Localization and de-noising seismic signals on SASW measurement by wavelet transform

SASW method is a nondestructive in situ testing method that is used to determine the dynamic properties of soil sites and pavement systems. Phase information and dispersion characteristics of a wave propagating through these systems have a significant role in the processing of recorded data. Inversion of the dispersive phase data provides information on the variation of shear-wave velocity with depth. However, in the case of sanded residual soil, it is not easy to produce the reliable phase spectrum curve. Due to natural noises and other human intervention in surface wave date generation deal with to reliable phase spectrum curve for sanded residual soil turn into the complex issue for geological scientist. In this paper, a time–frequency analysis based on complex Gaussian Derivative wavelet was applied to detect and localize all the events that are not identifiable by conventional signal processing methods. Then, the performance of discrete wavelet transform (DWT) in noise reduction of these recorded seismic signals was evaluated. Furthermore, in particular the influence of the decomposition level choice was investigated on efficiency of this process. This method is developed by various wavelet thresholding techniques which provide many options for controllable de-noising at each level of signal decomposition. Also, it obviates the need for high computation time compare with continuous wavelet transform. According to the results, the proposed method is powerful to visualize the interested spectrum range of seismic signals and to de-noise at low level decomposition.     

Effects of random variations of soil properties on site amplification of seismic ground motions

This paper investigates the effects of random variations of soil properties on site amplification of seismic waves. First, based on attenuation laws and the filtered Tajimi–Kanai spectrum, seismic motion at the base rock of a soil site is stochastically generated according to an assumed earthquake with a given magnitude and epicentral distance. Motions on the surface of this layered random soil site are calculated by nonlinear wave propagation methods, and by assuming the incoming seismic wave consisting of SH wave or combined P and SV waves. Soil properties, including shear modulus, damping ratio and mass density, as well as ground water level are considered as random in the numerical calculation. The Rosenblueth method is used to solve the random dynamic responses of the soil site. Parametric calculations are performed to investigate the effects of various parameters on site amplification of seismic waves. The mean and maximum ground motions on surface of the site are estimated. Numerical results indicate that the estimated surface motions differ substantially if the random variations of soil properties and soil saturation level are taken into consideration in the analysis.     

Suppression of seismic surface waves based on adaptive weighted super-virtual interferometry

For land seismic surveys, the surface waves are the dominant noises that mask the effective signals on seismograms. The conventional methods isolate surface waves from the effective signals by the differences in frequencies or apparent velocities, but may not perform well when these differences are not obvious. Since the original seismic interferometry can only predict inter-receiver surface waves, we propose the use of super-virtual interferometry (SVI), which is a totally data-driven method, to predict shot-to-receiver surface waves, since this method relieves the limitation that a real shot should collocate with one of the receivers for adaptive subtraction. We further develop the adaptive weighted SVI (AWSVI) to improve the prediction of dispersive surface waves, which may be generated from heterogeneous media at the near surface. Numerical examples demonstrate the effectiveness of AWSVI to predict dispersive surface waves and its applicability to the complex near surface. The application of AWSVI on the field data from a land survey in the east of China improves the suppression of the residual surface waves compared to the conventional methods.     

Estimation of rocking and torsion associated with surface waves extracted from recorded motions

By exploiting the capability of identifying and extracting surface waves existing in a seismic signal, we can proceed to estimate the angular displacement (rotation about the horizontal axis normal to the direction of propagation of the wave; rocking) associated with Rayleigh waves as well as the angular displacement (rotation about the vertical axis; torsion) associated with Love waves.For a harmonic Rayleigh (Love) wave, rocking (torsion) would be proportional to the harmonic vertical (transverse horizontal) velocity component and inversely proportional to the phase velocity corresponding to the particular frequency of the harmonic wave (a fact that was originally exploited by Newmark (1969) [15] to estimate torsional excitation). Evidently, a reliable estimate of the phase velocity (as a function of frequency) is necessary. As pointed out by Stockwell (2007) [17], because of its absolutely referenced phase information, the S-Transform can be employed in a cross-spectrum analysis in a local manner. Following this suggestion a very reliable estimate of the phase velocity may be obtained from the recordings at two nearby stations, after the dispersed waves have been identified and extracted. Synthesis of the abovementioned harmonic components can provide a reliable estimate of the rocking (torsional) motion induced by an (extracted) Rayleigh (Love) wave.We apply the proposed angular displacement estimation procedure for two well recorded data sets: (1) the strong motion data generated by an aftershock of the 1999 Chi-Chi, Taiwan earthquake and recorded over the Western Coastal Plain (WCP) of Taiwan, and (2) the strong motion data generated by the 2010 Darfield, New Zealand earthquake and recorded over the Canterbury basin. The former data set is dominated by basin-induced Rayleigh waves while the latter contains primarily Love waves.     

