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STA/LTA算法拾取微地震事件P波到时对比研究 总被引：2，自引：0，他引：2
本文将HZ-MS48微地震采集仪监测的实际数据,利用STA/LTA算法来识别微地震事件P波到时.比较了在不同STA(短时窗平均值)情况下对拾取精度和结果的影响.结果表明:此算法确定信噪比比较高的微地震事件是非常有效的,能精确拾取P波到时.利用5ms、10ms、20ms三种不同的短时窗处理数据,发现对P波拾取的敏感程度不同,短时窗的值越大,拾取P波的敏感性越低,拾取精度降低,触发的阈值应随着短时窗的增加而减小. 相似文献
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基于特征值分解方法,本文讨论了一种适用于地方震事件S波震相到时拾取的自动处理算法。该算法计算参数少、简便快捷、易于实现,通过选用七个不同长度的时间窗,有效地减小了窗长选择不合理所引起的震相拾取误差。利用福建地震台网记录的9 855条三分向波形记录进行测试,结果表明:本文方法的S波平均拾取偏差为（0.003±1.34） s,其中79.6%的记录拾取偏差小于0.5 s,4.1%的记录拾取偏差超过2.0 s,说明本文方法能够满足日常工作基本需求。综上分析认为,波形记录质量是影响拾取算法结果精度的最主要因素,信噪比较高的记录,其S波到时拾取偏差显著优于信噪比较低的记录,对信噪比较低的部分记录进行带通滤波预处理后,S波震相拾取精度也有所提升。 相似文献
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在１９７６－１９８３年期间,格陵兰地区共记录到５３个３－５级地震,确定了所有的地震参数,分析了２９个地震的震相到时,得到了该地区Ｐｎ,Ｐｇ,Ｐ１１（ＰＭＰ）Ｓｎ和Ｌｇ震相的走时曲线及其视速度值,该结果与加拿大走时曲线相一致,发现一部分地震图上有在直达波Ｐ与Ｓ之间记录到一个附加的震相－ｉ,ｉ震相的存在与震中距,震源深度有关,初步的物理解释是,ｉ震相可解释成为（Ｐｓ）或（Ｓｐ）转换波,该转换波发生在台 相似文献
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本文对利用强震近场加速度记录确定时,空、强三个完整的震源参数。文中给出一种利用计算机自动识别地震记录的Ｐ波初动到时和Ｓ波震相到的算法。根据新近发表的Ｗｏｏｄ－Ａｎｄｅｒｓｏｎ地震仪器的最新参数,修牍正唐山地区量规函数。利用唐 山数字震观测台阵得到的近场加速度数据,计算了１０次地震的震源位置和震级,并对定位误差进行了综合分析,将强震台网测定的震源参数与地震台 相似文献
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面波的尾波衰减经验关系和震级 总被引：2，自引：1，他引：1
从南京地震台ＤＫ－１中长周期地震纪录,取得地震面波的尾波地动双振幅Ａ随尾波推移时间τ（自图Ｐ波起算）的衰减关系,并以Ｍｓ（ＰＥＫ）震级标度为基准,定义面波的尾波震级Ｍｓｃ＝０．８８１ｇＡＨ＋１．５１ｌｇτＨ＋０．７３＝０．８６１ｇＡｚ＋１．４７ｌｇτｚ＋０．７６,尾波的多点测量改善了Ｍｓｃ的精度,震级标准差Ｓ＝０．１２。 相似文献
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丽江7.0级地震的余震震源参数研究 总被引：6，自引：2，他引：6
本从ＰＤＲ－２数字化近源（６．２ｋｍ≤△≤４２ｋｍ）台网记录的丽江余震中初选了７４个地震，初定了震中位置，震中方位角。用相应的台网数据处理技术，研究了丽江地震序列的体波谱。对震级２．５≤Ｍ≤５．７、地震矩２１．４０≤ｌｏｎｇＭ０≤２３．２８的地震，得出了丽江地区地震系列的震源参数；以及Ｐ波、Ｓ波的ｌｏｇＭ０与Ｍｄ的关系式分别为：ｌｏｇＭ０＾ｐ＝０．６２Ｍｄ＋１９．９３；ｌｏｇＭ０＾ｓ＝０．５９Ｍ 相似文献
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给出了三分量地震台地震数据自动在线分析系统的基本方法和算法以及初步实验结果。数据处理分为４步：（１）用基于能量的ｒ检测器进行初步检测和信号到时估算;（２）精取信号参数（到时、振幅、周期和尾波持续时间）;（３）用偏振分析估算地震射线的方位角和入射角;（４）对对一个固定的震源深度,刷远震Ｐ波挖估算事件的参数（震中坐标、发震时刻和震级）。在哈萨克斯坦东部的一个实验地震台上,用命名为“ＳＥＩＳＭＯＳＴＡＮ 相似文献
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STA/LTA—AIC算法对地震P波震相拾取稳定性影响 总被引：1，自引：1，他引：0
选取区域地震台网记录的地震波形数据,使用STA/LTA算法与STA/LTA—AIC算法,进行地震P波震相初至到时自动拾取,对地方震及震中距较大的震相进行P波震相拾取效果分析,发现:STA/LTA算法对于地方震P波震相识别精度较高,与STA/LTA—AIC算法拾取的P波震相初至到时相差不大;震中距变大后,STA/LTA算法对P波拾取位置相对于最佳位置向后延迟,STA/LTA—AIC算法有效矫正了STA/LTA算法拾取位置的延迟问题,与人工拾取位置差别可忽略不计。 相似文献
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微震信号自动检测的STA/LTA算法及其改进分析 总被引：1，自引：0，他引：1
