基于地震信号波形形态差异的面波噪声稀疏优化分离方法

实际地震信号通常可表示为具有波形特征差异的多种基本波形信号的线性组合,如叠前道集中的工频干扰噪声与有效波信号、面波噪声与体波信号等.选择单一数学变换方法,往往不易实现地震信号的稀疏表示.近年来发展的形态成分分析理论,通过联合多种数学变换,可实现对复杂信号的稀疏表示.本文根据单道地震记录中面波与体波信号波形结构特征的差异性,提出一种基于形态成分分析的面波噪声衰减方法.针对面波的低频、窄带以及频散特性选择一维平稳小波变换作为其稀疏表示字典,而针对体波波形的局部相关特性选择局部离散余弦变换作为其稀疏表示字典,建立基于双波形字典的形态成分分析模型,通过求解该稀疏优化问题获得最终的信噪分离结果.理论模型和实际地震资料处理证实该方法不仅能够衰减单炮地震记录中的强面波干扰噪声,同时能够更好地保护有效信号的波形特征与频谱带宽,为地震资料的后续处理和分析提供良好的数据基础.     

叠前地震资料噪声衰减的小波域方法研究

讨论了叠前地震记录中随机噪声的模拟方法,采用定性分析与Monte Carlo仿真相结合的方法,研究了在物理小波为基本小波的变换域该类随机噪声局部小波功率谱的统计特性,得出：其局部小波功率谱服从χ22分布.在此基础上,利用假设检验给出了在给定置信度下确定有效信号在小波变换域内能量分布空间的方法,通过在有效信号能量分布空间重建信号来压制噪声.给出了模型及实际地震资料算例,证明了本文提出的方法的有效性.     

用于三分向记录震相识别的小波变换方法

应用包含在小波变换系数中的信号偏振信息,提出了一种确定单台三分向记录图中Ｐ波和Ｓ波震相的小波变换方法．主要的思路是寻找地震信号在不同尺度下小波变换系数的显著特性．通过对小波变换系数主成分的分析,得到不同尺度下的Ｐ波和Ｓ波识别因子,进而形成确定Ｐ波和Ｓ波初至的定位函数．通过对模拟资料和实际地震资料的分析,认为由小波变换方法形成的定位函数具有一定的抗噪声能力,在精确识别Ｐ波和Ｓ波初至方面是非常有效的．本文首先介绍了小波变换的基本概念和详细方法,然后应用小波变换对实际资料进行处理,并给出了研究结果．      

基于分数阶小波域GSM模型的地震信号随机噪声压制方法

地震信号中的随机噪声是一种干扰波,严重降低了地震信号的信噪比,并影响着资料的后续处理和分析.本文根据地震信号中有效信号和随机噪声的差异,结合分数阶B样条小波变换与高斯尺度混合模型提出了一种地震信号随机噪声压制方法.首先利用分数阶B样条小波变换将含噪地震信号映射到最优分数阶小波时频域内,然后对各小波子带系数分别建立高斯尺度混合模型,由贝叶斯方法估计出源地震信号小波系数,最后使用分数阶B样条小波逆变换重构得到降噪后的地震信号.利用本文方法对合成地震记录和实际地震信号进行降噪处理,实验结果表明本文方法能够有效地压制地震信号中的随机噪声,并且较好地保留了有效信号.     

基于CUDA技术与GCV准则的小波变换压制地震面波的研究

压制噪声的同时能够最大程度的保留有效信号是滤波处理过程中的难点.在对地震记录频谱进行分析的基础上,认为基于GCV准则的离散小波变换自适应阈值萎缩方法可以有效分离地震记录在低频区的有效信号和面波噪声.通过该方法滤波处理,有效压制了地震记录的面波噪声,使得地震记录的信噪比得到大幅度提高.且自适应阈值处理降低了人工数据处理对地震记录造成的主观偏差,使得处理结果更为精确可靠.在前述方法研究的基础上,进一步分析讨论了地震信号小波变换滤波算法的GPU/CPU协同计算模式,并将其应用于实际地震记录的滤波处理.通过对比单独使用CPU计算和GPU/CPU协同计算模式的时间花销,后者计算效率得到显著提升,整体加速比最高达到了22倍.     

