SVD与EMD联合去噪方法在地震勘探数据处理中的研究与应用

将基于倾角扫描的奇异值分解与经验模式分解法相结合应用到地震资料随机噪声压制中。首先利用经验模式分解法消除部分噪声,增强地震道有效信号的相关性,再利用奇异值分解对地震信号进行同相轴自动追踪,截取小时窗数据体,并进行同相轴拉平处理,经SVD计算小时窗数据中心点的值来代替计算样点的值,最终实现随机噪声的压制。理论模型试算和实际资料处理表明,本文提出的EMD-SVD方法简单易行,比单一的SVD方法去噪效果更显著有效地消除了地震资料中的随机噪声,提高了地震资料的信噪比,并改善了叠加剖面的质量。     

时频域相位滤波在远震接收函数噪声压制中的应用

宽频带地震观测数据中有效信号和干扰噪声经常发生混频效应,常规的频率域滤波方法很难将二者分离.地震波信号属于时变非平稳信号,时频分析方法能够同时得到地震波信号随着时间和频率变化的振幅和相位特征,S变换是其中较为高效的时频分析工具之一.本文以S变换为例,提出了基于相位叠加的时频域相位滤波方法.与传统叠加方法相比,相位叠加方法对强振幅不敏感,对波形一致性相当敏感,更加利于有效弱信号信息的检测.时频域相位滤波方法滤除与有效信号不相干的背景噪声,保留了相位一致的有效信号成分,显著提高了信噪比.运用理论合成的远震接收函数数据和实际的宽频带地震观测数据检验结果显示该方法较传统的带通滤波方法相比,即使在信噪较低且混频严重条件下,时频域相位滤波方法的滤波效果依然很明显,有助于识别能量较弱的有效信号.     

地震记录小波域高阶相关叠加技术

水平叠加技术能够有效地压制随机噪声和多次波,但是对于由于相邻道的噪声表现出相关性和一致性而产生的某些相干干扰,常规的叠加技术容易产生假的同相轴,难以取得较高的信噪比.基于小波理论和高阶统计理论本文提出了小波域高阶相关叠加技术(HOCS),其基本原理是将经动静校正的CMP道集变换到小波域,然后在小波域求取高阶相关系数,进而加权叠加.数值实验和实际资料计算的结果表明,此方法比常规叠加更能够有效地提高信噪比,剔除常规加权叠加无法抑制的某些相关噪声.     

复杂地表条件下共反射面元(CRS)叠加方法研究

在地表地形复杂的情况下,静校正不易做好,这是制约山地资料处理质量的一个很重要的因素.复杂地表共反射面元（CRS）叠加不需对叠前数据做静校正,而且在得到叠加剖面后可以利用叠加得到的波场参数剖面实现基准面重建.地震数据的试算表明,复杂地表CRS叠加得出的剖面与常规处理剖面相比有着较高的信噪比和同相轴连续性.与水平地表CRS叠加不同的是,在复杂地表CRS叠加的时距公式中,波场三参数耦合,难以通过简化CRS道集的方法将它们全部分离并逐个优化.引入模拟退火算法后,有效地解决了这一组合优化的难题.     

WEIGHTED STACKING OF SEISMIC DATA USING AMPLITUDE-DECAY RATES AND NOISE AMPLITUDES1

The signal-to-noise (S/N) ratio of seismic reflection data can be significantly enhanced by stacking. However, stacking using the arithmetic mean (straight stacking) does not maximize the S/N ratio of the stack if there are trace-to-trace variations in the S/N ratio. In this case, the S/N ratio of the stack is maximized by weighting each trace by its signal amplitude divided by its noise power, provided the noise is stationary. We estimate these optimum weights using two criteria: the amplitude-decay rate and the measured noise amplitude for each trace. The amplitude-decay rates are measured relative to the median amplitude-decay rate as a function of midpoint and offset. The noise amplitudes are measured using the data before the first seismic arrivals or at late record times. The optimum stacking weights are estimated from these two quantities using an empirical equation. Tests with synthetic data show that, even after noisy-trace editing, the S/N ratio of the weighted stack can be more than 10 dB greater than the S/N ratio of the straight stack, but only a few decibels more than the S/N ratio of the trace equalized stack. When the S/N ratio is close to 0 dB, a difference of 4 dB is clearly visible to the eye, but a difference of 1 dB or less is not visible. In many cases the S/N ratio of the trace-equalized stack is only a few decibels less than that of the optimum stack, so there is little to be gained from weighted stacking. However, when noisy-trace editing is omitted, the S/N ratio of the weighted stack can be more than 10 dB greater than that of the trace-equalized stack. Tests using field data show that the results from straight stacking, trace-equalized stacking, and weighted stacking are often indistinguishable, but weighted stacking can yield slight improvements on isolated portions of the data.     

