基于瑞雷面波群速度频散反演上海地区S波速度结构

利用上海测震台网固定台站地震面波数据记录,通过多重滤波法提取周期为8—20s的瑞雷面波群速度频散曲线,反演得到台站下方介质一维速度结构。结果表明：对于整个上海地区,其剪切波速度横向不均性不明显,在相同深度,每个台站S波速度差异较小,上地壳平均速度约为3.6 km/s,中下地壳平均速度约为3.8 km/s、4.1 km/s。     

利用Rayleigh波反演浅土层的剪切波速度结构

根据均匀半空间Rayleigh波相速度与介质剪切波速度之间的关系,对某一频率面波的影响深度内各层介质进行"均匀"化,使其等效于均匀半空间．并利用模型进行正演,以确定在这种均匀化的前提下,面波勘探深度与波长的关系．应用相匹配滤波技术从实测面波信号中分离出基阶Rayleigh波信号,对它进行多重滤波和叠加处理,精确地计算出5．0-30．0Hz之间的基阶面波相、群速度频散．使用"均匀"化的方法,从相速度频散曲线中获得反演的初始模型,利用群速度频散反演得到35m以上各土层的剪切波速度结构．结果表明,反演结果与钻孔资料较为吻合     

基于小波谱能量曲线EWT的面波压制算法

面波提取和压制是地震资料处理的关键问题之一,对地震资料处理的准确性具有重要影响.针对传统地震面波压制算法面波分离精度低、有效波损伤大的问题,提出一种基于小波谱能量曲线(Wavelet Spectrum Energy Curve,WSEC)经验小波变换(Empirical Wavelet Transform,EWT)的面波压制算法,该算法利用连续小波变换(Continuous Wavelet Transform,CWT)精细化的时频分析能力得到地震信号的WSEC,从频率和能量两个维度对信号进行自适应分解,提高面波提取精度.首先对地震记录进行CWT,根据小波谱计算各频率点的能量得到WSEC;基于WSEC极大值点的频率及ε邻域法确定频谱分割边界进行改进EWT,得到依能量和频率分解的各固有模态分量(Intrinsic Mode Function,IMF);根据各子频带的频率和能量确定面波IMF,最后对面波IMF进行带通滤波以保护其中的有效波.仿真实验表明,算法能根据地震信号的频率和能量自适应分解,实现面波的精准分离与提取;实际地震资料处理表明,算法能准确分离面波,能最大限度保护有效波,提高资料信噪比,是一种有效可靠的面波压制算法.     

地震面波频散的数字计算——方法与试验

在108-乙型数字计算机上进行了地震面波频散处理方法的试验。包括:（1）参数固定的和可变的数值滤波;（2）测定群速度的“移动窗”和“多重滤波”技术;（3）测定相速度的互相关法。应用了快速傅氏变换计算两个台记录的地震面波的互相关函数。使用数字处理技术分析地震面波频散,除了提高计算速度和便于处理之外,还可扩大测量周期的范围至20-70秒,从此可作出对地壳参数性质的更可靠的测定。     

基于背景噪声初步研究河北及邻区的剪切波速度结构

本文根据2010年1～12月河北及邻区的83个宽频地震仪12个月连续噪声记录, 分析了河北及邻区瑞利面波的群速度频散曲线并反演了主要分区内的典型路径剪切波速度结构。 首先采用多重滤波方法提取了台站对5～50 s的面波群速度频散曲线, 然后用Herrmann线性反演方法反演了剪切波速度结构。 结果表明, 群速度频散曲线及剪切波速度分布特征与地表地质和构造特征表现出较好的相关性, 清晰地揭示了地壳内部的横向速度变化。 在短周期(8～20 s), 拥有较厚的沉积层的平原地区表现为明显的低速特征, 而隆起地区则表现为较高的群速度分布特征: 随着周期的增加(>20 s)速度的特征有所改变, 30 s之后由于受地壳厚度的影响, 两者的速度差异逐渐缩小, 在中下地壳波速度随深度增加而增大。 同时, 研究发现在研究区域内西南方向的噪声源占主导作用。     