基于地震子波支撑和Curvelet域稀疏约束的面波衰减方法

面波噪声衰减是地震数据处理流程中的重要一环,传统的面波衰减方法主要依靠面波与有效信号的几何特征差异,在变换域中将两者进行分离.受复杂近地表因素的影响,面波往往呈现非线性特征,并且在变换域中面波与有效信号存在部分重叠,这都导致面波噪声与有效信号难以彻底分离,消除面波的同时也损伤了有效信号.针对这一问题,本文综合利用Curvelet变换对地震数据的稀疏表征特性以及地震子波支撑来构建方程,通过Curvelet域稀疏约束来恢复压制面波时损失掉的有效信号.文中对该方法进行了模型试算和实际资料处理,处理结果表明:本文方法能够在一定程度上恢复损失的有效信号,提高了面波压制方法的保幅性.     

基于小波分频叠前相干噪声压制方法

基于小波分析的去噪方法在地震资料叠前处理中得到了广泛应用.本文主要介绍利用小波变换的分频特性来压制相干噪声.通过小波分频技术将叠前地震信号分解为不同频带,然后利用有效波和相干干扰波的频谱差异来区分有效信号和噪声,最后利用加权方法去掉不需要的噪声信息来达到去除相干噪声的目的.实际资料的处理结果表明：基于小波分频方法能很好地压制相干噪声,从而提高地震资料信噪比和分辨率.     

二进小波变换方法的地震信号分时分频去噪处理

应用二进小波变换理论，对地震记录剖面进行小波分解，在小波变换域，对各分量剖面进行分时分频相关分析，并依此进行加权处理，最后通过小波反交换算法恢复出地震记录剖面．经实验该方法对衰减地震信号的噪声具有比较好的效果．     

基于小波分频与径向道变换的联合压制面波方法（英文）

面波是地震记录上严重的干扰波。基于小波变换的面波衰减方法考虑了面波频率低的特点,但是当有效信号和面波干扰存在频率重叠时,其压制效果不理想。径向道变换考虑了面波与有效信号视速度差异,有利于去噪,但是在去除面波的同时也会损害有效信号的低频分量。本文根据面波和有效信号在视速度以及小波域能量的差别,将小波变换的局部分析能力与径向道变换的去噪优势相结合,提出了基于小波分频与径向道变换的联合面波压制方法。首先应用小波变换,将地震记录分解为不同频段,对出现面波的频段作径向道变换,然后再作低切滤波处理,最后利用径向道反变换后的记录与其他频段的记录进行小波重构得到去除面波的记录。两种方法的联合使用提高了小波分频去除面波的能力,同时也较好的保护了有效信号。通过模型数据实验分析和实际资料数据处理的结果表明,本文提出的方法具有较强的去噪能力和良好的保幅性能。     

基于小波包变换的滤波方法

基于小波包变换的基本原理,提出了对不同频率范围的信号和噪声进行滤波处理的方法．利用该方法可将噪声与信号分离以及将不同频段信号分解,从而达到滤波的目的．仿真结果表明,小波包变换具有许多其它分析手段所不具备的优点,是一种有效的滤波方法,可应用于地震信号的预处理     

钻柱振动倒谱分析及其钻头源信号提取方法研究

随钻地震参考信号处理的关键是从众多噪音成分中提取较弱的钻头源信号.钻头随机激励源信号由于其频率范围宽,持续时间短,易受钻柱和其他机器噪音的影响.倒谱分析方法是一种非线性滤波技术,该技术不但可以将时域卷积信号转变为倒时域信号的相加,而且通过窗函数的选择,还可消除结构混响,提取源信号.本文根据钻柱模拟实验数据,利用了倒谱滤波技术进行瞬态源信号的提取,并用该方法进行SWD参考信号的处理,从而达到钻头源信号强化的目的.     

Acoustic full waveform inversion of synthetic land and marine data in the Laplace domain

Elastic waves, such as Rayleigh and mode‐converted waves, together with amplitude versus offset variations, serve as noise in full waveform inversion using the acoustic approximation. Heavy preprocessing must be applied to remove elastic effects to invert land or marine data using the acoustic inversion method in the time or frequency domains. Full waveform inversion using the elastic wave equation should be one alternative; however, multi‐parameter inversion is expensive and sensitive to the starting velocity model. We implement full acoustic waveform inversion of synthetic land and marine data in the Laplace domain with minimum preprocessing (i.e., muting) to remove elastic effects. The damping in the Laplace transform can be thought of as an automatic time windowing. Numerical examples show that Laplace‐domain acoustic inversion can yield correct smooth velocity models even with the noise originating from elastic waves. This offers the opportunity to develop an accurate smooth starting model for subsequent inversion in the frequency domain.     