N次根倾斜叠加方法在间断面研究中的应用

将N次根倾斜叠加应用于地幔间断面研究,通过实例计算,给出了不同次根倾斜叠加的结果,展示了N次根倾斜叠加方法的特点,不但可以增加信噪比,而且还提高了信号的清晰度,但有时会引起信号的畸变.N的选取取决于资料的噪声分布、信噪比和台站个数等因素.本文讨论了间断面倾斜对信号相对于参考震相的走时差、水平慢度差的影响,为分析倾斜叠加结果提出了修正标准,并为准确确定间断面深度提供了依据.     

基于多用户峰度准则的海洋强噪声衰减方法(英文)

海洋地震勘探过程中,由于采集设备的老化或电源的不稳定而造成的漏电,在地震记录表现为强噪音干扰,利用常规噪音衰减方法处理此类强噪音效果并不理想。鉴于强噪音在统计学上具有相同的特性,本文在基于峰度的盲分离(blind source separation,BSS)算法研究基础上,推导出一种基于多用户峰度(multiuser kurtosis,MUK)准则的噪音衰减算法来估计地震记录中具有相同统计特性的强噪音,并将其从地震记录中分离,从而达到衰减强噪音的目的。模型试验与实际资料的处理表明:该方法能够在好的衰减海洋地震勘探记录中的强噪音,保留了更多的有效信息,提高海洋地震数据的信噪比,具有可行性和应用前景。     

Common-Reflection-Surface Stack for Converted Waves

The finite-offset (FO) common-reflection-surface (CRS) stack has been shown to be able to handle not only P-P or S-S but also arbitrarily converted reflections. It can provide different stack sections such as common-offset (CO), common-midpoint (CMP) and common-shot (CS) sections with significantly increased signal-to-noise ratio from the multi-coverage pre-stack seismic data in a data-driven way. It is our purpose in this paper to demonstrate the performance of the FO CRS stack on data involving converted waves in inhomogeneous layered media. In order to do this we apply the FO CRS stack for common-offset to a synthetic seismic data set involving P-P as well as P-S converted primary reflections. We show that the FO CRS stack yields convincing improvement of the image quality in the presence of noisy data and successfully extracts kinematic wavefield attributes useful for further analyses. The extracted emergence angle information is used to achieve a complete separation of the wavefield into its P-P and P-S wave components, given the FO CRS stacked horizontal and vertical component sections.     

GNMF小波谱分离在地震勘探噪声压制中的应用

地震勘探资料噪声压制及信噪比提高是整个地震勘探信号处理过程中的重要任务,随着地震勘探深度的增加及其复杂性,人们对地震数据质量的要求越来越高.勘探环境的复杂化使得采集到的地震资料中有效信号被大量噪声淹没,无法清晰辨识,严重影响后续的数据处理与解释.小波去噪是地震勘探中常用且发展较成熟的一种方法,但是其涉及到的阈值函数选取问题一直令人困扰,虽然已有多种阈值函数被提出,但仍存在各自的缺陷.本文利用小波分解在时域及频域良好的信号细节体现特性,引入模式识别中的非负矩阵分解(NMF)谱分离思想,针对小波系数阈值优化问题,提出了一种小波域图非负矩阵分解(GNMF)消噪算法.该方法首先在小波分解基础上,利用GNMF算法实现小波分解系数谱中信号分量与噪声分量的谱分离,然后通过反变换重构各分离子谱对应的子信号,最后利用K均值聚类算法将得到的多个子信号划分为信号类及噪声类,最终得到重构信号及分离噪声.合成记录和实际地震资料的消噪结果验证了新方法在提高信号与噪声分离准确性和精度方面的有效性,同时新方法避免了阈值选取造成的噪声压制不理想或有效成分损失问题.与小波消噪结果的对比及数值分析也说明了新方法在噪声压制及有效成分保持方面的优势.     

