The distribution of earthquake multiplets beneath the southwest Pacific

Earthquakes beneath the southwest Pacific occur from the surface down to 700 km depth. Teleseismic waveforms created by some of these earthquakes are almost identical. We investigate Tonga–Kermadec and Vanuatu subduction zone earthquake P-coda waveforms using a cross-correlation technique and hierarchical clustering algorithm in order to determine the origin of waveform similarity and the distribution of earthquakes producing similar waveforms.We show that scatterers forming the majority of power in the P-wave coda are localised around the receiver. As a result, waveform similarity provides a much weaker constraint on source separation than in local studies. Waveform similarity can provide stronger constraints on focal mechanism.Most earthquake multiplets within the Tonga–Fiji–Kermadec Wadati–Benioff zone are found at depths between 0–60 km and 520–620 km. A significant proportion of all deep-focus events in south Pacific subduction zones have waveforms similar to those of at least one other event. Relative relocation of events within the largest identified multiplet reveals a planar zone of seismicity sub-parallel to the nodal plane of a related centroid moment tensor solution.Groups of earthquakes with similar waveforms remain active on at least the 14-year recording timescale. We equate this to repeated rupture on single or closely related shear systems within the subducting slabs.     

Detection of earthquake clusters on the basis of waveform similarity: An application in the monferrato region (Piedmont, Italy)

In August 2000 and July 2001 two seismic sequences, characterized by mainshocks with Ml (local magnitude) respectively 5.1 and 4.8, occurred in the Monferrato region (Italy). The regional seismic network of North-western Italy (RSNI) recorded more than 250 foreshocks and aftershocks. The routine locations, obtained from the Hypoellipse code, show a seismic activity concentrated in a circular area, of a radius of about 15 km, located near Acqui Terme, and randomly distributed in depth. Location errors, due to an uneven azimuthal station distribution of the regional seismic network, prevent recognition of the geometry of the active zone. Waveform analysis revealed the presence of several multiplets. In order to discriminate and successively relocate them, an automatic cross-correlation procedure was applied. Normalized cross-correlation matrixes, for the RSNI stations which recorded almost 90% of considered events, on the basis of a signal to noise ratio analysis, were computed using only S wave time windows. The use of a relocation procedure, based on the double-difference method which incorporates ordinary absolute travel-time measurements and/or cross-correlation differential travel-times, allowed us to overcome the constraints of the uneven distribution of stations giving a quite different frame of seismicity. The improved locations showed that the seismic activity is mainly arranged along a NE-SW oriented volume, at a depth range of 8–20 km, involving the basement crystalline units. This orientation is confirmed by the analysis of the focal mechanisms: most focal solutions show a strike slip component with one of the nodal planes consistent with the main orientation of the seismic events.     

Perspectives of Cross-Correlation in Seismic Monitoring at the International Data Centre

We demonstrate that several techniques based on waveform cross-correlation are able to significantly reduce the detection threshold of seismic sources worldwide and to improve the reliability of arrivals by a more accurate estimation of their defining parameters. A master event and the events it can find using waveform cross-correlation at array stations of the International Monitoring System (IMS) have to be close. For the purposes of the International Data Centre (IDC), one can use the spatial closeness of the master and slave events in order to construct a new automatic processing pipeline: all qualified arrivals detected using cross-correlation are associated with events matching the current IDC event definition criteria (EDC) in a local association procedure. Considering the repeating character of global seismicity, more than 90 % of events in the reviewed event bulletin (REB) can be built in this automatic processing. Due to the reduced detection threshold, waveform cross-correlation may increase the number of valid REB events by a factor of 1.5–2.0. Therefore, the new pipeline may produce a more comprehensive bulletin than the current pipeline—the goal of seismic monitoring. The analysts’ experience with the cross correlation event list (XSEL) shows that the workload of interactive processing might be reduced by a factor of two or even more. Since cross-correlation produces a comprehensive list of detections for a given master event, no additional arrivals from primary stations are expected to be associated with the XSEL events. The number of false alarms, relative to the number of events rejected from the standard event list 3 (SEL3) in the current interactive processing—can also be reduced by the use of several powerful filters. The principal filter is the difference between the arrival times of the master and newly built events at three or more primary stations, which should lie in a narrow range of a few seconds. In this study, one event at a distance of about 2,000 km from the main shock was formed by three stations, with the stations and both events on the same great circle. Such spurious events are rejected by checking consistency between detections at stations at different back azimuths from the source region. Two additional effective pre-filters are f–k analysis and F _prob based on correlation traces instead of original waveforms. Overall, waveform cross-correlation is able to improve the REB completeness, to reduce the workload related to IDC interactive analysis, and to provide a precise tool for quality check for both arrivals and events. Some major improvements in automatic and interactive processing achieved by cross-correlation are illustrated using an aftershock sequence from a large continental earthquake. Exploring this sequence, we describe schematically the next steps for the development of a processing pipeline parallel to the existing IDC one in order to improve the quality of the REB together with the reduction of the magnitude threshold.     

