statistics of mine subsidence at three metal mines in China (Jinchuan Nickel Mine, Sanshandao Gold Mine, and Jingerquan Nickel Mine). Data sets for these mines consisted of 1088, 345, and 101 Global Positioning System (GPS) monitoring points, covering monitoring periods of 14.5, 4, and 3.5 years, respectively. Although these mines had different geological and hydrological settings, mining methods, and stress fields, their noncumulative frequency-size distributions for subsidence and uplift events can be described using power laws. The subsidence power-law exponent for these three mines ranged from 1.20 to 1.67, 1.49 to 1.94, and 1.01 to 1.17, with mean values of 1.46, 1.76, and 1.09, respectively. The power-law scaling for each mine was valid over the range from 2 to 455 mm, 2 to 566 mm, and 2 to 277 mm, respectively; scaling was positively correlated with the power-law exponent. The frequency-size statistics for subsidence events having different time scales showed an identical power-law dependence. The power-law behavior of uplift events was similar to subsidence events. This power-law behavior, its underlying mechanisms, factors influencing the power-law exponent, and the threshold between normal and extreme subsidence events are discussed herein. We conclude that the power-law distribution of mine subsidence events reflects the scale invariance of the subsidence system. This has important practical applications for subsidence hazard assessment and subsidence event prediction.