利用多道信号测定短周期面波频散

使用适配滤波频时分析技术处理面波信号,获取滤波后的时域包络,并对具有相同群速度的各道信号包络的振幅进行叠加,取叠加所得极大值对应的走时为该频率的群延时,以此来提高群速度的测量精度对P-τ,（相慢度-时间）域的波场进行傅氏变换,然后在P-ω（相慢度-频率）平面叠加多道信号来测定相速度．利用这两种方法处理合成的短周期瑞利波地震图,结果表明：经过振型分离以后,利用基阶振型信号所求出的相速度、群速度曲线更加接近理论频散值．对地震勘探资料进行处理,取得了5-40Hz内的相速度、群速度频散,且曲线较为平滑     

华北地区基于噪声的瑞利面波群速度层析成像

本文利用华北地震科学台阵2007年1~4月份、190个宽频带和10个甚宽带垂直分量的地震噪声数据,通过互相关方法提取了瑞利面波的经验格林函数,用多重滤波方法测量了瑞利面波的群速度频散曲线.我们将研究区域划分为0.5°×0.5°的网格,利用噪声层析成像方法得到了研究区域7 s、12 s、16 s、23 s的瑞利面波群速度分布图像,所得结果较好地揭示了地壳内部、尤其是浅部地壳的横向速度变化.研究表明,短周期的群速度分布同地表地质结构、地形密切相关;华北地区的地壳结构具有明显的横向不均匀性,华北盆地及山间的沉积盆地显示出低速异常,而基岩广泛出露的太行山和燕山隆起区,呈现高速异常;多数强震(M≥6.0级)都发生在高群速度与低群速度的过渡地带.     

多地震叠加提取双台间面波频散信息

利用中国HIA台和哈撒克斯坦BRVK台的甚宽频地震仪记录的2011年日本MW9.0大地震及3次MW6——7强余震数据, 采用互相关法提取了双台间的瑞雷波群速度频散曲线．研究发现, 对于同一台记录的大地震和强余震激发的瑞雷波, 其主要能量的周期范围明显不同, MW9.0大地震面波主要能量周期长(70 s以上), 而强余震面波的主要能量周期相对较短（10——50 s）．单独利用大地震数据无法提取60 s以下的群速度频散, 而单独利用强余震数据无法提取100 s以上频散．将双台记录的特大地震、强余震数据进行互相关叠加, 可以提取出较为可靠的宽频带瑞雷波群速度频散曲线（10——200 s）．      

地震信号多尺度分解及弱震相的提取

地震波携带着地球内部(包括震源和介质)的信息,这些信息是研究地球物理及地震的重要依据之一。并以频率、相位、振幅、时间等物理量特征,如何提取这些信息就显得至关重要。傅里叶变换实现了信号从时域到频域的变换,揭示了波列中各频率成分的能量分配,但丢失了时间这一重要信息。Gabor变换对傅氏变换作了推进和发展,通过加窗和平移的方法实现了时域局部化,但由于窗口一经选定,对所有频率的信号都固定不变,无法对高频和低频成分同时获得高分辨率,在许多研究中受到局限。1984年,法国地球物理学家Morlet提出了小波分析的概念和理论,后经许多科…     

利用双台脉动记录的相关系数估计福建地区瑞利面波的群速度

本文利用福建省数字地震监测台网中8个宽频带台站的速度型脉动记录,计算两两台站之间垂直分量的脉动在相同时间窗(窗长为5分钟)的相关系数,按照移动窗技术得到各个不重叠窗口的相关系数,并对其进行相干叠加,依此计算出两个台站之间瑞利面波的群速度及其在福建地区的空间分布。结果表明,叠加结果的信噪比随叠加次数的增加而增加,不同时间段叠加结果波形相似;峰值到时稳定,台风不会对结果产生明显影响;利用这个方法得到的福建地区周期约为3～5秒的瑞利面波群速度在2.9～3.1km/s之间,这和传统方法得到的瑞利面波的传播速度很接近。     

