3?21响水爆炸的地震学分析及谱比法研究

使用P/S谱比法重点对响水爆炸中信噪比较高的几个台站记录进行了处理分析。选取2013年1月19日发生在距其7 km左右的一次天然地震事件作为对比。得出频率在2—15 Hz范围内,90%以上的台站,爆炸P/S谱比大于1,天然地震这一值小于1,而在4—15 Hz范围内,这一结果达到了100%。为了进一步验证此方法判断爆炸与天然地震的可行性,本文又对2015年天津港爆炸事件进行计算,得到了相同的结果。此研究为使用P/S谱比法验证低震级爆炸提供案例。本文在研究的同时,对响水爆炸事件进行了波形特征及频谱特征分析。得出此事件地震记录的震相较单一,与普通的爆破记录较相似,并没有出现像2015年天津港爆炸中那样低速的空气声波与地面耦合的Rayleigh波。得到此事件有两个主频率,分别为0.2—1 Hz和4—10 Hz。      

3·21响水爆炸的地震学分析及谱比法研究

使用P/S谱比法重点对响水爆炸中信噪比较高的几个台站记录进行了处理分析。选取2013年1月19日发生在距其7 km左右的一次天然地震事件作为对比。得出频率在2—15 Hz范围内,90%以上的台站,爆炸P/S谱比大于1,天然地震这一值小于1,而在4—15 Hz范围内,这一结果达到了100%。为了进一步验证此方法判断爆炸与天然地震的可行性,本文又对2015年天津港爆炸事件进行计算,得到了相同的结果。此研究为使用P/S谱比法验证低震级爆炸提供案例。本文在研究的同时,对响水爆炸事件进行了波形特征及频谱特征分析。得出此事件地震记录的震相较单一,与普通的爆破记录较相似,并没有出现像2015年天津港爆炸中那样低速的空气声波与地面耦合的Rayleigh波。得到此事件有两个主频率,分别为0.2—1 Hz和4—10 Hz。     

首都圈地区“重复地震”及其在区域地震台网定位精度评价中的应用

根据Schaff和Richards^[1]对“重复地震”的定义,利用波形相关识别出首都圈地区2002~2006年发生的“重复地震事件”.对宽频带/甚宽带和短周期记录,分别采用0.5~5.0 Hz、1.0~5.0 Hz带通滤波,识别出859例“重复地震”事件,占总数约24%.假定“重复地震对”间的距离小于1 km,地震台网测得的两个地震之间的距离系台网定位误差所致,而相应的震相走时差为人工拾取误差,给出了首都圈数字地震台网的定位精度估计.结果显示观测条件较好的首都圈东北部地区平均定位精度约为5 km;西南部地区约为13 km,是观测条件有待改善地区.     

博阿断裂西段重复地震识别及断层深部滑移速率研究

本文选取博阿断裂西段周围30 km范围内2010年1月—2015年12月期间9个台站记录到的1272次地震事件的波形记录,利用波形互相关技术从中识别出65组(231次)重复地震,并且基于这些重复地震事件估算该断层的滑移速率.结果显示:该区域重复地震比例为18.2%;博阿断裂阿拉山口—精河段、精河—新源段的平均滑移速率分别约为0.99 mm/a和1.35 mm/a,乌苏—石场段、巴仑台—乌什城段的平均滑移速率分别为1.36 mm/a和2.03 mm/a,这与GPS观测结果基本一致;深部滑移速率的极大值分布在2—10 km深度范围内,其中巴仑台—乌什城段在8 km深度处达到了极大值8.6 mm/a.      

一种自动扫描地震漏检事件方法的研究与实现

地震事件的自动处理过程中会发生遗漏.台站数量越多,地震分析员在手动扫描遗漏事件时所花费的时间就越长.本文讨论了一种自动扫描漏检事件的方法,该方法利用分析员的分析经验,结合台站分布状况和地球物理学规则,重新关联那些具有很可能来自特定震源区域而未被分析员关联的信号,以形成一个待验证的事件,供分析员审定.该方法大大减少了分析员的工作量,提高了地震公报的质量.     

江苏及周缘地区地震精定位与构造意义分析

采用双差定位方法,对江苏地震台网记录到的江苏及邻区地震事件(1990-2009年)重新定位,共获取1020个定位结果,震中平均误差为:南北向0.42 km,东西向0.43 km,垂直向0.53 km.精定位后约94%的地震事件震源深度分布在5-20 km范围内,平均震源深度为12.3 km.震源深度自东向西,从海域向陆...     

