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1.
基于连续不波变换的大地电磁信号谱估计方法 总被引：3，自引：0，他引：3
在基于连续小波变换的大地电磁信号谱估计方法中,通过引入整体平均、小波系数收缩和显著性检验等统计技术,以提高谱估计的精度。文中同时计论了连续小波换中各种参数的选 取问题,给出了Ｍｏｒｌｅｔ小波函数中尺度与傅里叶频率之间转换的经验公式,并给出了谱估计的具体算法。结果表明,本文方法可有效压制较强的白噪声和局产中相关噪声。与ＦＦＴ谱估计方法相比,该方法大大降低了对信号记录长度的要求,因而对大地电磁信号的处 相似文献
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大地电磁信号具有非线性、非平稳、非最小相位特征,不符合以Fourier变换为基础的传统功率谱估计的基本要求. Hilbert-Huang变换是近年发展起来的处理非线性、非平稳信号的完全局部时频分析方法. 本文在简要介绍Hilbert-Huang变换基本原理与算法基础上,以实际数据分析为例,探讨了它在大地电磁信号处理及噪声压制中的应用. 提出利用Hilbert时-频能量谱对大地电磁信号进行时段筛选,以提高信号品质,增强数据处理的质量和资料的可解释性. 利用经验模态分解方法及其多尺度滤波特征,可以有效地分析MT信号中的噪声分布特征,并进行干扰压制. 相似文献
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低频电磁信号在地下电性结构探测中具有重要作用,经过长距离传播,信号衰减,可能被淹没于噪声中.利用多重自相关检测方法,对微弱低频电磁信号进行检测,并与自适应滤波法和离散小波变换法进行对比.利用Matlab对3种算法进行仿真研究.结果表明,多重自相关法能更好抑制噪声,有效检测微弱信号,检测性能优于小波变换法和自适应滤波法. 相似文献
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基于广义S变换的大地电磁测深数据处理 总被引：9，自引：7，他引：2
S变换是一种优于短时傅里叶变换和小波变换的时频分析方法.采用广义S变换进行大地电磁场时间序列频谱分析,一方面能够提高对电磁噪声成分的时间定位能力,便于实现电磁噪声的滤波处理;另一方面可以增加频谱系数的个数,从而改善大地电磁阻抗张量元素的统计特性.本文从广义S变换和大地电磁测深数据处理方法的原理出发,给出了采用叠加窗函数的离散广义S变换形式,讨论了广义S变换窗口宽度比例因子、窗口宽度与可提取频谱系数个数之间的关系,定义了利用离散广义S变换时频谱计算大地电磁场分量功率谱公式;在此基础上,研究了基于S变换时谱频的大地电磁测深数据ROBUST处理方法.最后,通过实测资料进行方法检验,结果表明本文方法比短时傅里叶变换处理效果更好,并且有利于识别和压制电磁噪声. 相似文献
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尝试性地将一种双树复小波包变换方法应用于地震信号分析中. 复小波包变换综合了实小波包变换与连续复小波变换各自的优点，不但能提取信号的相位信息，而且选取与被分析信号相频特性相匹配的复小波包，可以对信号产生更好的聚焦作用. 本文描述了一种双树复小波包变换算法，并给出了模拟信号及实际地震记录的分析实例. 研究结果表明，双树复小波包变换是分析具有非线性相位地震信号的一种较为有效的方法. 相似文献
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《地球物理学进展》2015,(6)
针对常用大地电磁(magnetotelluric,MT)信号小波阈值去噪中阈值函数和阈值选取的不足,选取一种新的阈值函数,并提出了基于小波变换多分辨Stein无偏风险估计,自适应的获得最优阈值的方法;给出了新函数和自适应阈值的确定方法;在与小波硬、软阈值去噪、小波模极大值法去噪结果对比的基础上,用仿真实验验证了方法的可行性;最后用内蒙某地实测的大地电磁数据进行了去噪效果的对比研究.结果表明:本文选取的新函数和自适应阈值的确定方法是正确、有效的,克服了常用小波硬、软阈值去噪的缺点;去噪后大地电磁信号变得平稳,估算的响应参数方差减小,曲线更为圆滑、连续,为后续的地质解释和评价提供了更为准确的信息. 相似文献
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大地电磁信号整理分析 总被引：1，自引：1，他引：0
小波分析是具有时频多分辨率分析特点的新的信号处理方法,本文应用时间序列反映出大地电磁信号功率谱特性并比较了几种常规实验手段的分析效果,通过小波变换分离出假频所在通道并进行初步除噪,按能量强弱对信号重新截断划分．本文的目的就是尽可能的消除对各组信号不一致的影响因素(局部噪声),提取共性较强的部分并按能量的差异来划分这些信号． 相似文献
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断层等不连续性结构的检测在地震勘探中具有重要的意义.本文简单介绍了高维连续小波变换的基本理论,包括:高维连续小波变换的定义、高维小波变换系数的切片以及快速实现方法等,利用典型的合成信号说明了高维连续小波变换具有更好的方向选择性(相比于常用的高维张量积小波变换),将高维连续小波变换引入地震资料不连续性检测,并提出了利用小尺度高维连续小波变换系数检测地震资料不连续性的方法,同时给出了方法的实现流程.合成信号以及实际三维地震数据处理效果验证了本文所提方法的有效性. 相似文献
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B. BUTTKUS 《Geophysical Prospecting》1975,23(4):712-748
The application of homomorphic filtering in marine seismic reflection work is investigated with the aims to achieve the estimation of the basic wavelet, the wavelet deconvolution and the elimination of multiples. Each of these deconvolution problems can be subdivided into two parts: The first problem is the detection of those parts in the cepstrum which ought to be suppressed in processing. The second part includes the actual filtering process and the problem of minimizing the random noise which generally is enhanced during the homomorphic procedure. The application of homomorphic filters to synthetic seismograms and air-gun measurements shows the possibilities for the practical application of the method as well as the critical parameters which determine the quality of the results. These parameters are:
- a) the signal-to-noise ratio (SNR) of the input data
- b) the window width and the cepstrum components for the separation of the individual parts
- c) the time invariance of the signal in the trace.