利用重复地震研究山东乳山地区地壳介质波速变化

利用2013年10月—2015年6月山东乳山震群的地震波形资料,基于距离乳山震群最近的3个台站所记录的地震波形互相关系数c≥0.9的地震即为重复地震的原则,识别了乳山震群的重复地震．利用波形互相关时延法,计算分析了文登台和招远台这两个固定台站的走时差随时间的变化特征．结果表明:乳山震群的地震相似性很好,且震中位置较为集中,重复地震的时间跨度较大,有利于提高观测结果的时间分辨率;乳山震群中3次M_S＞4.0地震前均出现了短期的走时差低值异常现象,反映了乳山震群震源区在中强震前会出现短期地壳介质速度明显升高的过程,可以为该区域的中强震预测提供一定依据．      

基于机器学习算法的银川台阵资料自动化震相分析和定位

近年来快速发展的机器学习算法显著提高了震相拾取的精度和效率.采用卷积神经网络和递归神经网络的震相识别方法对银川台阵2019年6～7月的连续波形数据进行事件检测和P、S震相拾取,并通过快速震相关联和事件定位得到了银川地区较全的地震目录.结果表明,当震相数小于10时,虽然可以检测出较多事件,但分布呈弥散状,与区域地震活动特...     

基于深度学习卷积神经网络的地震波形自动分类与识别

发展高效、高精度、普适性强的自动波形拾取算法在地震大数据时代背景下显得越来越重要.波形自动拾取算法的主要挑战来自如何适应不同区域的不同类型地震事件的分类与筛选.本文针对地震事件-噪音分类这一问题,使用13839个汶川地震余震事件建立数据集,应用深度学习卷积神经网络(CNN)方法进行训练,并用8900个新的汶川余震事件作为检测数据集,其训练和检测准确率均达到95%以上.在对连续波形的检测中,CNN方法在精度和召回率上优于STA/LTA和Fbpicker传统方法,并能找出大量人工挑选极易遗漏的微震事件.最后,我们应用训练好的最优模型对选自全国台网的441个台站8天的连续波形数据进行了识别、到时挑取及与参考地震目录关联,CNN检出7016段波形,用自动挑选算法拾取到1380对P,S到时,并与540个地震目录事件成功关联,对1级以上事件总体识别准确率为54%,二级以上为80%,证明了CNN模型具有泛化能力,初步展示了CNN在发展兼具效率、精度、普适性算法,实时地震监测等应用上具有巨大潜力.     

A real time processing system of seismic waves using personal computers — Function and characteristics

Conclusions The real-time processing system of CTSN performs following: A/D conversion; automatic event detection; event data saving; automatic measure of P and S arrivals; event location and print out the calculated results. It is corrected at ny moment by using the off-line system. Since December 1993, this system has been operating normally in the CTSN. More than 4 000 earthquakes have been recorded in the system. It has high accuracy in automatic picking P and S arrivals. The location of the earthquakes determined by on-line system are close to those given in published catalogues which are determined by manual procedure. This system can finish locate event in three minutes. It also gives satisfactory epicenter locations for distant events by inputting manually S arrivals in the off-line system. The operation of this system had brought the technical superiority of the CTSN. It not only reduces the labor intensity and simplifies the working procedure, but also makes our research facility into the superior ranks in this field of our country. In conclusion, the real-time processing system of seismic wave provides technical support for the daily requirements of monitoring seismic activity as well as a lot of digital waveform data used seismic research in Sichuan area. This subject is sponsored by the Scientific and Technical Committee of Sichuan Province.     

2017年3月渤海地震序列微震检测与发震构造分析

地震序列发震构造研究是区域地震活动性和地震危险性分析的重要基础.2017年3月渤海海域发生地震序列活动,该序列发生在郯城-庐江断裂带与张家口-渤海地震带的交汇部位,区域构造较为复杂.然而在渤海海域,连续运行的固定地震监测仪器难以布设,导致地震监测能力相对较弱.本文首先采用模板匹配方法对序列遗漏地震进行检测,再使用波形互...     

利用sPn震相测定芦山MS7.0级地震余震的震源深度

利用南北地震带南段密集流动地震台阵的观测数据,采用波形互相关方法拾取Pn波走时,应用滑动时窗相关法识别sPn震相,通过sPn与Pn震相之间的走时差测定了芦山地震序列中28个M_L4.0级以上余震的震源深度.结果表明,震源深度集中在10~20 km范围内,垂直余震带的北西-南东向震源深度剖面揭示,余震分布表现出西深东浅的特点,倾角大约为39°.这些余震在空间上具有较好的线性分布特征,推测可能发生在与主震有关的破裂面上或邻近位置,由此推测主震的破裂面倾角大约为39°.根据余震的空间分布特征,认为芦山地震的发震断层并非双石-大川断裂,可能是其东侧的一条隐伏断层.     

