Scaling features of ambient noise at different levels of local seismic activity: A case study for the Oni seismic station

Investigation of dynamical features of ambient seismic noise is one of the important scientific and practical research challenges. We investigated scaling features of the ambient noises at the Oni seismic station, Georgia, using detrended fluctuation analysis method. Data from this seismic station, located in the epicentral zone of Oni M6.0, 2009, earthquake, were selected to include time periods with different levels of local seismic activity.     

新冠肺炎疫情对佘山与大洋山地震台背景噪声的影响

人类的生产生活产生的振动会以高频地震波的形式被地震台站所记录。2020年1月,新冠肺炎疫情爆发,为了应对此次疫情,各地政府分别启动应急响应,国内地震记录出现最长、最突出的人为地震降噪期。各地震台站背景噪声显著下降,在人口稠密及工业发达地区尤为明显。同时,静噪期为探测地下地震源的微弱信号提供了可能。静噪期内,佘山地震台2 Hz频点背景噪声功率谱密度值比平时降低10 dB,而大洋山地震台10 Hz频点背景噪声功率谱密度值较平时降低约5 dB;佘山地震台2—10 Hz以及大洋山地震台10 Hz以上频率的背景噪声受静噪期影响明显。结合地震台站所处位置分析,疫情期间佘山地震台附近人口流出较多,2—10 Hz频率的背景噪声变化明显;大洋山地震台背景噪声则受工厂、轮渡、高速汽车等影响较大,f ≥10 Hz的背景噪声变化显著,而频率在2—10 Hz则无明显变化,表明该台人口总数趋于平稳。地震噪声和人类活动之间的相关性表明,地震学研究可以提供实时人口动态估计。     

华北地区地震环境噪声特征研究

利用华北流动地震台阵观测的垂直分向连续波形数据, 通过计算功率谱密度和相应的概率密度函数, 对华北地区地震环境噪声特征进行了分析研究. 结果表明, 东部平原和沉积盆地2 Hz以上的高频环境噪声水平与全球新高噪声模型（NHNM）相近, 周期3——18 s的平均噪声水平低于NHNM和新低噪声模型（NLNM）的平均值; 山区及西部高原的高频噪声水平明显低于NHNM, 周期1——18 s的噪声水平大多明显低于NHNM和NLNM的平均值; 不同区域18 s以上周期的噪声水平差异相对较小. 流动地震台阵部分台站的环境噪声存在明显的昼夜变化, 个别台站噪声水平明显高于周边台站, 表明这些台站受人类活动干扰较大. 不同台站的噪声水平分析表明, 将台站布设在摆坑内, 能在一定程度上降低高频和低频段的噪声水平. 台站环境噪声特征的研究结果可为流动地震台阵观测数据质量的定量评估, 观测期间的台站优化调整等提供重要依据.      

中国大陆背景噪声成像研究及应用前景

对长时间序列的背景地震噪声进行互相关计算可以得到台站间的经验格林函数,这种方法不依赖天然地震及人工震源,仅利用台站记录的背景噪声就能得到地下结构,该方法可以更为便捷地获得地震活动性较低地区的地下构造.随着背景噪声层析成像技术的发展应用,该方法会进一步提高地壳上地幔速度模型的分辨率.本文综述了背景噪声成像技术及其在中国大...     

Soil characteristics and site effect assessment in the city of Delhi (India) using H/V and f–k methods

Local site conditions substantially affect the characteristics of seismic waves and its potential to cause earthquake damage. To accurately identify the variation of seismic hazard at different locations within the cities, measurements from a three-component station may be used for estimating the resonance frequencies and evaluate the expected level of damage at each site. This information can also be complemented with array measurements of ambient noise in order to estimate the V_s profiles and characterize the corresponding sediment layers at each site.     

台网噪声评估及其对气枪震源激发效果影响的研究

为了研究背景噪声对长江地学气枪主动源实验激发效果的影响,收集了240个台站激发前72小时的背景噪声数据及20个定点激发的叠加结果进行实验分析.先剔除异常台站,按照国标将台网噪声水平划分为高、中、低3个等级进行评估,从而研究气枪波形信噪比与台站背景噪声的关系.结果表明:① 台站接收能力与背景噪声水平密切相关;② 气枪信号的信噪比在一定范围内受背景噪声的影响大于距离衰减的影响;③ 长江马鞍山—安庆流域段不同定点激发的场地条件基本一致;④ 随气枪信号叠加次数的增加,低噪台站的信噪比增长速度快于中、高噪台站,若想获得同样的叠加效果,高噪台站需要的叠加次数远大于低噪台站.      