通过对合成微震数据和实测微震记录的处理实验,对自动检测有效微震信号的STA/LTA(短时窗平均/长时窗平均)算法及其改进的加权系数法、多窗口算法和修正的能量比算法进行了分析和对比,给出了时窗长度、触发阈值和特征函数对算法性能的影响特征及其选取规律.与原STA/LTA算法相比,加权系数法,降低了微震事件的漏判率;多窗口算法和修正的能量比法提高了对低信噪比微震记录检测的正确率及微震到时的拾取精度. 相似文献
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针对低信噪比条件下微震初至拾取准确度低的问题,基于信号幅度变化引入权重因子,对传统长短时窗比值（STA/LTA）算法进行改进,提高初次拾取精度。为了进一步降低拾取误差,对变分模态分解（VMD）算法进行优化,基于互相关系数和排列熵准则自适应确定VMD分解层数,对初次拾取结果前后2—3 s的记录进行优化VMD,并计算分解后各本征模函数（IMF）的峰度赤池信息准则值,得到各IMF的到时,以各IMF的拾取结果及能量比综合加权得到二次拾取到时。仿真实验表明:改进后的STA/LTA在较低信噪比下可降低初次拾取误差约0.01 s以上;相比经验模态分解（EMD)和小波包分解,自适应VMD分解后能再次降低误差,最终与人工拾取结果平均误差在0.023 s以内。实际微震信号初至拾取结果表明,本算法能快速有效地识别初至P波,与人工拾取结果相比误差小,准确率高。 相似文献
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为了改善传统岩性密度测井仪的缺陷,本文基于传统的双 源距探测器密度测井仪,提出在负源距范围内增加一个反散射探测器,构成新的三探测器密 度测井仪器. 利用Monte Carlo方法通用程序MCNP(3B),从光子与地层相互作用的机理出发 ,计算得到了反散射探测器、长源距探测器和短源距探测器的光子通量的能谱分布、光子通 量与源距的关系、光子通量与地层密度的关系、源距与探测深度的关系以及计数能窗等. 从 结果看,三探测器密度测井仪的长、短源距探测器对地层的响应关系与双源距密度测井仪的 长、短源距探测器一致,而反散射探测器对地层具有明确的响应关系,其响应关系与长、短 源距探测器近似相反,且其计数率很高. 因此,在负源距范围内增加第三个探测器是可行的 ,这将有利于提高密度测井的测量精度和垂向分辨率. 同时表明了Monte Carlo方法在核测 井仪器早期研制中的有效性,对仪器设计具有指导作用. 相似文献
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Fast and accurate P-wave arrival picking significantly affects the performance of earthquake early warning(EEW)systems.Automated P-wave picking algorithms used in EEW have encountered problems of falsely picking up noise,missing P-waves and inaccurate P-wave arrival estimation.To address these issues,an automatic algorithm based on the convolution neural network(DPick)was developed,and trained with a moderate number of data sets of 17,717 accelerograms.Compared to the widely used approach of the short-term average/long-term average of signal characteristic function(STA/LTA),DPick is 1.6 times less likely to detect noise as a P-wave,and 76 times less likely to miss P-waves.In terms of estimating P-wave arrival time,when the detection task is completed within 1 s,DPick′s detection occurrence is 7.4 times that of STA/LTA in the 0.05 s error band,and 1.6 times when the error band is 0.10 s.This verified that the proposed method has the potential for wide applications in EEW. 相似文献
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实验室声发射三维定位及标本波速场各向异性研究 总被引：1，自引：0，他引：1