3D surface‐wave estimation and separation using a closed‐loop approach

Surface waves in seismic data are often dominant in a land or shallow‐water environment. Separating them from primaries is of great importance either for removing them as noise for reservoir imaging and characterization or for extracting them as signal for near‐surface characterization. However, their complex properties make the surface‐wave separation significantly challenging in seismic processing. To address the challenges, we propose a method of three‐dimensional surface‐wave estimation and separation using an iterative closed‐loop approach. The closed loop contains a relatively simple forward model of surface waves and adaptive subtraction of the forward‐modelled surface waves from the observed surface waves, making it possible to evaluate the residual between them. In this approach, the surface‐wave model is parameterized by the frequency‐dependent slowness and source properties for each surface‐wave mode. The optimal parameters are estimated in such a way that the residual is minimized and, consequently, this approach solves the inverse problem. Through real data examples, we demonstrate that the proposed method successfully estimates the surface waves and separates them out from the seismic data. In addition, it is demonstrated that our method can also be applied to undersampled, irregularly sampled, and blended seismic data.     

Nonstationary deconvolution using maximum kurtosis optimization

Deconvolution is an essential step for high-resolution imaging in seismic data processing. The frequency and phase of the seismic wavelet change through time during wave propagation as a consequence of seismic absorption. Therefore, wavelet estimation is the most vital step of deconvolution, which plays the main role in seismic processing and inversion. Gabor deconvolution is an effective method to eliminate attenuation effects. Since Gabor transform does not prepare the information about the phase, minimum-phase assumption is usually supposed to estimate the phase of the wavelet. This manner does not return the optimum response where the source wavelet would be dominantly a mixed phase. We used the kurtosis maximization algorithm to estimate the phase of the wavelet. First, we removed the attenuation effect in the Gabor domain and computed the amplitude spectrum of the source wavelet; then, we rotated the seismic trace with a constant phase to reach the maximum kurtosis. This procedure was repeated in moving windows to obtain the time-varying phase changes. After that, the propagating wavelet was generated to solve the inversion problem of the convolutional model. We showed that the assumption of minimum phase does not reflect a suitable response in the case of mixed-phase wavelets. Application of this algorithm on synthetic and real data shows that subtle reflectivity information could be recovered and vertical seismic resolution is significantly improved.     

Determination of dispersive phase velocities for SASW method using harmonic wavelet transform

The spectral analysis of surface waves (SASW) method is an in situ, seismic method for determining the shear wave velocity (or maximum shear modulus) profile of a site. The SASW test consists of three steps: field testing, evaluation of dispersion curve by phase unwrapping method, and determination of shear modulus profile by inversion process. In general, field testing and dispersion curve evaluation are regarded as simple work. However, because of characteristic of Fourier transform used in the conventional phase unwrapping method, dispersion curve is sensitive to background noise and body waves in the low frequency range. Furthermore, under some field conditions such as pavement site, the usual phase unwrapping method can lead to erroneous dispersion curve. To overcome problem of the usual phase unwrapping method, in this paper, a new method of determining dispersion curve for SASW method was applied using time–frequency analysis based on harmonic wavelet transform as an alternative method of a current phase unwrapping method. To estimate the applicability of proposed method to SASW method, numerical simulations at various layered soil and pavement profiles were performed and the dispersion curves by proposed method are more reliable than those by the usual phase unwrapping method.     

浅层地震反射资料的多阶振型面波反演

浅层地震反射波法和面波方法是两种相互独立发展的地震勘探方法,在各自的数据采集和处理中,对方都是作为干扰信号而存在. 本文利用浅层地震反射资料中被视为干扰的面波信号,通过成熟的多道面波勘探技术处理浅层地震反射资料,在频率-波数域中提取多阶振型面波的频散曲线,并基于该曲线反演浅地表S波速度结构. 这种方法充分开发利用了已有数据,无需单独的面波数据采集系统,同时为解释浅层地震反射资料提供了额外的信息约束. 结果表明:浅层地震反射资料中可提取出可靠的多阶振型面波频散曲线,并能给出稳定的反演结果,同时,面波反演的多解性可以通过高阶振型反演得以进一步约束;低速层的存在是观测频散曲线出现振型跳跃或呈“之”字形回折的必要条件而非充分条件.      

