均衡多道1范数匹配多次波衰减的方法与应用研究

反馈迭代法多次波衰减分为预测和相减两个步骤.在匹配相减过程中,当多次波和一次波同相轴不满足正交性,以及去除多次波后的地震记录不满足能量最小的情况下,最小二乘自适应匹配滤波方法不能获得正确的匹配,因此多次波的衰减产生误差.针对这两个问题,本文提出了基于1范数最小的均衡多道自适应匹配滤波法.该方法通过在空间方向上对地震记录进行均衡,避免了多次波和一次波同相轴正交的假设条件.同时利用了1范数对于大异常值保持稳健的特点,因此可以有效地解决去除多次波后的地震记录能量最小的问题.通过对模型数据和野外实际数据的多次波压制结果显示,该方法可以有效、准确地衰减多次波.     

改进的1范数匹配滤波法及在南海深水盆地的应用

地震勘探中多次波的存在会影响速度模型的建立、地震成像效果、反演和解释过程中的介质属性提取等,因此多次波的压制成为至关重要的研究课题.本文采用改进的1范数匹配滤波法,基于1范数对大值条件的开放性,利用预测出的多次波模型Hilbert变换道及求导道,从理论上克服2范数的大值条件,并改善常规1范数下的正交性条件,在一次波和多次波叠合之处及能量差异大的情况下有效压制多次波.模型及南海深水盆地实际海洋地震数据的处理结果显示了改进的1范数匹配方法在压制多次波方面相对于常规2范数、1范数的优越性.     

基于非二次幂Curvelet变换的最小二乘匹配算法及其应用

本文提出了基于非二次幂Curvelet变换的最小二乘匹配算法.首先,根据输入地震信号的频谱和方向等特征进行非二次幂Curvelet变换,根据其特征不同,最大程度地将有效信号和噪声分开;然后,在噪声能量集中的非二次幂Curvelet子记录上对输入数据和预测的噪声模型进行最小二乘匹配滤波处理.本方法提高了常规最小二乘匹配算法在时间空间域内进行信噪分离的稳定性和准确性.对含有面波的实际地震数据进行测试,其结果表明本方法可以有效地压制面波干扰,特别是当面波和有效信号有交叉或重叠等现象出现时,能较好地保护反射同相轴信息.本方法还可用于对含自由表面多次波和层间多次波等地震数据进行自适应信噪分离.     

基于均衡伪多道匹配滤波的海底电缆多次波压制方法研究（英文）

由于自由表面、海底等强反射界面的影响,海底电缆采集资料中鸣震等干扰往往非常严重且与有效波耦合在一起,降低了资料品质。海底电缆双检合成技术利用速度检波器和压电检波器对于下行波场的不同极性响应可以有效压制检波点端多次波,突出有效反射,提高地震资料的分辨率。本文在深入研究双检合成理论及匹配滤波技术的基础上,提出了基于均衡伪多道自适应匹配滤波方法的双检匹配合成方法压制检波点端多次波,不依赖于传统的求取反射系数的匹配合成方法,完全数据驱动,并在合成记录和实际资料的处理过程中均取得了良好的效果,证明了方法的有效性。     

基于多道卷积信号盲分离的多次波自适应相减方法

本文将多次波自适应相减问题表示为一个多道卷积信号的盲分离问题.利用2D卷积核来表示预测多次波和实际多次波之间的差异,并采用分离出的一次波信号的非高斯性最大化作为优化目标,我们提出一种基于多道卷积信号盲分离的多次波自适应相减算法.为了求解上述非线性优化问题,所提方法将其转化为一个迭代线性优化问题,采用迭代最小二乘方法加以实现.由于采用了多道卷积信号盲分离模型,所提方法能够适应预测和真实多次波之间在时间及空间上的变化.通过对简单模型数据、Pluto数据和实际数据进行处理,验证了所提算法的有效性.     