基于谱元法数值模拟研究地震判定准则

本文以宁夏区域地震台网为例,分析了波形互相关法在判定重复地震中可能存在的问题并讨论了相应的处理方法,通过构建三维非均匀体模型并利用谱元法数值模拟地震波的传播,统计了不同台站观测到的地震对波形互相关系数的分布,进一步研究了互相关系数与非均匀体性质及震源机制解之间的关系。结果表明:针对宁夏区域地震台网,利用波形互相关法判定重复地震比地震定位方法更有效;互相关系数在不同台站的取值与震源附近三维非均匀体强度和直达波与尾波的振幅比有关,对于相同的震源间距,较弱震源、较弱非均匀体或者较强振幅的直达波均会导致波形互相关系数变高,因此应选取更高的互相关系数阀值来判定重复地震。宁夏区域地震台网平均台间距为30—50 km,通过选取直达波较弱的台站或只截取尾波窗口计算互相关系数并设定较高的阀值,利用波形互相关法可有效地判定M_L1.0—3.0重复地震,进而为重复地震的监测与研究提供依据。      

利用重复地震观测重庆巫山地区地壳介质变化

利用波形互相关技术,对重庆数字地震台网记录的巫山地区90次地震波形资料进行相关计算,识别出24对同时被2个地震台站记录且各台波形互相关系数不小于0.8的重复地震对;利用射线追踪方法,对巫山地区重复地震位置做归一化处理,得到所选台站记录地震P波走时差变化,结果显示,在2013年重庆巫山M_L 3.7地震前,建坪、双龙、荆竹地震台记录到该地区短期地壳介质速度有明显升高现象。     

内蒙古数字化记录近震震相特征

对内蒙古测震台网2008年以来速报的346次地震（包括天然地震与爆破、塌陷）进行统计,以典型震例,分区域、分类别总结震相特征。在此基础上,讨论利用典型震例与波形互相关性在未来地震定位与震相精确识别方面应用的可能性,及利用非常规震相（sPn震相）准确测定震源深度的应用前景。通过以上分析,以期进一步提高内蒙古地震速报和编目工作质量。     

波形相关意义“重复地震”研究综述

波形相关意义的“重复地震”在自然界中普遍存在,其数量远远超过我们的预期。近年来由于数字地震观测技术的普及和发展,有关“重复地震”的研究引起越来越多的关注,目前“重复地震”研究已被广泛应用于检测地壳介质性质变化、评估地震台网的定位精度、估计地震“复发”的概率和断层深部滑动速率的估算方面的估计;在提高定位和震相识别精度、断层结构、震源物理及地震预测研究等方面也都显示出值得关注的应用潜力。本文对有关“重复地震”的最新研究及应用成果进行了总结和归纳。     

重庆地区重复地震识别及在数字地震台网定位评价中的应用

利用重庆数字地震台网2010年1月至2017年12月的地震波形资料和观测报告,选出5个研究区1 251个M_L≥1.5地震进行波形互相关计算,识别出358对同时被2个地震台站记录且各台波形互相关系数(cc)不小于0.8的重复地震对,涉及342个地震事件,约占地震总数的27%。将筛选出的重复地震对用于定量判断地震目录中震相拾取误差及评估台网定位精度,结果显示:重庆数字地震台网的垂直定位误差约为3 km,水平定位误差约为5 km,Pg、Sg震相拾取误差分别为0.5 s和0.7 s;其中武隆区地震定位和震相拾取精度最高,綦江区最低。     

The Precursory Significance of Cumulative Slip of Repeating Earthquake Sequences Prior to Moderately Strong Earthquakes— A Case Study of Four Remarkable Earthquake Sequences of HaichengXiuyan

The Haicheng-Xiuyan region is an earthquake-prone area in Liaoning Province where earthquake sequences frequently occur and is regarded as the regional seismic window. In this area we found many earthquake events with the highest waveform similarity in the records of the same station from some remarkable seismic sequences,namely repeating earthquake sequences. In principle,rupture areas of the repeating events overlap with each other and are most closely located. Therefore these events may reflect the seismic process near the earthquake fault. In this paper, we identified four remarkable earthquake sequences of Haicheng-Xiuyan by waveform cross-correlation. The result shows that the cumulative slip of repeating earthquakes is related to moderately strong earthquakes,among which the Xiuyan M_S5. 4 foreshock sequence has the strongest and most apparent pre-shock accelerating-like slip behavior.     