天津港“8·12”爆炸事件记录波形分析

利用天津地震台网23个短周期地震仪记录到的2015年8月12日天津港爆炸事件波形数据,对事件进行初步分析和研究。分别使用能量包络线法和波形匹配法,共识别出4次爆炸事件,并结合波形互相关的主事件定位法对爆炸事件进行定位。分析结果表明:第一次爆炸发生的时间为2015年8月12日23时34分4秒,1.77s后发生了规模更大的二号爆炸事件;34.11s后又发生了最强的三号爆炸事件;86.33s再一次发生了能量较弱的四号爆炸事件,其中二号与三号爆炸事件相距65~70m,二号与四号事件相距160~170m。此外,通过选用爆破、矿塌、核爆和天然地震等不同类型事件的波形数据,从时间域和频率域分别对这些事件进行对比分析,发现其震相特征表现出明显差异。     

从全球长周期波形资料反演2001年11月14日昆仑山口地震时空破裂过程

利用从全球数字地震台网记录的资料中选择出的震中距小于90°且震相清晰的20个台站的长周期垂直分量P波震相, 通过反演得到了2001年11月14日昆仑山口地震的震源时空破裂过程. 结果表明, 这次地震由三次子事件构成. 第一次子事件的破裂从震中位置(35.97°N, 90.59°E)开始并向东西两侧扩展, 向西以4.0 km/s的破裂速度扩展了140 km, 向东以 2.2 km/s的破裂速度扩展了80 km, 表现为以自东向西为主的不对称双侧破裂, 形成了约220 km长的断层. 在第一次子事件的破裂开始后大约52 s, 在震中以西约220 km的地方, 第二次子事件的破裂开始. 此时, 第一次事件没有结束, 但已进入愈合阶段. 第二次子事件的破裂向东西两侧扩展, 向西以2.2 km/s的破裂速度扩展了50 km, 向东以5.8 km/s的破裂速度扩展了70 km, 表现为以自西向东为主的不对称双侧破裂, 形成了约120 km长的断层. 在第二次子事件开始后大约 12 s, 第二次子事件的破裂与第一次子事件的破裂在震中以西约140 km处发生了聚合. 在第一次子事件的破裂开始后大约56 s, 在震中以东约220 km的地方, 第三次子事件开始. 此时, 第一次事件仍未结束, 但已进入愈合阶段的尾声. 第三次子事件的破裂向东西两侧扩展, 向西以4.0 km/s的破裂速度扩展了140 km, 向东以3.7 km/s的破裂速度扩展了130 km, 基本上是一次不对称双侧破裂, 形成了约270 km长的断层. 在第三次子事件开始后大约36 s, 第三次子事件的破裂与第一次子事件的破裂在震中以东约80 km处发生了聚合. 此后, 震源过程主要是第一次子事件与第三次子事件聚合后的断层运动过程.     

2010年4月14日青海玉树地震震动图

在2010年4月14日07时49分(北京时间)青海省玉树藏族自治州玉树县(33.2°N,96.6°E)7.1级地震发生后,综合考虑震中地区的地质构造背景、活动断裂分布、震源机制结果、震源破裂过程、我国西部的地震动参数经验衰减关系及局部场地效应的影响,用考虑场地效应的震动图快速生成方法,在震后约2小时后得到玉树地震震中地区的震动图,并提供给相关部门使用.结果表明,此次地震的地震烈度特征预测如下:①烈度的展布方向NW-SE向,与玉树断裂的走向一致;②极震区的烈度为Ⅸ度,面积约为300km2;③烈度Ⅸ度区主要位于震中东南方向沿断裂走向近40km和西北方向沿断裂走向15km之间的区域;④Ⅸ度区的西北端由于局部场地条件的影响,其烈度由基岩参考面的Ⅸ度区降为土层上的Ⅷ度区;⑤Ⅷ度区面积约为3000km2;⑥Ⅶ度区的面积约为8000km2;⑦Ⅵ度区面积约为24000km2.     

一种基于温度历史和瞬态地温场模拟的剥露历史反演方法

根据低温热年代学数据,提取岩石从深部剥露到地表的信息,对理解诸多地质问题(如造山带演化、地表过程及其相互作用等)具有重要意义.本文提出一种基于岩石温度历史(可利用古温标、热年代计等方法制约),并考虑剥露过程对地温场扰动的剥露历史反演计算方法.基于假定的与真实数据的正反演模拟和参数敏感性分析表明:热扩散率的变化对剥蚀量计算影响不大,在常规岩石热扩散率变化范围内(20～35km2/Ma),总剥蚀量变化小于10%;传统计算方法低估了剥蚀总量,对于现今地温梯度小于20℃/km、冷却速率大于2～3℃/Ma,或现今地温梯度大于30℃/km、冷却速率大于5～10℃/Ma的地区,需要考虑热平流对剥蚀量计算的影响;匀速冷却的热历史指示剥蚀速率持续减小,而非匀速剥蚀.本文将该方法应用到龙门山南段和四川盆地,反演计算显示龙门山南段15Ma以来的剥蚀总量为8km,四川盆地中部80Ma以来剥蚀总量约为3km、东部约5km.     

