A novel technique for automatic seismic data processing using both integral and local features of seismograms
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摘要: 提出一种基于信号整体与局部特征的地震数据自动处理新方法， 该方法不同于以往仅采用包络线互相关来直接检测事件. 新方法依然按照检测、 识别、 关联和定位等4个步骤进行处理， 但在进行单个震相信号检测的同时， 也检测信号波列并利用其包络线特征来识别和关联震相. 文中详细阐述了数据处理过程中如何定义一个波列及抽取和应用其特征. 相关的数据处理技术目前已成功应用于区域台网的日常数据处理分析中. 作为例子， 给出了对新疆区域台网连续16天数据进行测试处理的结果. 实际应用结果表明， 这种新方法可以大幅度降低自动处理结果的误检、 漏检率， 在实际应用中具有很好的前景.Abstract: Reliable automation of data processing is of great significance for modern seismic monitoring. A novel technique for automatic seismic data processing which utilizes both integral and local features of seismograms was presented in this paper. However, unlike some previous efforts which seek to use envelope cross-correlation to detect seismic events directly, our technique keeps to follow the DIAL approach, i.e., by steps of signal detection, phase identification, association and event localization. However, in addition to detect signals corresponding to individual seismic phases, the new technique also detects continuous wave-trains and explores their envelope features for phase type identification and signal association. More concrete ideas about how to define wave-trains and combine them with various detections as well as how to measure and utilize their features in the seismic data processing were expatiated in the paper. This approach has been applied to the routine data processing of regional seismic networks for several years, and as an application example, here were presented test results for a 16 days' period using data from the Xinjiang regional seismic network. Practical application results show that the new technique can reduce both false alarm and missed event rate significantly and has good application prospects.
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图 1 地震信号整体特征及其与信号检测的关系
Figure 1. Fig.1 Integral features of seismogram and their relationship with individual signal detections
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图 2 波列持续状态计算方法示意图
Figure 2. Illustration of the method to calculate wave-trains triggered state
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图 3 根据信号检测的到时及各检测信号的峰值位置和峰值大小推测信号包络线形状
Figure 3. Inferred envelope shape of the seismogram in Fig.1 using arrival times and the integral characterization parameters defined in this study
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图 4 一次区域性地震在不同震中距台站的三分向信号记录
发震时间： 2010-06-01 04:29:29， 震中位置： 38.4°N、 74.0°E，震源深度： 156 km， 震级： ML3.1． 为提高在远距离台站上的信噪比， 波形全部经过4—8 Hz带通滤波. 图中的P、 S线分别对应于P波和S波的理论到时
Figure 4. Typical three-component seismograms recorded at regional distances
The waveforms are from an earthquake of ML3.1 occurred at 04:29:29 on 1 June, 2010. The epicenter of this earthquake is (38.4°N, 74.0°E) with focal depth 156 km. The waveform columns from left to right are 4—8 Hz band-pass filtered waveforms on vertical, south-to-north and west-to-east component respectively. The solid lines marked by P and S stand for theoretical arrival times of P and S
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图 5 一个实际应用的同时基于信号和波列检测及其特征参数的区域台网数据自动处理软件流程示意图
Figure 5. The flow chart of a practical data processing system for regional seismic networks using both integral and local features of seismic signals
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图 6 同时基于信号整体与局部特征的区域性P、 S震相对搜索方法示意图
Figure 6. Illustration of the method to search for regional P， S pairs by integral and local features together
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图 7 自动区分Sn和Lg原理示意图
Figure 7. Illustration of the method for automatic identification of phases Sn and Lg
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图 8 测试台网(新疆)台站分布
Figure 8. Locations of seismic stations (denoted by triangles) of Xinjiang seismic network
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图 9 本文方法对新疆局地震目录中2010年6月1—16日不同震级范围内地震事件检测结果的统计分析
Figure 9. Statistic result of automatically detected rate for events listed in the Xinjiang seismic events satalog in 1—6 June, 2010
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图 10 典型区域性事件自动处理结果实例
(a) 2010-06-09 10:58:59新疆和静ML2.6地震， 新疆局地震目录给出震中位置为42.33°N、 84.82°E， 自动处理结果误差约11 km； (b) 2010-06-09 16:01:08阿富汗兴都库什山区mb3.4地震， IDC REB中给出的震中位置为35.89°N、 69.57°E， 自动处理相对定位误差约31 km. 对每个事件， 图中显示的是最近的15个台站经0.5—5 Hz带通滤波后的垂直分量波形， 上面标出了对应台站的代码名称、 震中距及自动处理过程中实际触发的各个信号检测的到时位置及震相名称， 其中正体字母表示最终关联给相应事件的定义震相， 斜体字母代表未关联或未定义检测的震相， 其中N表示被识别为噪声的检测．
Figure 10. Examples of automatically processing results for two regional events
(a) Seismograms of the southern Xinjiang ML2.6 earthquake occurred at 10:58:59 on 9 June 2010. The epicenter is (42.33°N, 84.82°E) in Xinjiang seismic events catalog (XJEC), our automatically determined epicenter is 11 km away from it. (b) Seismograms of an mb3.4 earthquake occurred in the Hindu Kush region, Afghanistan, at 16:01:08 on 9 June 2010. For the epicenter of this earthquake is outside of Xinjiang seismic network, no information is given in the XJEC. However, the IDC REB epicenter of this earthquake is (35.89°N, 69.57°E)， and our automatically determined result is 31 km away from it. For each event, 0.5—5 Hz band-pass filtered vertical component seismograms from the 15 closest stations are displayed. For each seismogram, respective recording station and epicentral distance are given at its left side, and all detections triggered within the displayed waveform time window are added, where the labels marked by upright letters are automatically associated defining phases for corresponding event and the labels marked by italics are unassociated ones. N stands for detections identified as noise by the software
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图 11 新疆局地震目录中ML≥2.0地震自动定位结果与人工编目结果的比较(a)及震中相对误差分布(b)空心圆为新疆局地震目录给出的震中位置， 实心圆为本文自动定位结果， 实线相连表示是同一个事件
Figure 11. (a) Comparison of automatically determined epicenters in this study (red dot) with those in Xinjiang seismic events catalog (open blue circle) for events of ML≥2.0, wherer the marks linked together by short lines stand for results of same events; (b) Distribution of relative location errors between them
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