基于非因果滤波器的多次波匹配相减方法(英文)

在常规多道匹配滤波方法中的滤波器是物理可实现的因果滤波器,只能实现地震信号序列延迟的滤波。本文提出了最小二乘意义下的非因果多道输入多道输出维纳滤波方法,通过比较多道匹配相减中因果和非因果滤波方法之间的差别,验证了方法的有效性,解决了模型数据滞后于实际数据的情况。而且,通过定义长度随偏移距和层速度变化的滑动时窗,解决了匹配时窗内同相轴数量随偏移距增大而增加的问题。并将上述方法应用到改进的扩展多道匹配相减去除多次波的方法中,利用Pluto1.5理论模拟数据,对非因果滤波器和变长度时窗的匹配相减方法进行测试,取得了很好的去除多次波后的地震数据。     

基于表层多次波数据的近道地震数据插值方法研究(英文)

本文提出基于原始含表层多次波数据实现叠前共炮集地震数据插值。相对于利用相邻道的信息变换或外推插值用于缺失的地震数据重建,本文方法利用表层多次波数据互相关构建准一次波,将蕴含在表层多次波数据中的,而在采集记录中表现为缺失的近炮检距信息提取出来,并在滑动时间空间窗内采用最小二乘匹配滤波和均方根振幅校正方法进行准一次波校正而后用于数据插值重建。本文方法适用于表层多次波比较发育,同时又存在数据缺失尤其是近炮检距数据缺失情况。方法易于实现,不需多次波和一次波的提取,利用多次波中蕴含的信息实现缺失的地震数据弥补,为含有表层多次波的数据进行近炮检距地震信息的插值重建提供了一个很好的思路。     

多道自适应匹配滤波方法压制表面多次波

表面多次波压制是海洋地震数据处理的关键环节,基于波动方程的多次波压制方法可由多次波模型预测和自适应相减两步实现.因此,除了采用有效的算法实现高精度的多次波预测外,多次波的自适应相减也是改善多次波压制效果的重要手段.文中采用多道自适应滤波器完成表面多次波的自适应相减,利用数据驱动的基于波动方程预测多次波模型的高频重建道、Hilbert变换道、以及它们相应的上下延拓道改善预测多次波模型的振幅、相位、旅行时以及频带信息,使得修正后多次波模型与实际地震数据中的多次波更好地匹配.实际数据测试表明,文中所述方法可有效地完成表面多次波的自适应相减.通过讨论分析交叠时窗和滤波器的长度对自适应相减效果的影响,表明合理地利用时窗以及选择滤波器长度将有效地改善自适应相减的效果.     

用多道反褶积方法测定台站接收函数

本文提出了一种在时间域用多道反褶积测定台站接收函数的方法, 以提高台站接收函数的测量精度与分辨率.在单道反褶积的基础上，选取若干个质量较好的远震P波波形事件，构成多道信号，以垂直分量为输入，径向和切向分量作为期望输出，依据最小二乘，设计多道滤波器，提取接收函数.合成地震图与观测地震图的检验表明, 多道滤波方法能有效地测定台站接收函数，特别是多道反褶积能够有效地恢复地壳上地幔间断面所产生的弱转换波震相.     

衰减干涉假象的海洋一次波与多次波同时成像方法

海水与空气间的强波阻抗差使得海洋地震资料普遍发育自由表面相关多次波,如何利用好多次波所携带的有效信息已成为提高海洋地震资料成像品质的新突破点.基于面炮偏移的一次波与多次波同时成像方法能够避免多次波预测精度的影响,但是,正向传播的震源子波与反向延拓的自由表面相关多次波所产生的干涉假象严重制约了该技术的应用,本文提出了一种基于单程波偏移算子,可在成像域压制干涉假象的一次波与多次波同时成像方法.其中包含了三个步骤:第一,传统单程波偏移成像方法中的震源子波替换为一次波、多次波与震源子波,初始上行延拓波场为一次波与多次波,基于单程波算子的波场延拓与互相关成像条件的应用得到包含干涉假象的一次波与多次波同时成像;第二,以子波为震源,自由表面相关多次波为记录,按照传统单程波偏移成像方法得到干涉假象;第三,基于最小二乘匹配滤波算法,将第一步的成像结果与第二步的干涉假象进行匹配相减,得到干涉假象衰减后的一次波与多次波同时成像,避开了由于实际资料子波无法准确提取而造成一次波与多次波对成像能量级的不一致性.Sigsbee2B模型测试验证了本方法的有效性,并在我国某探区深海实际资料处理中得到了成功应用,深层基底得到了清晰刻画,并且照明均衡度明显改善.     

