国家数字地震台网中心实时处理及大地震速报软件系统

国家数字地震台网中心实时系统是国家数字地震台网的重要组成部分。其软件系统主要功能有: 实时收集、存储47个国家数字地震台的地动波形数据,进行地震事件实时检测、自动定位、报警、人机结合精确定位。可速报国内M_S≥5.0、邻区M_S≥6.0、世界范围M_S≥7.0地震的震源位置及震级。软件系统的主要特点: 双机热备份,使用多种编程技术,具有实时性好、可靠性、稳定性高。提出地震定位计算法的几何背景,双曲线与圆相交地震定位法等。丰富和发展了地震定位理论,解决了初始定位长期得不到解决的问题,在全球大地震速报工作中取得了很好的效果。人机交互系统,操作简便,用图形和数字给出丰富的信息,有助于分析地震波形和地震定位结果,是一个计算机辅助思维、分析系统。     

Non-linear methods for event location in a global context

Directed search methods in four-dimensional hypocentre space do not require the differentiation of travel times and are particularly suitable for the use of information from multiple seismic phases including joint use of primary and depth phases (e.g. pP) for a reference model such as a k135. These approaches can be used with a wide range of measures of misfit between observed and estimated times. A very effective method of this class is the use of the neighbourhood algorithm that allows all previous hypocentre estimates to be employed to estimate the shape of the misfit surface. When used with a robust measure of misfit such as the sum of the absolute values of the residuals (L1 norm), the neighbourhood algorithm provides rapid convergence, and a measure of the uncertainty in the hypocentral estimate from the concentration of the points with low misfit in four-space. Such a procedure is well suited to the first pass analysis of observations since it is not distracted by occasional readings associated with other events. Phase association can then be improved and a more conventional procedure used to provide error ellipsoids around a well-defined depth.     

Application of 3D empirical travel times to routine event location

The unmodeled effects of lateral heterogeneity are a primary cause of event mislocation in routine methods. Approaches that account for the effect of lateral heterogeneity on travel times are commonly used in specialized studies, but some methods have recently been developed that are suitable for routine location. A variety of changes to the routine procedures have been suggested by other authors. These proposed changes are shown to be compatible to with the use of 3D travel time predictions. 3D empirical travel times are discussed in a routine context. This one step approach, based on direct use of a database of the most reliable previous observations, is shown to be suitable as an additional final step in routine procedures to give a supplementary high accuracy location. The empirical travel time approach is tested on a reference dataset of 155 ground truth events and shown to reduce epicentral mislocation by 45%. The approach is found to be particularly effective at reducing large mislocations. Improvement is demonstrated for every region represented in the dataset but particularly large improvements are shown for events in Europe, USA and Japan.     

Results of locating the IASPEI GT(0-5) reference events using the standard ISC procedures

The International Seismological Centre (ISC) is charged with production of the definitive global bulletin of seismic events, based on the most comprehensive set of parametric data collected from all over the world. Almost every event in the bulletin retains the original hypocentral solutions reported to the ISC by contributing agencies. In addition, where possible, the ISC computes its own solution, which is intended to be the most accurate where the data from several networks are used. It is because of the requirement for consistency of the bulletin over the years that the procedures used at the centre to compute hypocentres have remained rather conservative despite considerable advances made in the field of earthquake location.The ISC has developed and put into operation a new data management system. As a result, it is now possible to review and subsequently introduce more up-to-date methods of locating seismic events into the operations. The ISC Governing Council called for a workshop dedicated to location procedures, which was held during the 2005 IASPEI General Assembly in Santiago, Chile.To compare the accuracy of different location algorithms, a list of 156 reference events (IWREF) was selected prior to the workshop. The list includes geographically well distributed earthquakes and explosions with positions known with an accuracy of up to 5 km. It covers the period of 1954-2001 and includes all station readings and hypocentral solutions of different agencies available for these events in the ISC bulletin. Although the original ISC solutions are included, these may be different from the solution obtainable now due to changes in the ISC procedures over the years. This paper presents the results of relocation of these events using standard ISC location procedures as of 2005. These new ISC locations and analysis of their shifts with respect to reference locations present a benchmark for further improvement.     