根据慢度离差法的基本原理,给出由遗传算法确定 Ａ Ｅ 空间位置、发生时刻及慢度离差 ５个参量的具体方法。结合实验条件,通过数值试验对定位误差等问题进行探讨,并对真实 Ａ Ｅ 定位的误差分布给出统计上的圈定。数值试验结果表明,算法具有较高的精度和较好的收敛性及稳健性;探头数量及布设方式对定位结果的优劣有影响,４ 个以上探头有记录时,即可得到理想的结果;大的定位误差主要来源于台阵外部少数“ Ａ Ｅ”的结果。到时测量的随机误差小于最小测量时间单位的５０％ 时,平均有９７％ 的“ Ａ Ｅ”定位误差分布在３ ｍ ｍ 范围内,小于物理不可分辨精度（探头直径） 相似文献
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The rough‐sea reflection‐response varies (1) along the streamer (2) from shot to shot and (3) with time along the seismic trace. The resulting error in seismic data can be important for time‐lapse imaging. One potential way of reducing the rough‐sea receiver error is to use conventional statistical deconvolution, but special care is needed in the choice of the design and application windows. The well‐known deconvolution problem associated with the non‐whiteness of the reflection series is exacerbated by the requirement of an unusually short design window – a requirement that is imposed by the non‐stationary nature of the rough‐sea receiver wavelet. For a synthetic rough‐sea data set, with a white 1D reflection series, the design window needs to be about 1000 ms long, with an application window about 400 ms long, centred within the design window. Although such a short design window allows the deconvolution operator to follow the time‐variation of the rough‐sea wavelet, it is likely to be too short to prevent the non‐whiteness of the geology from corrupting the operator when it is used on real data. If finely spatial‐sampled traces are available from the streamer, the design window can be extended to neighbouring traces, making use of the spatial correlations of the rough‐sea wavelet. For this ‘wave‐following’ approach to be fruitful, the wind (and hence the dominant wave direction) needs to be roughly along the line of the streamer. 相似文献
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Polarization analysis of multi-component seismic data is used in both exploration seismology and earthquake seismology. In
single-station polarization processing, it is generally assumed that any noise present in the window of analysis is incoherent,
i.e., does not correlate between components. This assumption is often violated in practice because several overlapping seismic
events may be present in the data. The additional arrival(s) to that of interest can be viewed as coherent noise. This paper
quantifies the error because of coherent noise interference. We first give a general theoretical analysis of the problem.