Measurement of interstation phase velocity by wavelet transformation

In this paper,we present wavelet transformation method to measure interstation phase velocity. We use Morlet wavelet function as mother wavelet to filter two seismograms at various period of interest,and correlate the wavelet filtered seismograms to form cross-correlogram. If both wavelet filtered signals are in phase at that period,the phase of the cross-correlogram is a minimum. Using 3-spline interpolation to transform cross-correlation matrix to a phase velocity verse period image,it is convenient for u...     

Analysis of dispersed multi-mode signals of the SASW method using the multiple filter/crosscorrelation technique

Spectral analysis of surface waves (SASW) is a nondestructive in-situ testing method used for determining the thickness and elastic properties of pavement and soil sites using the dispersion characteristics of surface waves. In previous studies, it has been demonstrated that for some sites errors may arise in experimental dispersion curves when the usual SASW test and data analysis procedures are followed, in particular the phase unwrapping procedure and source-to-near-receiver spacing distance. These errors occur due to the participation of more than one surface wave mode in SASW signals. In this study, the multiple filter/crosscorrelation technique often used in earthquake seismology for the analysis of multi-mode earthquake records is presented and applied for calculating phase velocities from SASW signals. It is demonstrated that this technique produces results that are generally more accurate than those produced by the usual phase unwrapping procedure.     

Enhancement of Signal-to-noise Ratio in Natural-source Transient Magnetotelluric Data with Wavelet Transform

—For audio-frequency magnetotelluric surveys where the signals are lightning-stroke transients, the conventional Fourier transform method often fails to produce a high quality impedance tensor. An alternative approach is to use the wavelet transform method which is capable of localizing target information simultaneously in both the temporal and frequency domains. Unlike Fourier analysis that yields an average amplitude and phase, the wavelet transform produces an instantaneous estimate of the amplitude and phase of a signal. In this paper a complex well-localized wavelet, the Morlet wavelet, has been used to transform and analyze audio-frequency magnetotelluric data. With the Morlet wavelet, the magnetotelluric impedance tensor can be computed directly in the wavelet transform domain. The lightning-stroke transients are easily identified on the dilation-translation plane. Choosing those wavelet transform values where the signals are located, a higher signal-to-noise ratio estimation of the impedance tensor can be obtained. ? In a test using real data, the wavelet transform showed a significant improvement in the signal-to-noise ratio over the conventional Fourier transform.     

S变换在面波去噪中的应用r

S变换是一种用于分析非平稳信号的时频变换方法, 可以很好地刻画地震信号的时频特性. 本文将S变换用于地震面波数据的噪声去除中, 首先介绍了S变换的理论基础, 然后设计了时频滤波和阈值滤波两种方法, 分别对天然地震面波数据和背景噪声数据进行去噪处理, 并与相位匹配滤波进行了比较． 结果表明, 面波数据经S变换去噪后, 群速度频散曲线的短周期部分得到改善, 能够连续追踪至6 s左右, 但长周期部分出现了缺失; S变换去噪的效果优于相位匹配滤波, 两者相结合会得到更加理想的结果．      

面波频散测量的频时分析法

总结了面波频时分析(FTAN)的主要成果,如移动窗分析法、多重滤波法、残差频散测量法、时间变量滤波法,力图阐述各方法间的联系.对滤波参数的选择,详细介绍了常相对带宽、均等显示滤波、线性时间分辨、最佳滤波等,其中线性时间分辨是本文首次提出的新方法.对频时分析中的显示技术作了必要的讨论,最后介绍了如何利用频时分析方法作相速度测量.     

