| 四川省理县西山村滑坡运动变形过程中的微震研究 |
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| 引用本文： | 盛敏汉,储日升,危自根,包丰,郭爱智.四川省理县西山村滑坡运动变形过程中的微震研究[J].地球物理学报,2018,61(1):171-182. |
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| 作者姓名： | 盛敏汉 储日升 危自根 包丰 郭爱智 |
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| 作者单位： | 1. 中国科学院测量与地球物理研究所大地测量与地球动力学国家重点实验室, 武汉 430077;2. 中国科学院大学, 北京 100049 |
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| 基金项目： | 国家重点基础研究发展计划（2013CB733203），国家自然科学基金优秀青年基金（41322027），国家自然科学基金面上项目（41474049，41661164035）联合资助. |
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| 摘 要： | 西山村滑坡位于地震活动性剧烈的龙门山地区，这个区域有大量的滑坡在汶川地震中被触发，此后西山村滑坡发生持续变形.为了监测该滑坡体的运移和局部破裂产生的微弱的地震信号，由微震事件获取滑坡滑动和变形模式，2015年八月底至十一月底，我们在滑坡上布置了30套地震仪.首先通过信号到时和波形特征把滑坡上的微震信号从人类活动产生的信号和滑坡体以外的区域地震信号区分开来.然后以识别到的微震波形为模板，用滑动时窗互相关的方法匹配其他的微震事件.结果表明，96个微震事件能被30个台站都记录到.通过对这些事件的定位，我们发现大部分（80个）能被所有台站记录到的事件发生在滑坡的底部，其他的少部分（16个）发生在滑坡的顶部.这意味着有相当多的能量积聚在滑坡的顶部和底部，而滑坡的底部则更活跃.除此外，在滑坡的中部有较多更微弱的事件被周围的部分仪器记录到.基于这些微震事件的位置，我们发现四个辐射地震信号的不稳定区域和钻孔监测到的不稳定区域比较吻合.这些辐射地震信号的不稳定区域应该和滑坡体的运动和内部变形相关.由此表明，地震学方法也是监测滑坡的变形的有效手段，是现有监测手段的有力补充.
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| 关 键 词： | 滑坡变形监测 微震检测 模板匹配 滑坡内部变形 |
| 收稿时间： | 2017-06-16 |
Study of microseismicity caused by Xishancun Landslide deformation in Li county,Sichuan Province |
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| SHENG MinHan,CHU RiSheng,WEI ZiGen,BAO Feng,GUO AiZhi.Study of microseismicity caused by Xishancun Landslide deformation in Li county,Sichuan Province[J].Chinese Journal of Geophysics,2018,61(1):171-182. |
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| Authors: | SHENG MinHan CHU RiSheng WEI ZiGen BAO Feng GUO AiZhi |
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| Institution: | 1. State Key Laboratory of Geodesy and Earth's Dynamics, Institute of Geodesy and Geophysics, Chinese Academy of Sciences, Wuhan 430077, China;2. University of Chinese Academy of Sciences, Beijing 100049, China |
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| Abstract: | The Xishancun Landslide is located in the Longmenshan Mountains where the 2008 Wenchuan earthquake occurred. The 2008 Wenchuan earthquake triggered a large number of landslides in this region. Since then, the Xishancun Landslide is continuously deforming. In order to monitor slidequakes generated by the slope movement and the internal fracturing of the rock mass and to understand slip and strain pattern of the landslide, a seismic network with 30 seismometers was deployed on the landslide in the autumn of 2015. Firstly, we distinguish signals of slidequakes from those generated by human activities and local earthquakes through their onsets and waveform characteristics. Then we use the sliding-window cross-correlation method based on waveform matching to identify other slidequakes. We find 96 slidequakes recorded by all seismometers. We relocate the slidequakes using a grid-search algorithm by minimizing travel-time residuals. 80 events are located on the foot of the landslide while the others are located on the head, which indicates that considerable energy is accumulated in the foot and head of the landslide. Besides large slidequakes, there are smaller events which are only recorded by a few nearby stations. These small slidequakes occur in middle part of the landslide where less energy is released. Based on the distribution of those slidequakes, we find four seismically unstable regions which agree well with distinct deformation areas obtained from borehole data. The distribution of those slidequakes might be related to the internal structure and the movement of the landslide, indicating that seismic method is a useful tool to monitor landslide deformation and a powerful complement to other means. |
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| Keywords: | Monitoring landslide deformation Slidequake detection Template matching Landslide internal deformation |
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