用逐步代价最小决策法识别地震与爆破

在动态时间规整法的基础上, 建立了逐步代价最小决策法(SAMC). 该方法中的代价函数可以很好地反映特征归属, 对较差的特征具有一定的“容忍度”、 稳定性好, 还可用全程代价函数评判识别结果的可信度. 用SAMC方法对北京及其周边地区33次地震和29次爆破中提取的5个分类特征量进行识别, 识别率为90%; 从该5个特征量中选择较好的3个特征量进行识别, 识别率为92%; 在上述地区另选13次事件作为检验样本进行U检验, 5个分类特征量和3个分类特征量的识别率分别为92%和100%, 识别效果很好. 这表明SAMC是识别地震与爆破的有效方法.      

遗传BP网络在地震和爆破识别中的应用

将遗传算法(GA)和反向传播算法(BP算法)相结合成为GA-BP算法，以此建立了遗传BP神经网络．并将以BP算法为基础的BP神经网络及以GA-BP算法为基础的遗传BP神经网络用于对地震和爆破的识别中．得到的结果表明:遗传BP网络比BP网络对事件的识别能力略好些．      

Application of genetic BP network to discriminating earthquakes and explosions

Introduction Artificial Neural Network (ANN) is an important branch of artificial intelligence. It is proposed on the foundation of the study on modern neural science, is a man-made network that can implement some functions based on the mans comprehensive understanding for cerebral neural network (HAN, WANG, 1997). ANN is a mathematical model of simplified human brain neural network and is used to simulate the structures and functions of human brain neural network. ANN is a complex netw…     

Spectral classification methods in monitoring small local events by the Israel seismic network

We use the dense Israel Seismic Network (ISN) to discriminate between low magnitude earthquakes and explosions in the Middle East region. This issue is important for CTBT monitoring, especially when considering small nuclear tests which may be conducted under evasive conditions. We explore the performance of efficient discriminants based on spectral features of seismograms using waveforms of 50 earthquakes and 114 quarry and underwater blasts with magnitudes 1.0–2.8, recorded by ISN short-period stations at distances up to 200 km. The single-station spectral ratio of the low and high-frequency seismic energy shows an overlap between explosions and earthquakes. After averaging over a subnet of stations, the resolving power is enhanced and the two classes of events are separated. Different frequency bands were tested; the (1–3 Hz)/(6–8 Hz) ratio provided the best discriminant performance. We also estimated normalized r.m.s. spectral amplitudes in several sequential equal frequency windows within the 1–12 Hz band and applied multiparametric automatic classification procedures (Linear Discrimination Function and Artificial Neural Network) to the amplitudes averaged over a subnetwork. A leave-one-out test showed a low rate of error for the multiparametric procedures. An innovative multi-station discriminant is proposed, based on spectral modulation associated with ripple-firing in quarry blasts and with the bubbling effect in underwater explosions. It utilizes a distinct azimuth-invariant coherency of spectral shapes for different stations in the frequency range (1–12 Hz). The coherency is measured by semblance statistics commonly used in seismic prospecting for phase correlation in the time domain. After modification, the statistics applied to the network spectra provided event separation. A new feature of all the above mentioned procedures is that they are based on smoothed (0.5 Hz window), instrument-corrected FFT spectra of the whole signal; they are robust to the accuracy of onset time estimation and, thus well suited to automatic event identification.     

Applicability of P/S amplitude ratios for the discrimination of low magnitude seismic events

Applicability of regional P/S amplitude ratios for the discrimination of low-magnitude seismic events was tested and proved using earthquakes and explosions in Central Asia. Results obtained show that regional P/S amplitude ratios which may discriminate medium or large magnitude events well, are also applicable to low magnitude events. Their performances for low magnitude events are almost as good as that for medium or large events. Statistical comparisons based on 25 P/S discriminate from the four seismic stations WMQ, BLK, MUL and MAK showed that the average misclassification rate for low-magnitude seismic events averagely was only 2 percent higher than that for medium and large magnitude seismic events.     