新冠疫情防控前后湖北恩施地震台背景噪声变化分析

利用2018年1月至2020年3月恩施地震台站观测的垂直分量连续波形数据,通过计算噪声功率谱密度和概率密度函数,统计其不同频段功率谱密度分布情况,对比分析疫情前后恩施地区噪声水平变化特征.同时,将2018年、2019年和2020年垂直向地震噪声的加速度幅值进行对比,发现春节前几日的加速度幅值变化曲线高度一致,表明这三年...     

Feasibility of borehole ambient noise interferometry for permanent reservoir monitoring

The analysis of seismic ambient noise acquired during temporary or permanent microseismic monitoring campaigns (e.g., improved/enhanced oil recovery monitoring, surveillance of induced seismicity) is potentially well suited for time‐lapse studies based on seismic interferometry. No additional data acquisition required, ambient noise processing can be automatized to a high degree, and seismic interferometry is very sensitive to small medium changes. Thus there is an opportunity for detection and monitoring of velocity variations in a reservoir at negligible additional cost and effort. Data and results are presented from an ambient noise interferometry study applied to two wells in a producing oil field in Romania. Borehole microseismic monitoring on three component geophones was performed for four weeks, concurrent with a water‐flooding phase for improved oil recovery from a reservoir in ca. 1 km depth. Both low‐frequency (2 Hz–50 Hz) P‐ and S‐waves propagating through the vertical borehole arrays were reconstructed from ambient noise by the virtual source method. The obtained interferograms clearly indicate an origin of the ambient seismic energy from above the arrays, thus suggesting surface activities as sources. It is shown that ambient noise from time periods as short as 30 seconds is sufficient to obtain robust interferograms. Sonic log data confirm that the vertical and horizontal components comprise first arrivals of P‐wave and S‐waves, respectively. The consistency and high quality of the interferograms throughout the entire observation period further indicate that the high‐frequency part (up to 100 Hz) represents the scattered wave field. The temporal variation of apparent velocities based on first‐arrival times partly correlates with the water injection rate and occurrence of microseismic events. It is concluded that borehole ambient noise interferometry in production settings is a potentially useful method for permanent reservoir monitoring due to its high sensitivity and robustness.     

鄂西地区宽频地震台阵背景噪声特征

利用鄂西地区长时间段宽频地震台站的三分量背景噪声记录,采用波形互相关方法得到台站对间的互相关函数,并通过聚束分析获得瑞雷波和勒夫波的慢度谱,研究鄂西地区背景噪声源的时空分布特征。结果表明,5~10 s周期范围,背景噪声来源于南太平洋且没有季节变化;10~20 s周期范围,慢度谱上显示明显的能量环,表明噪声源来源于多个方向,且表现出强烈和急剧的季节变化;20~40 s周期范围,慢度谱上也存在明显的能量环,其产生机制可能与此周期下提出的次重力波机制相似。在不同的周期范围内,噪声源分布方位有所不同,但在周期10~40 s范围噪声源在各方向均有分布。因此,利用长时间段连续噪声数据计算的互相关函数在周期10~40 s范围内满足背景噪声面波层析成像的理论前提。     

龙门山断裂带中上地壳速度结构的短周期环境噪声成像

本文利用在龙门山断裂带周边布设的57个台站自2008年11月至2009年11月为期一年的垂直分量连续地震环境噪声数据,通过短周期地震环境噪声成像方法,获得了龙门山断裂带中北段地壳25km深度范围的S波精细速度结构.结果表明:(1)龙门山断裂带周边区域10km以上的速度结构与地表断裂的分布形态具有良好的一致性,速度结构控制了龙门山主要断层的深部延展特征;在15km及以下深度,S波速度结构呈现沿龙门山和沿岷山隆起走向的交叉构造格局,由此造成的速度结构差异可能影响了汶川地震的破裂过程;(2)速度结构随深度的分布特征为龙门山断裂带主要断层的深部延伸形态给出了良好的约束,结果进一步确认了龙门山断裂中段的高角度铲型断裂构造特征;(3)研究区的南端发现了龙门山断裂下方20km以下深度具有与松潘地块中地壳低速层相关的低速结构的迹象,这可能是汶川地震破裂带南段22km左右深度存在脆韧转换带的一个证据.研究结果显示出密集台阵和短周期环境噪声成像方法在地壳浅部精细结构和断层探测研究中具有巨大潜力.     

