用优化聚束滤波方法消除低信噪比地震资料中的多次波

针对常规方法如f k,Radon变换不能很好解决的消除低信噪比地震勘探资料的多次波问题,本文提出了优化聚束滤波方法,采用具有静态权的自适应聚束滤波器,并调整聚束滤波器设计的约束准则,去除低信噪比复杂实际资料中的多次波．实际资料处理结果表明,优化聚束滤波方法改善了最小方差无偏聚束滤波方法不能较好地处理低覆盖低信噪资料处理的局限性,在实际处理中计算量增加不大．     

用广义消除旁瓣聚束滤波方法消除三维地震资料中的相关噪音

本文提出了一个新的方法以消除三维地震资料中的相关噪音。广义消除旁瓣聚束滤波方法(GSC)作为自适应线性约束聚束滤波方法(LCMV)的一个广义形式,包括一个固定的自适应聚束滤波器和一个在无约束聚束滤波器前的控制矩阵。考虑到三维观测系统的复杂性、在三维聚束滤波方法设计中有两个关键点:(1)采用将地震资料按方位角分区,把三维时距关系简化为二维;(2)引入动态平衡面元,避免有的方位角分区内地震道数可能不够。合成资料和实际资料结果表明,新研究的广义消除旁瓣聚束滤波方法能够得到高效、稳定和高分辨率的解。     

P-SV反射转换波的倾角时差校正（DMO）方法研究

倾角时差校正（ＤＭＯ）方法对于复杂地质构造条件下的纵波反射波（Ｐ－Ｐ）的多次覆盖地震数据的叠加具有显著的提高信噪比的效果．对于转换反射波（Ｐ－ＳＶ）来说，进行倾角时差校正（ＤＭＯ）处理就更需要．本文首先对Ｐ－ＳＶ波的倾角时差校正（ＤＭＯ）的几何原理进行了分析，然后重点研究用波动方程进行ＤＭＯ的方法，即Ｐ－ＳＶ转换反射波的叠前部分偏移的波动方程法．这种方法也适用于Ｐ－Ｐ反射波的叠前部分偏移处理．研究结果表明，波动方程ＤＭＯ方法在振幅保真方面比几何原理的ＤＭＯ方法有显著改善．     

P－SV转换波的一种处理方法─叠前抽道集法

本文利用纵波和横波的迭加速度资料来计算Ｐ－ＳＶ波勘探中转换点的近似位置。再按转换点对Ｐ－ＳＶ波重新抽道集，得到可与反射资料ＣＭＰ道集相兼容的时间剖面图。利用理论模型对上述方法进行了可靠性检验，并用该方法对实际资料作了处理。同时还得到了实际资料的Ｐ波和Ｐ－ＳＶ波的彩色振幅比剖面图。结果表明：采用改进的叠前抽道集法所得到的剖面图具有很好的空间分辨率。     

基于匹配滤波的多次波压制方法研究

常规滤波方法对浅海多次波压制不能取得理想效果.通过改变模型表面边界条件,求解波动方程实现多情景地震数值模拟.利用自由边界条件模拟时获得含海平面强反射多次波地震记录,而利用吸收边界条件时得到理想条件下无多次波地震记录.对比分析多次波对有效地震信号的影响得到海平面强反射多次波改变了有效地震信号的振幅、频率和相位.利用归一化方法计算得到压制多次波滤波器算子,并作用于含海平面强反射多次波地震记录.叠加地震剖面对比分析表明,归一化滤波器算子较好的压制了地震记录中的多次波,提高地震资料分辨率.最后,根据多次波产生条件,给出了利用实际区域简化地质模型的地震数值模拟结果计算归一化滤波器算子的方法,从而利用该方法压制实际地震数据中多次波.     