地震资料处理中小波函数的选取研究

本文给出了常见地震子波的一个模拟公式，可以很好地模拟零相位及混合相位子波，在一定意义上也可以近似模拟最大相位及最小相位子波．模拟出的子波加上适当的修正项后满足允许条件，可用作小波函数．与Ｍｏｒｌｅｔ小波类似，在实际应用中这些修正项在一定条件下可以略去，文中对Ｍｏｒｌｅｔ小波作了改造，使其能更好地适应于地震资料处理．研究了反射波能量及噪声等干扰波在时间－尺度域的分布特征与所选基本小波的关系．提出用地震子波（或与地震子波相近的函数）作为基本小波，对地震资料进行去噪及分频解释的方法．最后用实例证明方法的有效性．     

利用基于子波估计的频谱校正方法提高Q值估计精度(英文)

用Q值刻画的地震衰减在地震信号处理和解释中具有很广泛的应用。利用反射地震资料进行Q值估计需要解决地震子波和反射系数序列耦合的问题。从反射地震资料中去除反射系数序列的影响,这个过程称为频谱校正。本文提出了一种基于子波估计的求取Q值的方法,进而设计了一个反Q滤波器。该方法利用反射地震资料的高阶统计量进行子波估计,并利用所估计子波实现频谱校正。我们利用合成数据实验给出了质心频移法与频谱比法这两种常用的Q值估计方法在不同参数设置下的性能。人工合成数据和实际数据处理表明,利用本文提出的方法进行频谱校正后,可以得到可靠的Q值估计。经过反Q滤波,地震数据的高频部分得到了有效地恢复。     

基于小波变换的长周期桥梁选波方法研究

时程分析输入地震波的选取对长周期大跨度桥梁影响显著。本文基于规范目标谱,以MATLAB为依托,通过选取最优小波基并利用小波系数迭代法实现频域调整,使地震波反应谱不断逼近给定目标谱,最后结合相对误差和长周期拟合参数两个指标进行综合评价,选取适用于长周期大跨度桥梁的时程分析地震波,提出长周期桥梁全过程批量选波方法。将该方法应用于奉节长江大桥,与基于时域调整方法的Seismo Match选波软件对比选波效果,并将选波结果应用于背景桥梁的时程分析。结果表明,利用本文选波方法所得结构关键截面响应与软件选波所得响应在横桥向和竖桥向存在一定差异。本文方法可为长周期大跨度桥梁时程分析选波提供参考。     

基于小波分析的场地波速测量方法

在场地波速测量中,由于噪声等因素的影响很难准确识别P、S波的初至时刻,致使波速结果存在很大的误差。本文给出了一种基于小波变换的波速测量的新方法。该方法利用波动信号的小波变换与弹性波群速度的关系准确识别弹性波初至时刻。弹性波小波变换的峰值时刻代表着以群速度传播的弹性波的初至时刻,使P波、S波的初至时刻的确定具有明确的物理意义,波速的结果准确、可靠、稳定。此外,波动信号的小波多尺度分析还可以确定地层中传播的弹性波的频散特性。最后,该方法在场地波速测量的实测信号的应用表明该方法可准确确定P、S波速。     

黄土丘陵河谷场地地震动特征研究

研究黄土丘陵河谷场地在地震作用下强地面运动特征的变化情况,可以揭示强震对该类场地上震害的触发机理。结合黄土高原的地貌特征,建立具有代表性的动力数值分析模型,通过输入不同幅值、频谱特性和持续时间的地震波,对起伏地形和覆盖黄土层共同影响下的黄土河谷场地进行地震反应分析。结果表明:黄土层和地形耦合作用控制了地表的PGA变化,使其趋于复杂,在同一输入波不同振幅作用下,与基岩河谷各测点相比,黄土覆盖河谷场地的地震动频谱幅值均有所增加,并且频谱主峰均向高频移动。在不同地震波输入下,场地不同部位的固有频率受地形高程和土层影响;而地震动大小和频谱幅值不仅与场地的基本频谱和地形起伏有关,也与输入地震波的频谱成分相关。输入波PGA与地震频谱特征都不变时,同一场地输出的地震频谱形状具有相似的特征,随着地震持时增长,能量向场地基本频率附近集中,从而可能导致场地上相应频率建筑物震动幅值增加,造成累积破坏。     

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.     