基于非稳态多项式拟合的地震噪声衰减方法研究(英文)

基于非稳态多项式拟合理论,针对地震数据中同相轴振幅变化这一特征,我们提出了一种地震噪声衰减的新方法。非稳态多项式拟合系数是时变的,通过整形正则化约束多项式拟和系数的光滑性,自适应的估计地震数据的相干分量。基于动校正后的共中心点道集(CMP)中地震信号的相干性,利用非稳态多项式拟合估计有效信号,从而衰减随机噪声。对于线性相干噪声,如地滚波,首先利用径向道变换(RadialTraceTransform,RTT)将地震数据变换到时间一视速度域,在时间—视速度域利用非稳态多项式拟合估计出相干噪声,然后减去相干噪声。该方法可以有效的估计振幅变化的相干分量,不需要相干分量振幅为常量的假设。模拟和实际资料处理结果表明,与传统的稳态多项式拟合和低切滤波相比,该方法可以更为有效的衰减地震噪声,同时保真了地震有效信号。     

金属矿山地地区地震勘探随机噪声的波动方程模拟

消减随机噪声是目前陆地地震勘探数据处理的关键问题之一,分析随机噪声的产生机制及特征是对其进行有效压制的先决条件.本文针对中国南方山地金属矿区的勘探环境,根据随机噪声中包含的自然噪声和人文噪声的发声机理分别确定其噪声源函数,以波动方程作为噪声传播模型对山地地区随机噪声进行建模,将随机噪声作为一个综合波场,并且与实际噪声记录进行比较.随机噪声记录作为时空域的二维随机过程,分别对模拟噪声和实际噪声记录的时间域波形(振动图)特征包括频谱、功率谱密度,相空间轨迹图,统计量特征(能量分布,累积分布,均值,方差,峰度,偏度),和空间域波形(波剖面)特征包括波数谱和统计量特征进行比较,对比结果显示在时空域模拟噪声和实际噪声都有基本相同的性质,证明了本文对随机噪声模拟方法的可行性,为进一步研究随机噪声时空域传播特性以及噪声消除奠定理论基础.     

Periodicity in midwest US climatic data: the Hale cycle signal or the luni-solar signal?

Cohen and Sweeter (1975) found the 20 to 22-year Hale (double sunspot) cycle signal in the maximum entropy spectra of sunspot and Atlantic tropical cyclone data. Currie (1996) corroborated and extended their analysis, but he argued that this signal is the 18.6-year luni-solar tidal constituent. Currie maintains that Cohen and Sweeter mistakenly conjectured that this long term periodicity was induced by the 20 to 22-year Hale cycle signal. However, no further investigation of periodicity in the extracted wave forms corresponding to the 18.6-year luni-solar signal was conducted. In this study, we follow Currie's signal processing procedures to extract the wave forms corresponding to the 18.6-year luni-solar signal. In order to investigate the periodicity in the extracted wave forms, multi-taper method (MTM) is used for harmonic analysis. Band pass filters are then designed to extract the wave forms corresponding to the individual components identified in the MTM harmonic analysis. The investigation results of the monthly precipitation and Palmer's drought severity index (PDSI) data in three of the midwestern states – Illinois, Indiana and Ohio – show that two periodic components, the 20 to 22-year Hale cycle signal and the other component with periods between 16.9 and 13.5 years, are identified. The bistability phenomenon, which Currie found in these wave forms, is more likely to result from the superposition of these two periodic components, rather than from a nonlinear mechanism. Besides, a periodic component with an approximate period of 33 years is detected.     

Periodicity in midwest US climatic data: the Hale cycle signal or the luni-solar signal?