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ML≥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。     

基于深度学习技术的地震实时流数据自动处理辅助工具开发

以JOPENS系统实时流接收为基础,应用Redis共享内存技术和近年来发展较快的深度学习震相自动识别技术,设计一套可7×24小时不间断稳定接收并实时识别连续地震流数据中P、S震相的系统,为地震台网实时数据处理提供一套辅助工具,并在福建省地震局测震台网128个台站的实时数据流上进行测试。该工具由Redis实时数据流共享模块与深度学习震相到时自动拾取、MSDP震相格式转换3个模块组成,可以实时接收并自动识别台网地震连续波形,生成P、S震相报告,并可导入MSDP人机交互工具进一步处理,在一定程度上可以减轻人工处理工作量。     

A novel technique for automatic seismic data processing using both integral and local feature of seismograms

A novel technique for automatic seismic data processing using both integral and local feature of seismograms was presented in this paper. Here, the term integral feature of seismograms refers to feature which may depict the shape of the whole seismograms. However, unlike some previous efforts which completely abandon the DIAL approach, i.e., signal detection, phase identification, association, and event localization, and seek to use envelope cross-correlation to detect seismic events directly, our technique keeps following the DIAL approach, but in addition to detect signals corresponding to individual seismic phases, it also detects continuous wave-trains and explores their feature 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 feature in the seismic data processing were expatiated in the paper. This approach has been applied to the routine data processing by us for years, and test results for a 16 days’ period using data from the Xinjiang seismic station network were presented. The automatic processing results have fairly low false and missed event rate simultaneously, showing that the new technique has good application prospects for improvement of the automatic seismic data processing.     

上海地震台阵对2004年12月26日印度洋地震的精确定位

通过对上海地震台网和上海地震台阵对2004年12月26日印度洋地震的定位结果与NEIC定位结果的比较，得出上海台阵定位结果比上海台网的定位结果更加精确。     

关于速报深远震问题的探讨

通过分析云南数字地震台网1998~2006年的地震记录资料,给出了该台网的深远地震震相记录特征,避免了常规分析方法中将深远地震误作浅源地震而带来的定位误差;利用1978年1月~2005年8月的深远地震记录资料,绘制了全球深远地震震中分布图,以作为地震速报的参考。     

A neural-tree-based system for automatic location of earthquakes in Northeastern Italy

A neural network system for P and S-picking and location of earthquakes in Northeastern Italy is described. It is applied to 7108 seismograms corresponding to 1147 earthquakes occurring in Northeastern Italy and surrounding area in the period 2000–2003. Its results are compared with two sets of manual picks and with the picks performed by the existing seismic alert system. The new system recognizes 89% and 67% of P and S arrival times, respectively, which allows locating 92% of the earthquakes. P and S-picks differ from the best available manual picks by 0.00 ± 0.07 s and 0.00 ± 0.18 s, respectively. The corresponding earthquake locations differ by −0.18± 0.77 km in longitude, 0.10± 0.62 km in latitude and 0.1± 2.0 km in depth. These results suggest its use for alert purposes and rapid production of preliminary bulletins.Considering a subset of picks that are common to all the available data sets, the absolute accuracy (i.e., the inverse of the standard deviation of differences between the estimated and the true, unknown arrival times) of each picking method is estimated. The best available manual data set has standard deviation 0.03 s for P waves and 0.07 s for S waves, while for the new system it is 0.06 s and 0.18 s for P and S waves, respectively.This paper has not been submitted elsewhere in identical or similar form, nor will it be during the first three months after its submission to Journal of Seismology.     

A real-time AI-assisted seismic monitoring system based on new nodal stations with 4G telemetry and its application in the Yangbi MS 6.4 aftershock monitoring in southwest China

A rapidly deployable dense seismic monitoring system which is capable of transmitting acquired data in real time and analyzing data automatically is crucial in seismic hazard mitigation after a major earthquake. However, it is rather difficult for current seismic nodal stations to transmit data in real time for an extended period of time, and it usually takes a great amount of time to process the acquired data manually. To monitor earthquakes in real time flexibly, we develop a mobile integrated seismic monitoring system consisting of newly developed nodal units with 4G telemetry and a real-time AI-assisted automatic data processing workflow. The integrated system is convenient for deployment and has been successfully applied in monitoring the aftershocks of the Yangbi M_S 6.4 earthquake occurred on May 21, 2021 in Yangbi County, Dali City, Yunnan in southwest China. The acquired seismic data are transmitted almost in real time through the 4G cellular network, and then processed automatically for event detection, positioning, magnitude calculation and source mechanism inversion. From tens of seconds to a couple of minutes at most, the final seismic attributes can be presented remotely to the end users through the integrated system. From May 27 to June 17, the real-time system has detected and located 7 905 aftershocks in the Yangbi area before the internal batteries exhausted, far more than the catalog provided by China Earthquake Networks Center using the regional permanent stations. The initial application of this integrated real-time monitoring system is promising, and we anticipate the advent of a new era for Real-time Intelligent Array Seismology (RIAS), for better monitoring and understanding the subsurface dynamic processes caused by Earth's internal forces as well as anthropogenic activities.     