Generalized diffraction‐stack migration and filtering of coherent noise

We reformulate the equation of reverse‐time migration so that it can be interpreted as summing data along a series of hyperbola‐like curves, each one representing a different type of event such as a reflection or multiple. This is a generalization of the familiar diffraction‐stack migration algorithm where the migration image at a point is computed by the sum of trace amplitudes along an appropriate hyperbola‐like curve. Instead of summing along the curve associated with the primary reflection, the sum is over all scattering events and so this method is named generalized diffraction‐stack migration. This formulation leads to filters that can be applied to the generalized diffraction‐stack migration operator to mitigate coherent migration artefacts due to, e.g., crosstalk and aliasing. Results with both synthetic and field data show that generalized diffraction‐stack migration images have fewer artefacts than those computed by the standard reverse‐time migration algorithm. The main drawback is that generalized diffraction‐stack migration is much more memory intensive and I/O limited than the standard reverse‐time migration method.     

Reliability Evaluation on Weak Signal Extraction for Airgun Source Surveys

Based on the data synthesis simulation and the actual processing of the airgun seismic source signal, three quantitative indicators of signal-to-noise ratio, waveform correlation coefficient and phase offset, are superimposed. We systematically evaluate the functions of the following three stack methods including linearity, phase weighting and S-transform in the extraction of weak signals under strong background noise and quantitatively estimate the reliability of the stack results. Through the comprehensive discussion of the above three methods of stack results, the preliminary comparative analysis believes that the linear stack signal-to-noise ratio is low, but the waveform distortion is minimal; the phase-weighted superimposed signal-to-noise ratio is high and the phase offset is small, but the results of the waveform quality and linear stack are larger than the deviation; the S-transform stack has a relatively higher signal-to-noise ratio and a small loss of waveform amplitude, but there is a certain phase shift phenomenon. It is therefore suggested that linear stack technology should be used when the requirements of both waveform quality and time precision are high. However, the selection of the stack method when the airgun source excitation is limited should be emphasized. If high fidelity is required, the S-transform stack method should be selected; if the required time is high, accuracy can be selected by phase-weighted stack method to achieve reasonable extraction of weak signals.     

HORIZONTAL STACKING AND MULTICHANNEL FILTERING APPLIED TO COMMON DEPTH POINT SEISMIC DATA*

The common depth point method of shooting in oil exploration provides a series of seismic traces which yield information about the substrata layers at one location. After normal moveout and static corrections have been applied, the traces are combined by horizontal stacking, or linear multichannel filtering, into a single record in which the primary reflections have been enhanced relative to the multiple reflections and random noise. The criterion used in optimum horizontal stacking is to maximize the signal to noise power ratio, where signal refers to the primary reflection sequence and noise includes the multiple reflections. It is shown when this criterion is equivalent to minimizing the mean square difference between the desired signal (primary reflection sequence) and the weighted horizontally stacked traces. If the seismic traces are combined by multichannel linear filtering, the primary reflection sequence will have undergone some phase and frequency distortion on the resulting record. The signal to noise power ratio then becomes less meaningful a criterion for designing the optimum linear multichannel filter, and the mean square criterion is adopted. In general, however, since more a priori information about the seismic traces is required to design the optimum linear multichannel filter than required for the optimum set of weights of the horizontal stacking process, the former will be an improvement over the latter. It becomes evident that optimum horizontal stacking is a restricted form of linear multichannel filtering.     