高速列车移动震源地震记录

地球上的环境噪声作为被动震源已被用于地球内部结构研究,在地球科学与工程方面取得了良好的应用效果.随着人类活动频繁加剧,由移动交通工具产生的交通噪声,已经成为一种特别需要关注的环境噪声被动震源.高速运行列车产生的交通噪声,相比其他交通噪声能量强,连续稳定,并且具有可重复性,特别是近十几年来,中国高速铁路发展迅速,形成了覆盖中国大陆的高速铁路网络,为大范围、长期观测高速列车产生的交通噪声并研究其应用提供了基础.我们利用地震勘探检波器,分别采集高速列车运行产生的地震记录以及相同位置无高速列车运行的环境噪声,对地震记录信号以及环境噪声进行了频谱分析以及地震波干涉等处理.频谱分析结果显示,高速列车运行产生的地震信号能量约是环境噪声能量的10³倍,而地震信号频率成分与高速列车运行速度相关.我们分别对高速列车运行产生的地震信号与环境噪声进行了地震波干涉处理,重建出地震初至波以及续至波信息,经过初步分析,重建的初至波地震波场揭示了地表地震波传播特征,而续至波波场十分复杂.高速列车作为一种移动被动震源产生的地震记录具有应用潜力.     

Retrieval of local surface wave velocities from traffic noise – an example from the La Barge basin (Wyoming)

In regions where active source seismic exploration is constrained by limitations of energy penetration and recovery, cost and logistical concerns, or regulatory restrictions, analysis of natural source seismic data may provide an alternative. In this study, we investigate the feasibility of using locally‐generated seismic noise in the 2–6 Hz band to obtain a subsurface model via interferometric analysis. We apply this technique to three‐component data recorded during the La Barge Passive Seismic Experiment, a local deployment in south‐western Wyoming that recorded continuous seismic data between November 2008 and June 2009. We find traffic noise from a nearby state road to be the dominant source of surface waves recorded on the array and observe surface wave arrivals associated with this source up to distances of 5 kms. The orientation of the road with respect to the deployment ensures a large number of stationary points, leading to clear observations on both in‐line and cross‐line virtual source‐receiver pairs. This results in a large number of usable interferograms, which in turn enables the application of standard active source processing methods like signal processing, common offset stacking and traveltime inversion. We investigate the dependency of the interferograms on the amount of data, on a range of processing parameters and on the choice of the interferometry algorithm. The obtained interferograms exhibit a high signal‐to‐noise ratio on all three components. Rotation of the horizontal components to the radial/transverse direction facilitates the separation of Rayleigh and Love waves. Though the narrow frequency spectrum of the surface waves prevents the inversion for depth‐dependent shear‐wave velocities, we are able to map the arrival times of the surface waves to laterally varying group and phase velocities for both Rayleigh and Love waves. Our results correlate well with the known geological structure. We outline a scheme for obtaining localized surface wave velocities from local noise sources and show how the processing of passive data benefits from a combination with well‐established exploration seismology methods. We highlight the differences with interferometry applied to crustal scale data and conclude with recommendations for similar deployments.     

Dispersion Energy Analysis of Rayleigh and Love Waves in the Presence of Low-Velocity Layers in Near-Surface Seismic Surveys

High-frequency surface-wave analysis methods have been effectively and widely used to determine near-surface shear (S) wave velocity. To image the dispersion energy and identify different dispersive modes of surface waves accurately is one of key steps of using surface-wave methods. We analyzed the dispersion energy characteristics of Rayleigh and Love waves in near-surface layered models based on numerical simulations. It has been found that if there is a low-velocity layer (LVL) in the half-space, the dispersion energy of Rayleigh or Love waves is discontinuous and ‘‘jumping’’ appears from the fundamental mode to higher modes on dispersive images. We introduce the guided waves generated in an LVL (LVL-guided waves, a trapped wave mode) to clarify the complexity of the dispersion energy. We confirm the LVL-guided waves by analyzing the snapshots of SH and P–SV wavefield and comparing the dispersive energy with theoretical values of phase velocities. Results demonstrate that LVL-guided waves possess energy on dispersive images, which can interfere with the normal dispersion energy of Rayleigh or Love waves. Each mode of LVL-guided waves having lack of energy at the free surface in some high frequency range causes the discontinuity of dispersive energy on dispersive images, which is because shorter wavelengths (generally with lower phase velocities and higher frequencies) of LVL-guided waves cannot penetrate to the free surface. If the S wave velocity of the LVL is higher than that of the surface layer, the energy of LVL-guided waves only contaminates higher mode energy of surface waves and there is no interlacement with the fundamental mode of surface waves, while if the S wave velocity of the LVL is lower than that of the surface layer, the energy of LVL-guided waves may interlace with the fundamental mode of surface waves. Both of the interlacements with the fundamental mode or higher mode energy may cause misidentification for the dispersion curves of surface waves.     