多事件联合与双差地震定位方法研究：以朝鲜核试验定位为例

双差定位法（Double-difference Earthquake Location,简称DD）和多事件联合定位法（Joint Hypocenter Determination,简称JHD）是精确多事件定位中常用的两种方法.对震源机制相近的相邻事件,DD方法利用事件之间的相对到时精准地反演它们之间的相对位置,到时差数据能够利用波形互相关等方法直接测量,但是却无法准确地确定绝对位置;相比之下,JHD方法能够同时反演事件的绝对位置和台站走时校正值.结合两种方法的优点,本文提出一种混合定位方法,同时利用绝对到时数据和到时差数据准确地反演事件绝对位置和台站走时校正.本文利用模拟数据对该方法进行了验证并将其应用于朝鲜核试验定位,结果表明该方法能够有效减小走时计算误差所导致的定位误差.对于朝鲜核试验,相比单次事件+DD定位方法和JHD方法,相对Myers的定位结果定位偏差分别减小45.67%和40.00%.

     

大岗山水库地震台网水库诱发地震常规定位方法对比

采用MSDP软件中的单纯型、HypoSat和LocSat定位方法,从震源深度及残差等方面,对比分析2014年大岗山水库区域内123次M_L≥2.0地震的定位结果,选择适用于水库诱发地震的最佳定位方法,并以库区17次定点爆破事件为例,验证最佳定位方法的可靠性。结果认为,LocSat定位方法更适用于水库诱发地震。     

煤矿井下微震震源高精度定位研究

煤矿井下微震震源准确定位,对于动力灾害监测预警具有重要意义.由于微震震源需要通过井下传感器接收信息反演确定,传感器的安装位置限制于煤矿井下巷道周围,传感器沿巷道近平面的不合理布置将大大降低震源定位精度.针对由传感器信息反演震源位置引起的病态问题,本文提出了基于微震监测测点优化布置的震源高精度定位算法.首先通过计算系数矩阵条件数,判定病态问题;然后利用中心化法和行平衡法联合进行病态矩阵预处理.对预处理后的矩阵 A、b 利用L曲线法计算正则参数,结合Tikhonov正则化算法计算得到震源坐标正则解.研究结果表明,中心化法有效降低了矩阵数量级,行平衡预处理降低了病态条件数,预处理后Tikhonov正则解的震源坐标误差最小可以达到3.09 m,与预处理前的高斯消去解相比误差大大降低.通过上述优化处理,实现了井下受限空间微震监测震源高精度定位.     

The Characteristic Analysis and Seismic Triggering Study of the M6.2 and M6.1 Dayao Earthquake Sequences in 2003

INTRODUCTIONTheM6·2 andM6·1 earthquakes occurred successivelyin Dayao,Yunnan Province on July 21and October 16 ,2003 and bothinduced human casualty and economic loss to some extent .Adequatehistorical information reveals that ,earthquakes bigger thanM6·0 in Yunnan are distributed mainlyalong some active tectonic faults and seismic belts . Dayao and Yao an are in the Dianzhong tectonicblock andthere are noapparentfaultsthere(Su Youjing,2004) .Seismic activitylevel inthisregioniswea…     

高频GNSS实时地震学与地震预警研究现状

为实现从注重灾后救助向注重灾前预防转变,如何提高地震灾害监测预警和风险防范能力成为我们关注的重点.本文给出了国际上GNSS位移记录、强震动加速度记录、测震速度记录在地震预警中的应用现状,并总结了各自的特点,归纳出围绕高频GNSS地震学在震级与破裂过程实时反演中的几个需要进一步研究的关键问题：（1）引入北斗系统,基于高频GNSS（GPS/BDS）双系统的实时位移解算方法来提高实时单站位移解算精度,使实时解算精度达到厘米级;（2）开展强震仪加速度记录基线偏移校正研究,弥补地震近场GNSS站密度不足问题;（3）强震仪加速度记录与GNSS位移记录特点不同,开展强震仪加速度数据与GNSS位移数据实时融合处理研究,快速获得包含丰富地震形变和速率的波形数据;（4）测震学方法可快速估算震级,但是在强震发生时会出现震级饱和现象,造成震级估算偏低.需要开展基于GNSS位移时间序列的多种方法相结合的实时震级估算方法研究,通过与地震学方法比较和结合,来得到精度高、计算快的震级估值算法;（5）基于高频GNSS、断层初始模型快速选取、断层尺度、参数自适应调整是快速判断断层破裂方向的基础,在断层破裂过程自适应准实时反演算法方面需要进一步加强.通过国内外研究现状调研、分析,表明基于高频GNSS地震学的震级快速确定、震源破裂过程准实时反演算法的发展将对我国地震预警系统从"二网融合"到"三网融合"提供坚实的技术支撑.     