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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χ22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. 相似文献
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A new method of Vibroseis deconvolution has been recently proposed by the authors. This discussion describes the effects of noise on the application of this method. The initial deconvolution step involves estimating the spectrum of the Vibroseis wavelet by homomorphic filtering. It is shown that noise causes problems with phase estimation. Hence, the Vibroseis wavelet is assumed to be zero phase. Examples demonstrate that zero phase cepstral filtering is a robust wavelet estimation approach for noisy data. The second step of the deconvolution method forms an impulse response model by a spectral extension method. Although this step can improve the resolution of seismic arrivals, it must be applied with caution in view of the deleterious effects of noise. 相似文献
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基于保角变换的双谱域相位谱估计方法及其在地震子波估计中的应用(英文) 总被引：2，自引：0，他引：2
地震子波估计是地震资料处理与解释中的重要环节,它的准确与否直接关系到反褶积及反演等结果的好坏。高阶谱(双谱和三谱)地震子波估计方法是一类重要的、新兴的子波估计方法,然而基于高阶谱的地震子波估计往往因为高阶相位谱卷绕的原因,导致子波相位谱求解产生偏差,进而影响了混合相位子波估计的效果。针对这一问题,本文在双谱域提出了一种基于保角变换的相位谱求解方法。通过缩小傅里叶相位谱的取值范围,有效避免了双谱相位发生卷绕的情况,从而消除了原相位谱估计中双谱相位卷绕的影响。该方法与最小二乘法相位谱估计相结合,构成了基于保角变换的最小二乘地震子波相位谱估计方法,并与最小二乘地震子波振幅谱估计方法一起,应用到了地震资料混合相位子波估计中。理论模型和实际资料验证了该方法的有效性。同时本文将双谱域地震子波相位谱估计中保角变换的思想推广到三谱域地震子波相位谱估计中。 相似文献
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A. T. WALDEN 《Geophysical Prospecting》1991,39(5):625-642
An accurate estimate of the seismic wavelet on a seismic section is extremely important for interpretation of fine details on the section and for estimation of acoustic impedance. In the absence of well-control, the recognized best approach to wavelet estimation is to use the technique of multiple coherence analysis to estimate the coherent signal and its amplitude spectrum, and thence construct the seismic wavelet under the minimum-phase assumption. The construction of the minimum-phase wavelet is critically dependent on the decay of the spectrum at the low-frequency end. Traditional methods of cross-spectral estimation, such as frequency smoothing using a Papoulis window, suffer from substantial side-lobe leakage in the areas of the spectrum where there is a large change of power over a relatively small frequency range. The low-frequency end of the seismic spectrum (less than 4 Hz) decays rapidly to zero. Side-lobe leakage causes poor estimates of the low-frequency decay, resulting in degraded wavelet estimates. Thomson's multitaper method of cross-spectral estimation which suffers little from side-lobe leakage is applied here, and compared with the result of using frequency smoothing with the Papoulis window. The multitaper method seems much less prone to estimating spuriously high coherences at very low frequencies. The wavelet estimated by the multitaper approach from the data used here is equivalent to imposing a low-frequency roll-off of some 48 dB/oct (below 3.91 Hz) on the amplitude spectrum. Using Papoulis smoothing the equivalent roll-off is only about 36 dB/oct. Thus the multitaper method gives a low-frequency decay rate of the amplitude spectrum which is some 4 times greater than for Papoulis smoothing. It also gives more consistent results across the section. Furthermore, the wavelet obtained using the multi-taper method and seismic data only (with no reference to well data) has more attractive physical characteristics when compared with a wavelet extracted using well data, than does an estimate using traditional smoothing. 相似文献
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R.E. WHITE 《Geophysical Prospecting》1980,28(3):333-358