A simple mathematical wavelet is then used to obtain a closed-form solution to the principal direction estimated for a transient
incident signal superposed with a time-shifted, unequal amplitude version of itself, arriving at an arbitrary angle to the
first wavelet. The effects of relative amplitude, arrival angle, and the time delay of the two wavelets on directional estimates
are investigated. Even for small differences in angle of arrival, there may be significant error (>10°) in the azimuth estimate. 相似文献
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Tong Shen Xianguo Tuo Huailiang Li Yong Liu Wenzheng Rong 《Journal of Seismology》2018,22(6):1613-1627
First arrival picking is a key factor which affects the precision of microseismic data analysis. Here, we propose a new method, which employs the maximum eigenvalue to constraint the Maeda-Akaike Information Criterion (Maeda-AIC) algorithm. First, aims at addressing the pick result affected by signal-to-noise ratio (SNR) of microseismic data, maximum eigenvalue method based on polarization analysis is applied, and the maximum eigenvalue is calculated firstly, as for three component (3C) microseismic data, the maximum eigenvalue is calculated with corresponding covariance matrix, a time window need to be set in the process of building the covariance matrix, and it is the only time window set in the method proposed in this paper, so the method is called single window Maeda-AIC (SWM-AIC), to the single component (1C) microseismic data, the variance of the data is taken as the maximum eigenvalue. Then, to reduce the effect of time window and increase the automation of the algorithm, Maeda-AIC method which is a non-window-based first arrival picking method is applied. Maeda-AIC values in preliminary window are calculated, and the preliminary window is the sequence before the largest eigenvalue of the 3C or 1C data. We validate the developed method with both synthetic and field microseismic data, using a range of signal-to-noise ratios. The developed method is compared with some basic methods, specifically STA/LTA, Maeda-AIC, and the maximum eigenvalue method. The results demonstrate that the new method is much better at identifying first arrival times than basic methods when the data have a low signal-to-noise ratio, and is even faster than the STA/LTA method with 1C data. In contrast to other improved methods, threshold value is not required for this method, and the only time window used in this method is just for maximum eigenvalue calculation, through test in the paper, its length has almost no effect on the first arrival picking. 相似文献
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BJ
RN URSIN 《Geophysical Prospecting》1977,25(4):658-666
The accuracy of the two most common arrival time functions used in seismic velocity estimation is investigated. It is shown that the hyperbolic arrival time function is more accurate than the parabolic arrival time function for a horizontally layered elastic medium. An upper bound on the difference between the two arrival time functions is given. A maximum-likehood detector for estimating the arrival time of the signals is given. For the signal-in-noise model that is used the maximum-likelihood detector is equivalent to a least-squares detector which corresponds to using the signal energy as coherency measure. The semblance coefficient corresponds to a normalized least-squares detector. The semblance coefficient is very similar to a filter performance measure that is used in least-squares filter design. 相似文献
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本文提出了一种新的反演方法:通过采用纵、横波走时数据对(从相同的震源产生的P和S波被同一台站记录)来联合反演纵波速度(Vp)和纵、横波速度比(Vp/Vs),然后单独反演横波速度Vs,在反演过程中同时对地震参数进行定位。该方法不需要假设P和S波的射线路径一致,它是沿着P和S波射线路径计算相对慢度扰动值。该方法直接把Vp/Vs作为一个模型参数,由此能获得比采用从独立反演获得的Vp和Vs计算出Vp/Vs的方法更精确的速度比值。该新方法被应用到反演日本东北地区的壳幔速度及波速比结构的研究中,获得了较好的效果。反演结果表明,在日本东北地区,太平洋俯冲板块为一高Vp,高Vs和低Vp/Vs异常区,而在活火山下方的浅部地幔楔以及背弧深部地区为低Vp,低VS和高Vp/VS异常。虽然这些特征在前人的研究中已经报道过,但与前人的研究结果相比,本次研究所获得的Vp/Vs的空间分布具有较小的分散性,同时,它的分布特征能较好的与地震波速度结构相吻合。 相似文献