利用噪声研究地下介质速度结构及其变化在中国大陆的应用

背景噪声层析成像技术已被广泛应用于地壳和上地幔速度结构的研究,这种方法不依靠地震的发生和人工源爆破,只需记录连续的噪声信号而无需产生信号,因为噪声穿过地下介质时会携带信息,然后通过利用台站记录到的连续背景噪声数据进行互相关计算和叠加,即可得到台站间的经验格林函数,从而获取对地下结构的认识。这种方法已经很好地应用于中国的东北地区、华北克拉通、青藏高原以及华南地区,并成功地揭示了这些地区地壳与上地幔顶部的速度结构。此外近年来,一些学者还利用噪声互相关技术研究地下介质地震波速度随时间的变化,通过对汶川大地震前后连续噪声记录的研究发现,大震发生后呈现同震波速降低和震后波速逐渐恢复的特点,这表明可以通过观测地震波特性的变化来监测地下应力的变化,从而为大震的预测预防工作提供科学依据。本文主要综述了近些年来背景噪声技术及其在中国大陆地区的应用。     

Some properties of low-frequency seismic noise

The low-frequency seismic noise recorded by the broadband IRIS stations in 1994–2012 is studied in the period range of 40 to 360 s. It is shown that for samples of a few months in length, the power spectra of noise at stations spaced apart a few thousand kilometers and operating in different meteorological and seismotectonic conditions are overall similar, which indicates that the sources of the noise are global. At the same time, the slope of the spectra changes with the increase in the period in the subintervals of 40–90, 120–200, and 200–360 s, which points to the difference of the sources generating the seismic noise. The amplitude of the noise at the stations located a few thousand km apart from the Sumatra earthquake of December 26, 2004, M = 9.2, and from the Tohoku earthquake of March 11, 2011, M = 9.0, increased after these events. This indicates the global character of the aftermath of these seismic catastrophes. After the Kronotskoe earthquake of December 5, 1997, which was weaker (M = 7.9), the noise grew only at the PET station located within 300 km of the epicenter. According to the records at the PET station, this earthquake was preceded by the increased noise level observed in 1994–1997. After 1999, the seismic noise declined and remained low up to the end of the studied interval with a duration of 14 years. Our results show that the low-frequency seismic noise generated by the sources in the atmosphere of the Earth is contributed by the processes taking place in the lithosphere.     

甘东南地区宽频带地震台阵背景噪声特征分析

基于甘肃东南地区150个宽频带流动台站2010年的垂直分量连续波形记录,通过计算台站对之间背景噪声的互相关函数并叠加得到5—10s和10—20s两个周期的瑞雷面波信号,并通过信噪比和归一化背景能量流两种方法研究了该地区背景噪声源的时空演化特征.研究结果表明,甘东南地区5—10s和10—20s周期的背景噪声源具有明显的季节变化特征和各自的优势方位.5—10s周期的背景噪声在夏季的能量优势方位为170°—240°,噪声源主要位于印度洋,而冬季为100°—150°,主要位于北太平洋;10—20s周期的背景噪声源则比较复杂,其优势方位受多个大洋的交替影响,夏季噪声源能量优势方位为170°—210°,噪声源主要位于印度洋,冬季为90°—150°和310°—355°,噪声源分别位于北太平洋和北大西洋.由于这两个周期的背景噪声源在甘东南地区存在明显的季节变化,因此在利用背景噪声方法研究该地区介质速度结构时需充分考虑噪声源的非均匀性所产生的影响.      