2013年3月涿鹿微震群遗漏地震事件检测和发震构造分析

震群活动时,短时间发生大量地震,不同地震事件的记录波形相互交叠影响,易造成地震目录的遗漏,对震群发震构造分析等研究带来不利的影响.本文针对2013年3月3日至5日在河北涿鹿发生的微震震群,利用匹配滤波技术,以地震台网观测目录所记录地震事件的波形为模板,在连续波形记录中搜索与模板相似的信号,从而检测台网目录遗漏的地震.利用波形互相关标定新检测到地震事件的P波和S波到时,进而对其震中位置和震级做出估计.计算结果显示,通过互相关扫描检测到52个地震台网常规分析遗漏的地震,约为地震目录给出的45个事件的1.16倍.检测到的遗漏地震震级估算为M_L0.1~0.9,通过震级-频次统计分析,加入遗漏地震后地震目录的完整性在M_L0.3~0.8范围内有较明显的改善.根据地震事件精定位结果,推测此次震群的发震构造为北西走向倾角较大的断层,施庄断裂为发震构造的可能性较大.     

一种低频地震事件的检测方法在汶川地震和芦山地震前的初步应用

本文发展了一种单台检测低频地震事件的方法, 并用其检测2008年汶川M_S8.0地震、 2013年芦山M_S7.0地震震前的低频事件。 使用汶川地震、 芦山地震前周边的宽频带台站数月的垂直向连续波形, 经过2~8 Hz带通滤波、 窗长为10 s的包络平滑、 窗长为20 min的中值滤波, 去除近场天然地震及远场大震与低频噪声的影响后, 发现这两个大地震前有少数台站在连续数天的时间内, 出现持续时间长(数十分钟到数小时)、 包络中值明显大于背景噪声的现象, 其波形记录及包络特征与非火山震颤(NVT)的波形记录及包络特征具有较好的相似性, 我们认为这是汶川地震和芦山地震前的疑似慢地震事件。 初步应用表明, 本文所用的方法对于从宽频带连续波形资料中提取NVT信号是可行的。     

Repeating earthquakes recorded by Liaoning Regional Seismograph Network

In the list of ’repeating pairs’ or ’doublets’ of earthquakes in China identified by Schaff and Richards using tele-seismic waveform cross-correlation, there were 23 repeating pairs located in Liaoning Province. In this study the waveforms of these events were cross-correlated using records from Liaoning Regional Seismograph Network (LRSN), and the ’repeating events’ in the sense of regional waveform cross-correlation were obtained. The result was compared with that of Schaff and Richards and was used for the assessment of the seismic phase picking and event location practice of LRSN. The result shows that ’repeating events’ in the sense of teleseismic waveform cross-correlation and those in the sense of regional waveform cross-correlation have significant difference, al-though with some overlap. However, the overall assessment of the location accuracy and the phase pick errors of LRSN by using these two sets of ’repeating events’, respectively, provides similar results, while ’repeating events’ in the sense of regional waveform cross-correlation seem to be better performing in such an assessment. With the assumption that the separation between the ’repeaters’ be less than 1 km, the uncertainty in routine earthquake location of LRSN is estimated to be below 5 km, with the average of 2 km. In the observational bulletins of LRSN the time error in phase picking is estimated to be within ±1s for 94% Pg readings and for 88% Sg readings.     

基于小波包分形和神经网络的地震与岩溶塌陷识别

本文以近年来广西地震台网中心记录的天然地震和岩溶塌陷为例,尝试利用基于小波包的分形和径向基函数神经网络技术对这两类事件的波形进行识别,以期有效地识别地震与岩溶塌陷。结果表明,基于小波包分形与神经网络相结合的事件识别方法对天然地震和岩溶塌陷事件的识别率高达89.5%,可作为识别天然地震与岩溶塌陷的一个有效方法。      

基于卷积神经网络的地震波形智能识别研究

随着世界上多个国家和地区的地震预警系统投入运行,误报和漏报等问题逐渐突显,特别是将标定以及强干扰波形误识别为大震事件,快速、精确地区分地震与其他波形是一个难题。针对于此,该研究提出了基于卷积神经网络地震波形智能识别方法。首先收集并处理了2012—2017年中国境内福建以及周边邻省共683个地震和478个爆破事件,并对这些样本筛选、截取和基线校正等预处理,共得到了27 500条三通道波形。在此基础上,构建了3 s波形输入的卷积神经网络模型(SW-CNN)。结果表明：模型对地震、噪声、爆破和异常波形的识别率分别为97.9、99、99.2和99.3%。相比于人工手动分类识别,该模型更省时和更稳定,为地震预警目前所面临的问题提供了一个新的解决方法。