基于小波变换方法的包头台形变分析

采用小波变换方法相继对包头台洞体应变和水管倾斜进行处理,研究形变数据固体潮、同震响应和周期性特征等。采用db4作为母小波对包头台形变进行5阶小波分解．分解后的细节部分能清晰地显示出包括1／3日波、半日波、日波和半月波等在内的固体潮汐波。对于2008年以来全球发生的M≥8．0级地震．包头台水管倾斜NS分量均有显著的同震响应现象发生．且在小波分解后的不同阶曲线中同震响应后续波形表现各异．另外在部分地震之前能观测到异常变化。采用Moflet小波作为母小波对包头台水管倾斜NS分量进行小波变换分析．获得的小波变换系数分布图能清晰地显示出倾斜数据中存在的包括半日潮和日潮在内的周期特征及其随时间变化情况。     

Surface wave attenuation based polarization attributes in time-frequency domain for multicomponent seismic data

In the paper, we propose a surface wave suppression method in time-frequency domain based on the wavelet transform, considering the characteristic difference of polarization attributes, amplitude energy and apparent velocity between the effective signals and strong surface waves. First, we use the proposed method to obtain time–frequency spectra of seismic signals by using the wavelet transform and calculate the instantaneous polarizability at each point based on instantaneous polarization analysis. Then, we separate the surface wave area from the signal area based on the surface-wave apparent velocity and the average energy of the signal. Finally, we combine the polarizability, energy, and frequency characteristic to identify and suppress the signal noise. Model and field data are used to test the proposed filtering method.     

Time–Frequency–Wavenumber Analysis of Surface Waves Using the Continuous Wavelet Transform

A modified approach to surface wave dispersion analysis using active sources is proposed. The method is based on continuous recordings, and uses the continuous wavelet transform to analyze the phase velocity dispersion of surface waves. This gives the possibility to accurately localize the phase information in time, and to isolate the most significant contribution of the surface waves. To extract the dispersion information, then, a hybrid technique is applied to the narrowband filtered seismic recordings. The technique combines the flexibility of the slant stack method in identifying waves that propagate in space and time, with the resolution of f–k approaches. This is particularly beneficial for higher mode identification in cases of high noise levels. To process the continuous wavelet transform, a new mother wavelet is presented and compared to the classical and widely used Morlet type. The proposed wavelet is obtained from a raised-cosine envelope function (Hanning type). The proposed approach is particularly suitable when using continuous recordings (e.g., from seismological-like equipment) since it does not require any hardware-based source triggering. This can be subsequently done with the proposed method. Estimation of the surface wave phase delay is performed in the frequency domain by means of a covariance matrix averaging procedure over successive wave field excitations. Thus, no record stacking is necessary in the time domain and a large number of consecutive shots can be used. This leads to a certain simplification of the field procedures. To demonstrate the effectiveness of the method, we tested it on synthetics as well on real field data. For the real case we also combine dispersion curves from ambient vibrations and active measurements.     

Dyadic wavelet analysis of PDA signals

The dyadic wavelet transform is used to analyze PDA measured signals in order to identify the CASE-damping factor, which may be directly calculated from the dyadic wavelet analysis, not from the correlation study; accordingly, the pile capacity may be more exactly estimated by the CASE method. The dyadic wavelet transform can decompose a PDA measured signal into an incident impact wave and a reflected impulse wave at the certain scale that are clearly shown on the wavelet transform graph. The relation between the incidence and the reflection has been established by a transfer function based on the dyadic wavelet transform and the one-dimensional wave equation, whose phase is the time delay between the incident and the reflected and whose magnitude is a function of the CASE-damping factor. An autocorrelation function analysis method is proposed to determine the time delay and to estimate the magnitude of the transfer function that is determined by the ratio of the maximum of the autocorrelation function to the second peak value represented the reflected wave on the autocorrelation function graph. Thus, the damping factor is finally determined. An analog signal, a PIT signal and five PDA signals demonstrate the proposed methods, by which the time delay, the CASE-damping factor, and pile capacity are determined. The damping factors and pile capacity are good agreement with those by CAPWAP.