不同深度布设台站的噪声及信号幅值特征分析

为探究地震观测中地震计检测到的噪声和信号强度均受其布设深度的影响,本文首先对CPUP和LPAZ两台站布设的不同深度地震计所得到的数据进行噪声水平和地震信号对比;其次采用对比功率谱密度的方法对两台站不同通道采集到的不同时段的噪声数据进行分析;最后比较两台站不同通道采集到的整月数据的噪声幅值、信号幅值、信噪比特征。结果显示:深度较大的通道,其噪声功率均值较小;当事件信号到来时,较深通道的地震计检测到的信号和噪声幅值比较浅通道均有所减小,在信号和噪声幅值均减小的共同影响下,信噪比有一定程度的变化,其中LPAZ台站的信噪比提高较为明显。      

流动地震观测背景噪声的台基响应

大规模流动地震台阵技术发展为高分辨率深部结构成像提供了重要基础,背景噪声是影响流动地震观测质量的关键因素. 为掌握流动地震观测噪声规律,发展流动地震观测降噪技术, 编制流动地震观测技术规范, 我们开展了针对不同台基流动地震观测背景噪声的观测实验与分析. 其中,山西省临汾市五个地点架设了共22个对比观测台站, 进行了超过一年半的连续观测. 通过计算不同频段范围内背景噪声记录的加速度功率谱密度, 研究了不同场地条件和环境噪声下流动地震观测台站的噪声特征及其台基响应,分析了不同台基处理方式对噪声的抑制效果. 结果表明:(1)高频人为噪声和长周期自然噪声是影响流动地震观测质量的主要噪声, 可以通过增加台基深度和改善台基处理方式等方法降低其影响; (2)增加台基深度能有效地降低长周期噪声和高频噪声, 2 m深坑能使高人为噪声台站各分量的高频频段和长周期频段分别降低5 dB和10 dB; (3)由于其不稳定性, 沙子台基的水平分量在长周期频段一般要高于摆墩台基5 dB, 流动地震观测中推荐使用摆墩台基; (4) 台站位置、台站内部温度和空气流动都是影响台站噪声的重要因素. 在此基础上提出了不同场地条件和噪声环境下的台基处理建议和适合国情的移动地震台阵台站建设参考方案, 有助于流动地震观测野外工作的标准化和规范化.     

地球背景噪声干涉应用研究的新进展

对地震台记录到的长时间的地球背景噪声进行互相关处理,得到的互相关函数可以近似地表征这两个台站之间的格林函数,这种数据处理方法被称为背景噪声干涉.近年来,背景噪声干涉研究在理论和实践上都有了长足进展,并被广泛用于地下波速结构及其演化规律的研究.本文首先简单介绍了背景噪声干涉研究的概念和理论依据,进而重点介绍了针对噪声源性质、互相关函数的波形到时和振幅特性的应用研究.通过对这三个方面研究的回顾,分析总结了该研究领域的新进展及需要解决的问题,并对背景噪声干涉研究的新特点进行了分析和展望.     

Detection capability of seismic network based on noise analysis and magnitude of completeness

Assessing the detection threshold of seismic networks becomes of increased importance namely in the context of monitoring induced seismicity due to underground operations. Achieving the maximum possible sensitivity of industrial seismic monitoring is a precondition for successful control of technological procedures. Similarly, the lowest detection threshold is desirable when monitoring the natural seismic activity aimed to imaging the fault structures in 3D and to understanding the ongoing processes in the crust. We compare the application of two different methods to the data of the seismic network WEBNET that monitors the earthquake swarm activity of the West-Bohemia/Vogtland region. First, we evaluate the absolute noise level and its possible non-stationary character that results in hampering the detectability of the seismic network by producing false alarms. This is realized by the statistical analysis of the noise amplitudes using the ratio of 99 and 95 percentiles. Second, the magnitude of completeness is determined for each of the nine stations by analysing the automatic detections of an intensive swarm period from August 2011. The magnitude–frequency distributions of all detected events and events detected at individual stations are compared to determine the magnitude of completeness at a selected completeness level. The resulting magnitude of completeness M _c of most of the stations varies between ?0.9 and ?0.5; an anomalous high M _c of 0.0 is found at the most distant station, which is probably due to inadequate correction for attenuation. We find that while the absolute noise level has no significant influence to the station sensitivity, the noise stationarity correlates with station sensitivity expressed in low magnitude of completeness and vice versa. This qualifies the method of analysing the stationary character of seismic noise as an effective tool for site surveying during the seismic station deployment.     