2002年夏季长白山天池火山区的地震活动研究

2002年6月以来,长白山天池火山区的地震活动明显增加. 本文利用2002年夏季布设在长白山天池火山区15套宽频带流动地震台站的记录资料,对天池火山区的地震活动进行了研究. 地震观测结果表明,2002年夏季长白山天池火山日平均地震发生频次超过30次. 地震主要位于长白山天池西南部和东北部两个区域,震源深度较浅,离地表的深度一般小于5km. 天池西南部和东北部的地震,b值存在较大的差异. 火山区地震记录的频谱分析和时频分析结果表明,这些地震主要为火山构造型地震. HSZ和DZD等台站地震记录中丰富的低频成分,可能与台站附近的局部介质或断层带有关. 我们认为2002年夏季频繁发生的地震和小震震群活动是由火山深部活动诱发的局部断裂活动引起.     

2022年9月5日四川泸定6.8级地震初步研究结果

北京时间2022年9月5日12时52分四川甘孜州泸定县(29.59°N,102.08°E)发生6.8级地震,中国地震预警网于震后6.1s产出首报预警结果;中国地震台网中心于震后3min发布自动速报结果,震后11min发布正式速报结果,同时联合中国地震局地球物理研究所、地质研究所、地震预测研究所和应急管理部国家自然灾害防治研究院启动地震应急产品产出工作,共产出震源基本参数、历史地震、地震构造、地震矩张量、余震精定位、地震烈度和震源破裂过程等9类应急产品。结合上述应急产品,对本次地震进行了研究,初步刻画了地震的构造环境、震源特征、断层形态和受灾区域,并分析了地震成因。结果表明,本次地震是发生在鲜水河断裂带南东段雪门坎—磨西断裂上的一次倾角近直立的走滑型事件,自起始破裂点向南东破裂,破裂长度约20km,最大滑移点深度约6km。余震精定位结果显示余震呈NW—SE向展布,长度约50km,深度主要集中在3～14km,展布方向与震中区域断裂走向基本一致,主震震中处断层倾角近乎垂直,与震源机制揭示的特征一致。烈度速报推测与地震烈度图显示极震区烈度达Ⅸ度,区域面积约280km²,Ⅷ度及以上区域总面积约505km²,涉及17个乡镇。认为本次地震是青藏高原隆升和高原上地壳物质向南东挤出,导致鲜水河断裂南东段雪门坎—磨西断裂上积累的应力的一次快速释放过程。     

Recent advances in earthquake monitoring II: Emergence of next-generation intelligent systems

Seismic data processing techniques, together with seismic instrumentation, determine our earthquake monitoring capability and the quality of resulting earthquake catalogs. This paper is intended to review the improvement of earthquake monitoring capability from the perspective of data processing. Over the past two decades, seismologists have made considerable advancements in seismic data processing, partly thanks to the significant development of computational power, signal processing, and machine learning techniques. In particular, wide application of template matching and increasing use of deep learning significantly enhance our capability to extract signals of small earthquakes from noisy data. Relative location techniques provide a critical tool to elucidate fault geometries and seismicity migration patterns at unprecedented resolution. These techniques are becoming standard, leading to emerging intelligent software systems for next-generation earthquake monitoring. Prospective improvements in future research must consider the urgent needs in highly generalizable detection algorithms (for both permanent and temporary deployments) and in emergency real-time monitoring of ongoing sequences (e.g., aftershock and induced seismicity sequences). We believe that the maturing of intelligent and high-resolution processing systems could transform traditional earthquake monitoring workflows and eventually liberate seismologists from laborious catalog construction tasks.     

震相关联方法在国家数字地震台网地震实时监测系统的应用

借鉴美国地质调查局（USGS）开发的Earthworm地震监测系统中自动地震定位模块的思想,将其中binder_ew软件模块功能应用到中国地震台网中心（CENC）开发的国家数字地震台网地震实时监测系统软件Ecums_rt中,运用地震震相关联方法,降低误触发地震台站对地震自动定位的干扰,从而实现软件优化,提升了Ecums_rt系统的地震事件自动定位监测能力。