Detection and Analysis of Near-Surface Explosions on the Kola Peninsula

Seismic and infrasonic observations of signals from a sequence of near-surface explosions at a site on the Kola Peninsula have been analyzed. NORSAR’s automatic network processing of these events shows a significant scatter in the location estimates and, to improve the automatic classification of the events, we have performed full waveform cross-correlation on the data set. Although the signals from the different events share many characteristics, the waveforms do not exhibit a ripple-for-ripple correspondence and cross-correlation does not result in the classic delta-function indicative of repeating signals. Using recordings from the ARCES seismic array (250 km W of the events), we find that a correlation detector on a single channel or three-component station would not be able to detect subsequent events from this source without an unacceptable false alarm rate. However, performing the correlation on each channel of the full ARCES array, and stacking the resulting traces, generates a correlation detection statistic with a suppressed background level which is exceeded by many times its standard deviation on only very few occasions. Performing f-k analysis on the individual correlation coefficient traces, and rejecting detections indicating a non-zero slowness vector, results in a detection list with essentially no false alarms. Applying the algorithm to 8 years of continuous ARCES data identified over 350 events which we confidently assign to this sequence. The large event population provides additional confidence in relative travel-time estimates and this, together with the occurrence of many events between 2002 and 2004 when a temporary network was deployed in the region, reduces the variability in location estimates. The best seismic location estimate, incorporating phase information for many hundreds of events, is consistent with backazimuth measurements for infrasound arrivals at several stations at regional distances. At Lycksele, 800 km SW of the events, as well as at ARCES, infrasound is detected for most of the events in the summer and for few in the winter. At Apatity, some 230 km S of the estimated source location, infrasound is detected for most events. As a first step to providing a Ground Truth database for this useful source of infrasound, we provide the times of explosions for over 50 events spanning 1 year.     

用决策方法识别地震和爆破

在矩阵决策方法的基础上,建立了识别地震与爆破的矩阵决策算法（MDA）．着眼于快速识别,研究了5个判据. 其中初动方向和振幅比判据的效果较好．用MDA算法对北京附近62个事件进行了识别和检验得到:用5个判据C检验的正确识别率达到97%, U检验也达到93%,识别效果较好;依次从5个判据中任选4个判据作决策识别和检验, 10个结果中有7个的正确识别率在93.3%以上.结果表明,本文建立的MDA算法和所选的特征能有效地识别地震与爆破,可应用于两者的快速识别．      

Yield Estimation for Semipalatinsk Underground Nuclear Explosions Using Seismic Surface-wave Observations at Near-regional Distances

—?A statistical procedure is described for estimating the yields of underground nuclear tests at the former Soviet Semipalatinsk test site using the peak amplitudes of short-period surface waves observed at near-regional distances (Δ < 150 km) from these explosions. This methodology is then applied to data recorded from a large sample of the Semipalatinsk explosions, including the Soviet JVE explosion of September 14, 1988, and it is demonstrated that it provides seismic estimates of explosion yield which are typically within 20% of the yields determined for these same explosions using more accurate, non-seismic techniques based on near-source observations.     

Isotropic and Nonisotropic Components of Earthquakes and Nuclear Explosions on the Lop Nor Test Site, China

—?We test the hypothesis that the existence of an observable non-zero isotropic component of seismic moment can be used as a discriminant to distinguish nuclear explosions from shallow earthquakes. We do this by applying the method described herein to a small set of data recorded between 1990 and 1996 following events (seven nuclear explosions, three earthquakes) that occurred on the Lop Nor test site in Western China. We represent each source as a sum of an isotropic component at the surface and a nonisotropic, double-couple component at an estimated depth. The explosions all possess a significant non-zero isotropic component and the estimated depth of the double-couple component of the moment tensor, presumably the result of tectonic release, lies between about 0 and 3?km. For the earthquakes studied, the isotropic component is indistinguishable from zero and the depths of the sources are estimated at 3, 17 and 31?km. The data set we have studied, although still very small, suggests that certain source characteristics (namely, double-couple depth and the ratio of the isotropic to nonisotropic components of seismic moment) may prove useful in discriminating explosions from shallow earthquakes. Further work is needed to determine whether these observations hold for explosions at other test sites, to investigate a much larger set of shallow earthquakes located in regions of interest, and to study the robustness of the estimated source parameters as source magnitude and the number of observing stations decrease.     

学习向量量化(LVQ)在地震和爆破识别中的应用

介绍了竞争神经网络和学习向量量化（LVQ）算法。此算法应用于对北京及周围地区地震和爆破的识别中，在对38个事件的应用中，得到的结果是，误识为3个，结果较好，说明在识别中是有效的。