南极中山与昭和站重力海潮负荷效应及背景噪声研究

利用南极中山站LCR-ET21重力仪器与昭和站GWR058仪器获得的重力潮汐观测资料,采用最新的三个全球海潮模型(Dtu10,Eot11A和HAM11A)研究了南极地区的海潮负荷效应和背景噪声.结果表明,由三个海潮模型计算的重力负荷均值改正后,中山站O_1和M_2振幅观测残差分别由13.83%和20.55%下降到5.32%和5.95%,昭和站O_1和M_2振幅观测残差分别由10.84%和21.52%下降到1.91%和3.40%,说明海潮负荷改正的有效性.利用加汉宁窗的FFT变换,获得了地震频段的地震噪声等级(SNM),其值分别为1.574(中山站)和1.289(昭和站).而在潮汐频段,中山站的背景噪声比昭和站高一个数量级,主要由不同观测仪器和台站局部环境所致.本文结果可为进一步利用南极重力资料研究局部环境和全球动力学问题提供有效参考.     

New Seismic Noise Models Obtained Using Very Broadband Stations

It has been two decades since the last comprehensive standard model of ambient earth noise was published Peterson (Observations and modelling of seismic background noise, US Geological Survey, open-file report 93–322, 1993). The PETERSON model was updated by analyzing the absolute quietest conditions for stations within the GSN (Berger et al. in J Geophys Res 109, 2005; Mcnamara and Buland in Bull Seism Soc Am 94:1517–1527, 2004; Ringler et al. in Seismol Res Lett 81(4) doi:10.1785/gssrl.81.4.605, 2010). Unfortunately, both the original model and the updated models did not include any deployed station in North Africa and Middle East, which reflects the noise levels within the desert environment of those regions. In this study, a survey was conducted to create a new seismic noise model from very broadband stations which recently deployed in North Africa. For this purpose, 1 year of continuous recording of seismic noise data of the Egyptian National Seismic Network (ENSN) was analyzed in order to create a new noise model. Seasonal and diurnal variations in noise spectra were recorded at each station. Moreover, we constructed a new noise model for each individual station. Finally, we obtained a new cumulative noise model for all the stations. We compared the new high-noise model (EHNM) and new low-noise model (ELNM) with both the high-noise model (NHNM) and low-noise model (NLNM) of Peterson (Observations and modelling of seismic background noise, US Geological Survey, open-file report 93–322, 1993). The obtained noise levels are considerably lower than low-noise model of Peterson (Observations and modelling of seismic background noise, US Geological Survey, open-file report 93–322, 1993) at ultra long period band (ULP band), but they are still below the high-noise model of Peterson (Observations and modelling of seismic background noise, US Geological Survey, open-file report 93–322, 1993). The results of this study could be considered as a first step to create permanent seismic noise models for North Africa and Middle East regions.     

基于背景噪声互相关格林函数的 单台时间误差估计

从江苏省数字地震台网2011年的宽频带记录数据中, 选取了不同背景噪声区域下的两组不同台间距的台站(A, B每组4个台站), 两组台站的平均台间距分别为44.6和30.5 km. 首先, 运用滑动窗互相关技术, 测量出各台站对间背景噪声互相关格林函数随时间的偏移量ΔD_Si-Sj, 然后通过奇异值分解来求解由ΔD_Si-Sj与系数矩阵构成的超定方程, 从而计算出单个台站的时钟误差ΔS_i;并引入协方差矩阵来估计不同置信水平下计算结果的误差范围. 计算结果表明, 除去明显的钟差误差(>3 s)外, 8个台站的时间误差平均均方根为0.4215 s, A与B两组台站在置信水平为95%时的时间误差范围分别为±0.4544 s和±0.4283 s; 而采用HYPOSAT定位方法对2010—2011年江苏地区的地震进行定位, 得到的平均走时残差约为0.386 s. 两者的计算精度基本相当, 表明基于背景噪声互相关格林函数计算出的单台时间误差是可信的.