Cohen and Sweeter (1975) found the 20 to 22-year Hale (double sunspot) cycle signal in the maximum entropy spectra of sunspot and Atlantic tropical cyclone data. Currie (1996) corroborated and extended their analysis, but he argued that this signal is the 18.6-year luni-solar tidal constituent. Currie maintains that Cohen and Sweeter mistakenly conjectured that this long term periodicity was induced by the 20 to 22-year Hale cycle signal. However, no further investigation of periodicity in the extracted wave forms corresponding to the 18.6-year luni-solar signal was conducted. In this study, we follow Currie's signal processing procedures to extract the wave forms corresponding to the 18.6-year luni-solar signal. In order to investigate the periodicity in the extracted wave forms, multi-taper method (MTM) is used for harmonic analysis. Band pass filters are then designed to extract the wave forms corresponding to the individual components identified in the MTM harmonic analysis. The investigation results of the monthly precipitation and Palmer's drought severity index (PDSI) data in three of the midwestern states – Illinois, Indiana and Ohio – show that two periodic components, the 20 to 22-year Hale cycle signal and the other component with periods between 16.9 and 13.5 years, are identified. The bistability phenomenon, which Currie found in these wave forms, is more likely to result from the superposition of these two periodic components, rather than from a nonlinear mechanism. Besides, a periodic component with an approximate period of 33 years is detected.     

Investigation of karstic hydrological processes of Niangziguan Springs (North China) using wavelet analysis

Niangziguan Spring complex is the largest karst spring in North China. We investigate the karst hydrological processes by using Morlet wavelet transform analysis and cross wavelet analysis based on monthly precipitation from 1958 to 2010 and spring discharge from 1958 to 2009. From Morlet wavelet transform coefficients of precipitation and the spring discharge in Niangziguan Springs Basin, we find that the precipitation and discharge are characterized by the multi‐scale features in the time domain, and the energy distribution of the signal is highly irregular across scales. Although precipitation eventually becomes spring discharge by infiltrating and propagating through karst formations, the signals are attenuated. The results also show that the precipitation of Niangziguan Springs Basin has the main periodic components of 1‐, 5‐, 12‐, and 17‐year periods with alternating wet–drought cycle. Similarly, the spring discharge of Niangziguan Springs has the main components of 17‐year periods, but the 1‐, 5‐, and 12‐year periodicity of precipitation are not reflected in spring discharge, which is filtered by the aquifers. The results of cross wavelet analysis reveal that the precipitation and spring discharge share the common periodicity of 17 years. This means that those signals with high energy and long timescales can penetrate through the aquifer and be reflected in spring discharge, whereas other signals are filtered and modified. Copyright © 2011 John Wiley & Sons, Ltd.     

Analyses on normal background characteristics about deformation observation data on the basis of wavelet transform method

Introduction Fourier transform that summed up a series discomposed sin functions of signal has been one of the widely used methods in the field of signal process all along. While for time information be-ing thrown away by this transform, it is difficult for us to judge when a special signal occurs on the way. Though short time Fourier transform (STFT) was developed later, which can probe local features of signals, it can not reveal what is really there because uniform window functions de-fin…     

基于S变换的软阈值滤波在深地震反射数据处理中的应用

深地震反射原始单炮数据是非平稳的弱能量反射信号,信噪比较低.如何提高信噪比一直是深地震反射数据前处理中的一大难题.S变换是一种适用于分析非平稳信号的时频变换方法.同其他分析时变信号的方法相比,S变换的基本小波不必满足小波在时间域均值为零的容许性条件,它的时频分辨率与分析信号的频率有关,且其在时间域的积分可以得到傅里叶频谱,其反变换也简单.因此,S变换容易表示深地震反射信号复杂的时频特性.本文在S变换的基础上,利用软阈值滤波方法对深地震反射数据进行处理,实验结果表明,该方法有效地提高了信噪比,压制了有效频带范围内的混频干扰,突出了弱反射信号,使得波组信息更加丰富,有利于连续追踪有效反射波组和识别薄地层,特别是提高了深部Moho界面反射层位的分辨率,为深地震反射剖面后续处理和准确解释奠定了基础.     

利用小波变换方法分析形变观测资料的正常背景变化特征

为定量刻画数字化形变观测资料中背景信息和噪声的时 频分布特征, 本文应用二进小波变换方法, 通过对小波分解的主模特征和随机白噪声识别因子变化特征分析, 剖析了山东数字化形变观测资料的正常动态背景和噪声变化规律. 结果表明, 当尺度取2, 3和4时, 分解后的细节部分存在着1/4日波、 半日波、 日波和半月波等准循环周期信号, 其中尤以尺度为3时的信号波幅最大; 尺度取1和5时的细节部分主要包含着噪声; 通过分析和追踪指定尺度的数字化形变观测资料小波变换的非震异常特征变化, 可望捕捉到与强地震孕育过程有关的前兆异常信息.