Common-reflection-surface stack — a real data example

The simulation of a zero-offset (ZO) stack section from multi-coverage reflection data is a standard imaging method in seismic processing. It significantly reduces the amount of data and increases the signal-to-noise ratio due to constructive interference of correlated events. Conventional imaging methods, e.g., normal moveout (NMO)/dip moveout (DMO)/stack or pre-stack migration, require a sufficiently accurate macro-velocity model to yield appropriate results, whereas the recently introduced common-reflection-surface stack does not depend on a macro-velocity model. For two-dimensional seismic acquisition, its stacking operator depends on three wavefield attributes and approximates the kinematic multi-coverage reflection response of curved interfaces in laterally inhomogeneous media. The common-reflection-surface stack moveout formula defines a stacking surface for each particular sample in the ZO section to be simulated. The stacking surfaces that fit best to actual events in the multi-coverage data set are determined by means of coherency analysis. In this way, we obtain a coherency section and a section of each of the three wavefield attributes defining the stacking operator. These wavefield attributes characterize the curved interfaces and, thus, can be used for a subsequent inversion. In this paper, we focus on an application to a real land data set acquired over a salt dome. We propose three separate one-parametric search and coherency analyses to determine initial common-reflection-surface stack parameters. Optionally, a subsequent optimization algorithm can be performed to refine these initial parameters. The simulated ZO section obtained by the common-reflection-surface stack is compared to the result of a conventional NMO/DMO/stack processing sequence. We observe an increased signal-to-noise ratio and an improved continuity along the events for our proposed method — without loss of lateral resolution.     

用调制解调技术降低地震数据采集器的漂移

地震数据采集是数字化地震观测的重要环节, 因为模拟数字转换器(A/D)是地震数据采集器的重要部件, A/D的技术水准在很大程度上决定了数据观测质量。 放大器及A/D的漂移和 1/f噪声是数据采集器漂移的主要来源, 对以低频信号观测为主要特征的地震观测有较大影响。 为降低其影响, 本文在算法上对此问题做了一些探讨, 在目前autozero技术上做出一些改进, 即用调制解调技术来降低1/f噪声对信号精度的影响, 并做了相应的算法模拟。 在此基础上, 对算法做了进一步改进, 利用高次谐波加权求和使输出信噪比得到一定程度的提高。 结果表明, 通过优化解调算法, 可以进一步提高信噪比约2 dB, 对试验电路获得的测试数据应用优化解调算法也证实了这一点。     

香港GPS基准站坐标序列特征分析

利用香港GPS连续运行参考站网络2001年1月至2007年8月的观测资料,全面深入地分析了12个基准站坐标序列特征.本文采用主成分空间滤波算法去除公共误差,来提高坐标序列的信噪比,并采用最大似然估计准则定量估计滤波后坐标序列的噪声特性,计算了地球表面质量负荷（包括大气、非潮汐海洋、积雪和土壤水）对香港GPS基准站坐标序列的影响.研究结果表明：香港GPS基准站坐标序列具有高度的空间相关性,其公共误差具有较强的季节性变化特征;地表质量负荷变化引起的香港地壳形变可以解释公共误差序列中约为3mm的垂向周年变化,经过质量负荷改正后的公共误差序列与高阶电离层误差高度相关;滤波后坐标序列的噪声特性可以用可变白噪声加闪烁噪声模型来描述,顾及闪烁噪声所计算的速度误差要比只考虑可变白噪声计算的速度误差大2~6倍;基准站间存在达1.5 mm/yr的相对水平运动,揭示香港地区存在活动断层;部分基准站坐标具有明显的振幅为1～2 mm本地季节性变化,所有测站的残差序列也表现出强烈的季节性变化.     

基于压缩感知重构算法的大地电磁强干扰分离

为压制大地电磁信号中的强人文干扰,提出一种基于压缩感知重构算法的大地电磁信号去噪方法.通过构建与常见典型强干扰相匹配而对有用信号不敏感的冗余字典原子,利用改进的正交匹配追踪算法,分离出大地电磁信号中的强干扰成分.为了验证所述方法的强干扰分离效果,首先通过在实测大地电磁信号中加入理想的强干扰信号进行了仿真分离实验,然后从大量实测数据中选取三种含有不同类型强干扰的时间域片段,用所述方法对实测数据中的强干扰进行分离,最后将所述方法应用于青海试验点以及庐枞矿集区某测点实测数据的综合处理.仿真实验结果表明,该方法在分离出强干扰的同时,能够较好地保留有用信号.实测数据处理结果表明,该方法能够有效压制强干扰,改善强干扰区大地电磁数据的质量.     