基于奇异值分解的时移地震互均衡方法

针对时移地震互均衡处理中的传统匹配滤波算法抗噪能力弱的特点,重新推导匹配滤波方程,引入奇异值分解方法求解,克服系数矩阵的奇异性,同时减少噪声的影响.模拟数据和实际数据都验证了基于奇异值分解匹配滤波较传统匹配滤波算法有更好的抗噪能力.     

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.     

A new stacking technique in ambient noise tomography

We have developed a new stacking technique in ambient noise tomography to obtain high-quality dispersion curves of Rayleigh waves.This technique is used to stack the vertical components of the Estimated Green Functions(EGFs) obtained respectively from cross correlation of the ambient noise data recorded by a remote seismic station and one of the short distance seismic stations of a seismic array.It is based on a phase-matched filter and is implemented by a four-step iterative process:signal compression,stacking,signal extraction and signal decompression.The iterative process ends and gives the dispersion curve of Rayleigh wave when the predicted one and the processing result converge.We have tested the method using the vertical components of synthetic Rayleigh wave records.Results show that this new stacking method is stable and it can improve the quality of dispersion curves.In addition,we have applied this method to real data.We see that the results given by our new technique are obviously better than the ones employing the traditional method which is a three-step process:signal compression,signal extraction and signal decompression.In conclusion,the new method proposed in this paper can improve the signal to noise ratio of EGFs,and can therefore potentially improve the resolution of ambient noise tomography.     

MAXIMUM LIKELIHOOD ESTIMATION OF SEISMIC REFLECTION COEFFICIENTS*

A seismic trace is modeled as a moving average (MA) process both in signal and noise: a signal wavelet convolved with a reflection coefficient series plus colored random noise. Seismic reflection coefficients can be estimated from seismic traces using suitable estimation algorithms if the input wavelet is known and vice versa. The maximum likelihood (ML) algorithm is used to estimate the system order and the reflection coefficients. The system order is related to the arrival time of the latest signal in a complex seismic reflection event. The least-squares (LS) method does not provide such information. The ML algorithm makes assumptions only about the Gaussian nature of the noise. It is better suited for seismic applications since the LS method inherits the white noise assumption. The Gauss-Newton (G-N) and Newton-Raphson (N-R) optimization algorithms are used to obtain the ML and the LS estimates. Reflection coefficient estimations are affected by the choice of sampling rate of seismic data. Theoretically, the optimum choice in system identification is the Nyquist rate. Experience with synthetic data confirms the theory. In practice, good estimates of reflection coefficients are possible only up to certain pulse separations (or, equivalently, orders). This is mostly due to numerical problems with the optimization algorithms used and partly due to the limited bandwidth of seismic signals. Good estimates from data simulated using three airgun array pulses recorded with 6–128 Hz filter setting are possible up to about 40.0 ms pulse separations. Successful estimations from pinchout and thin layer simulations and well controlled offshore “bright-spots” are given.     

基于单程波偏移算子的地表相关多次波成像

在常规地震资料处理中,多次反射波被视为噪声并从地震数据中去除,以免在之后的地震资料解释中造成误解.而事实上,多次波也是地震信号,是照明波场的一部分,能够对地下构造成像的精度做出贡献.本文分析了多次波在传统单程波叠前深度偏移中产生构造假象的机制和表现,为实现基于单程波偏移算子的多次波成像,修改了单程波叠前深度偏移的边界条件,即将输入的震源波场用包含多次波的记录来替代,输入的记录波场用预测出的表层相关多次波来替代,实现了基于单程波偏移算子的地表相关多次波成像,并从理论上给出了其成像依据.通过基于二范式最小能量差原则求取的匹配因子,将多次波成像结果与一次波成像结果进行匹配叠加,应用多次波成像来弥补一次波成像的不足.简单模型验证了基于单程波偏移算子的多次波成像方法的有效性,最后对Sigsbee2B模型进行了一次波与多次波联合成像试算,盐边界高陡构造成像质量得到了明显改善.     

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。     

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.     

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.