高铁列车通过高架桥桩基础激发地震波响应分析

当高铁列车行驶通过高架桥时, 其激发和传播地震波的机制与行驶在地面上时的高铁列车是不同的, 同时, 高铁地震波的波传播机制也因地面条件而异.本文结合前期工作, 研究高铁列车行驶通过高架桥(高架桥系统)时高铁地震波的激发机制, 给出改进的震源时间函数, 并对非对称性弹性波动方程下的合成高铁地震记录的响应特征和影响因素进行研究, 以更好地利用高铁列车这一可重复的移动震源进行浅层地质构造成像和反演以及开展工程防护研究.本文应用非对称性弹性波动方程进行高铁地震波数值模拟, 结合高铁实际数据, 研究分析高铁列车运行速度, 地层微孔缝隙特征尺度参数, 检波器位置, 震源类型, 深度衰减系数等多种因素对合成高铁地震记录的影响, 给出以下结论: (1)高铁列车运行速度的增大将使得合成地震记录的持续时间减小, 振幅能量增强, 同时幅频响应的能量逐渐集中在3 Hz、10 Hz和30 Hz附近.(2)地层微孔缝隙特征尺度参数的增大将使得合成地震记录出现衰减, 且主要影响20 Hz以上的频率成分.(3) 岩土介质对高铁地震波传播的影响显著.(4)高铁地震波以"分级点火"的形式激发, 使用Ricker子波作为震源所得的合成地震记录与实际数据匹配较好.(5)随着震源衰减的增大, 将使得合成地震记录出现全频带的衰减.     

Analysis of the spatial variation of seismic waves and ground movements from smart-1 array data

Specially designed arrays of strong motion seismographs located near earthquake sources are required for engineering studies of the near-source properties and the spatial variation of seismic waves. The SMART-1 array in Taiwan provides good records for this type of study. Careful study of the observed strong motion data permits the identification of wave types, directions and apparent wave velocities. In this paper, a principal direction ratio R (f,α) is defined; this indicates the principal direction of the motion (along a nearly straight line) within the range 0 < R < 1. Vertical motion of the ground is also included in this study. Orbit spectrum analysis is used to verify the identification of wave directions and wave types. The spatial variation of seismic waves along the principal direction is studied. From frequency-domain analysis, mathematical models of the spatial variation of ground displacement are developed using a wave-number spectrum and the cross-spectral density function between two spatial coordinates; these models in turn can provide two alternative models for the random vibration analysis of extensive structures subject to multiple point seismic excitation. The SMART-1 array data gathered during the January 29, 1981 earthquake also are used to demonstrate calculation of the ground strains and differential movements of the array site. From time-domain analysis, the spatial variation of seismic waves is defined for ground motion along the identified principal direction. The time variation of evolutionary spectra characterized by frequency-dependent parameters is used for this formulation. The SMART-1 array data again form the basis for discussion of the spatial variation of model parameters.     

Study of Basin-edge Effects on the Ground Motion Characteristics Using 2.5-D Modelling

This paper presents the role of basin-edge geometry in the generation of surface waves using 2.5-D modelling. The simulated responses of various basin-edge models revealed surface wave generation near the basin edge and their propagation normal to the edge. Seismic responses of basin-edge models using different fundamental frequency of soil along with spectral analysis of differential ground motion confirmed that surface waves start generating near the basin edge when body-wave frequency exceeds the fundamental frequency of soil. Spectral analysis of differential ground motion also confirmed the generation of high frequency surface wave. An increase of surface-wave amplitude with soil thickness was obtained. Large ground displacement observed near the basin edge may be due to the interference of surface/diffracted waves with the direct waves and their multiples. The effect of edge roughness on the surface-wave characteristics was found to be negligible as compared with the edge geometry. Simulated results revealed a decrease of surface-wave amplitude with edge slope, particularly in the case of surface waves caused by S waves. Surface wave generation near the basin edge was obtained for all four considered angles of incidence. At the same time, it was also inferred that the characteristics of these surface waves depend on the angle of incidence to some extent. The findings of this paper reveal that basin-edge effects deserve a particular attention for the purpose of earthquake-resistant design and seismic microzonation.Acknowledgement Financial assistance by the Department of Science and Technology (DST) New Delhi and the Indian National Science Academy (INSA), New Delhi is gratefully acknowledged.