A Study of the Adaptive Method for Decoupling Overlapping Seismic Records

Signal extraction from overlapping seismic records is a common problem in geophysical data analysis. Identification and separation of multiple seismic arrivals, analysis of large earthquakes as multiple point sources, and calculation of the true yield of a large nuclear explosion from interfering small explosion, all hinge on our ability to effectively decouple two interfering wave signals. This paper presents a method for signal separation based on an adaptive filtering technique. We apply a semi-deconvolution algorithm to overlapping explosion records and S/SKS phase groups, and then perform noise reduction and signal decoupling under different a priori conditions and assess the stabilities using a variance reduction approach. We demonstrate, through numerical experiments and analysis of seismic station records, that the adaptive method can be both robust and practical for regional and teleseismic applications.     

HORIZONTAL STACKING AND MULTICHANNEL FILTERING APPLIED TO COMMON DEPTH POINT SEISMIC DATA*

The common depth point method of shooting in oil exploration provides a series of seismic traces which yield information about the substrata layers at one location. After normal moveout and static corrections have been applied, the traces are combined by horizontal stacking, or linear multichannel filtering, into a single record in which the primary reflections have been enhanced relative to the multiple reflections and random noise. The criterion used in optimum horizontal stacking is to maximize the signal to noise power ratio, where signal refers to the primary reflection sequence and noise includes the multiple reflections. It is shown when this criterion is equivalent to minimizing the mean square difference between the desired signal (primary reflection sequence) and the weighted horizontally stacked traces. If the seismic traces are combined by multichannel linear filtering, the primary reflection sequence will have undergone some phase and frequency distortion on the resulting record. The signal to noise power ratio then becomes less meaningful a criterion for designing the optimum linear multichannel filter, and the mean square criterion is adopted. In general, however, since more a priori information about the seismic traces is required to design the optimum linear multichannel filter than required for the optimum set of weights of the horizontal stacking process, the former will be an improvement over the latter. It becomes evident that optimum horizontal stacking is a restricted form of linear multichannel filtering.     

Stacked

Analysis of prestack P-wave seismic data yields information about both the P- and S wave properties of the earth. An anticipated advantage of having two measurements (P and S) is that they can be combined into a new measurement that is less sensitive to lithology variations and more sensitive to fluid effects. The amplitude-variation-with-offset (AVO) gradient is one such measure that is often used qualitatively as a fluid indicator. The gradient always becomes softer (more negative) when hydrocarbon replaces brine in the pore spaces but the overall AVO response is dominated by the lithology. Fluid effects are expressed primarily by the normal-incidence P-wave response and only secondarily by the offset dependence. The gradient often does not function as an effective fluid indicator. This is partially due to the fact that the gradient is roughly twice as sensitive to S- than to P-wave properties. More importantly, effective random noise in the CMP gathers introduces a strong correlation between the AVO intercept and gradient and, hence, between the measured P- and S-wave properties. This correlation in the AVO attributes corresponds to a significant error in the estimation of the S-wave properties and can dominate the measurements from many of the popular AVO techniques. A simple method to minimize the effect of this noise-induced correlation is to stack the data. The stack corresponds to a coordinate rotation in elastic space with the stack amplitudes measured along one of the new axes and the other (unmeasured) axis naturally tending to line up with the noise and thus suppressing it. Fluid effects cause the data to move roughly perpendicular to this noise trend. The stack axis is then in the direction of the fluid effect. The stack thus combines both the P- and S-wave (normal and oblique incidence) information into a single measurement which can be made to optimally suppress background noise and highlight fluid effects. A major consequence of this interpretation is the simplicity of both prospect identification and quantitative amplitude analysis.     

在随机噪音背景下地震反射信号的增强

提高地震资料的信噪比，增强反射波同相轴连续性是地震勘探的基本问题之一。本文针对因存在噪音和信号比较弱，致使正常时差（NMO）校正加方法难以奏效的问题，提出提高信噪比和增强反射信号同相轴连续性的共反射面元（CRS）迭加方法，该方法将来自菲涅尔带的信息经校正迭加在一起，计算结果表明，该方法能有效提高信噪比，增强反射信号同相同的连续性。