A crucial step in the use of synthetic seismograms is the estimation of the filtering needed to convert the synthetic reflection spike sequence into a clearly recognizable approximation of a given seismic trace. In the past the filtering has been effected by a single wavelet, usually found by trial and error, and evaluated by eye. Matching can be made more precise than this by using spectral estimation procedures to determine the contribution of primaries and other reflection components to the seismic trace. The wavelet or wavelets that give the least squares best fit to the trace can be found, the errors of fit estimated, and statistics developed for testing whether a valid match can be made. If the composition of the seismogram is assumed to be known (e.g. that it consists solely of primaries and internal multiples) the frequency response of the best fit wavelet is simply the ratio of the cross spectrum between the synthetic spike sequence and the seismic trace to the power spectrum of the synthetic spike sequence, and the statistics of the match are related to the ordinary coherence function. Usually the composition cannot be assumed to be known (e.g. multiples of unknown relative amplitude may be present), and the synthetic sequence has to be split into components that contribute in different ways to the seismic trace. The matching problem is then to determine what filters should be applied to these components, regarded as inputs to a multichannel filter, in order to best fit the seismic trace, regarded as a noisy output. Partial coherence analysis is intended for just this problem. It provides fundamental statistics for the match, and it cannot be properly applied without interpreting these statistics. A useful and concise statistic is the ratio of the power in the total filtered synthetic trace to the power in the errors of fit. This measures the overall goodness-of-fit of the least squares match. It corresponds to a coherent (signal) to incoherent (noise) power ratio. Two limits can be set on it: an upper one equal to the signal-to-noise ratio estimated from the seismic data themselves, and a lower one defined from the distribution of the goodness-of-fit ratios yielded by matching with random noise of the same bandwidth and duration as the seismic trace segment. A match can be considered completely successful if its goodness-of-fit reaches the upper limit; it is rejected if the goodness-of-fit falls below the lower one. 相似文献
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根据维纳滤波理论导出的位场向下延拓滤波器为最佳下延滤波器,但因其实现需要已知待求位场和噪声的功率谱而在实际应用中受到限制.针对该问题,本文首先提出一种基于位场径向平均功率谱的位场噪声水平估计方法,进而利用偏差准则求取正则化参数,实现位场正则化向下延拓;然后将位场正则化下延结果的功率谱作为待求位场功率谱的估计初值,采用带修正项的迭代维纳滤波方法来更新对待求位场功率谱的估计,最后提出本文的位场向下延拓改进迭代维纳滤波方法.基于理论重力模型数据及航磁实测数据进行了向下延拓对比试验,结果表明,改进迭代法具有较好的收敛性,且下延精度优于Tikhonov正则化法和递增型维纳滤波法. 相似文献
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Joint AVO inversion, wavelet estimation and noise-level estimation using a spatially coupled hierarchical Bayesian model 总被引：1，自引：0，他引：1
The main objective of the AVO inversion is to obtain posterior distributions for P-wave velocity, S-wave velocity and density from specified prior distributions, seismic data and well-log data. The inversion problem also involves estimation of a seismic wavelet and the seismic-noise level. The noise model is represented by a zero mean Gaussian distribution specified by a covariance matrix. A method for joint AVO inversion, wavelet estimation and estimation of the noise level is developed in a Bayesian framework. The stochastic model includes uncertainty of both the elastic parameters, the wavelet, and the seismic and well-log data. The posterior distribution is explored by Markov-chain Monte-Carlo simulation using the Gibbs' sampler algorithm. The inversion algorithm has been tested on a seismic line from the Heidrun Field with two wells located on the line. The use of a coloured seismic-noise model resulted in about 10% lower uncertainties for the P-wave velocity, S-wave velocity and density compared with a white-noise model. The uncertainty of the estimated wavelet is low. In the Heidrun example, the effect of including uncertainty of the wavelet and the noise level was marginal with respect to the AVO inversion results. 相似文献
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大地电磁法(MT)以成本低廉,探测深度大、水平方向分辨能力高等优点,在矿产资源勘探方面得到广泛应用.然而,在老矿区或者矿区周围进行二次探矿时,强人文干扰严重影响观测数据的质量,导致反演结果出现偏差,甚至出现错误的解释结果.因此,需要对观测数据进行降噪处理.结合多分辨率分析算法和小波阈值算法的特点,本文提出了综合小波算法:采用db3小波基;基于多分辨率分析算法,去除长周期噪声;基于小波阈值算法,将Bayes估计配合改进型阈值函数去除短周期噪声干扰.对实测数据的处理结果显示,处理后的数据的时间序列以及视电阻率曲线质量都有了明显的改善,近源效应得到有效的抑制. 相似文献