P—SV转换波的一种处理方法—叠前抽道集法

本文利用纵波和横波的迭加速度资料来计算Ｐ－ＳＶ波勘探中转换点的近似位置。再按转换点对Ｐ－ＳＶ波重新抽道集，得到可与反射资料ＣＭＰ道集相兼容的时间剖面图。利用理论模型对上述方法进行了可靠性检验，并用该方法对实际资料作了处理。同时还得到了实际资料的Ｐ波和Ｐ－ＳＶ波的彩色振幅比剖面图。结果表明：采用改进的叠前抽道集法所得到的剖面图具有很好的空间分辨率。     

台站地震资料的时频域自适应极化分析和滤波

提出一种自适应协方差的时频域极化滤波方法。该方法在广义S变换时频方法的基础上,构造时频域自适应协方差矩阵,通过特征分析计算时频域瞬时极化参数,设计极化滤波器,实现多分量地震极化分析和滤波。其优势在于协方差矩阵的分析时窗的长度由多分量地震数据的瞬时频率确定,可以自适应于有效信号的周期,在每个时频点计算极化参数不需要进行插值处理;结合时间频率信息,解决在时间域或频率域波形或频率重叠的信号具有明显的直观性。模型数据及实际三分量台站地震数据处理结果表明,该极化滤波方法在台站地震资料分析和处理方面具有很好的直观性和较高的分辨率。     

二维地震资料波动方程非线性反演

针对反演的要求和实际问题的需要，提出利用地震资料叠前数据进行二维波动方程反演，采用最小平方拟合修正模型参数的非线性反演方法，构造了问题的加速迭代算法．反演算法充分利用了冗余的叠前数据和多道相关性，可以分离噪声和信号，使噪声不参与或很少参与反演，算法抗噪能力强．数值模拟例子表明算法有效和稳定，得到了令人满意的结果．     

基于结构自适应中值滤波器的随机噪声衰减方法

本文提出一种保护断层、裂缝等地层边缘特征的结构自适应中值滤波器,用于衰减地震资料中的随机噪声.基于地震反射同相轴局部呈线型结构的假设,采用梯度结构张量估计地层倾向,分析地层结构的规则程度,在此基础上引入地震剖面中线型和横向不连续性两种结构特征的置信度量.结构自适应中值滤波器根据这两种置信度量调整滤波器窗函数的尺度和形状,根据地层倾角调整滤波器窗函数的方向,从而使得滤波操作窗能够最佳匹配信号的局部结构特征.将本文方法用于合成和实际数据的处理,并与两种常用中值滤波方法进行对比,结果表明,该方法能够更好地解决地震剖面的随机噪声衰减和有效信号保真的问题,在增强反射同相轴的横向一致性的同时有效保持了剖面内的地层边缘和细节特征,显著改善了地震资料的品质.     

地震资料去噪方法技术综合评述

地震资料去噪,无论是叠前还是叠后,都是处理中非常重要的内容.随着勘探技术的进步,地球物理界积累和开发的去噪软件已越来越多.对各种去噪方法进行分门别类,阐述其基本原理、物理意义、适用条件、发展前景,既有理论价值又有实际指导意义.本文从噪声的特征出发,首先对地震资料噪声进行了分类;然后综合评述了目前实际生产中常用的几种去噪方法,包括频率域滤波、频率波数域滤波、频率空间域滤波、Radon变换、聚束滤波、基于小波分解和重建的去噪方法等;最后还简述了去噪技术的应用及发展情况.     

Robust multiple suppression using adaptive beamforming

Minimum variance unbiased (MVU) beamforming is a type of multichannel filtering which extracts coherent signals without distortion, whilst minimizing residual noise power. Adaptive beamforming estimates signal and noise characteristics as part of the extraction process. The adaptive beamformer used here is designed from models of primary and multiple reflection signals having parametrically specified moveout and amplitude variation with offset (MVO and AVO). Phase variation with offset (PVO) can also be included but it is not usually justified in practice. The resulting analysis provides data for input into AVO and PVO schemes for obtaining lithological information. Synthetic data examples illustrate details of implementation of parametric adaptive MVU beamforming and the response characteristics of the resultant design. Real data examples show that data-adaptive beamforming is more flexible and more effective in attenuating multiples in prestack common-midpoint seismic data than Radon transform methods. In common with other prestack multichannel processes, the advantages of beamforming are shown to best effect in data with a good signal-to-noise ratio.     

地震资料去噪方法、技术综合评述

地震资料去噪，无论是叠前还是叠后，都是处理中非常重要的内容.随着勘探技术的进步，地球物理界积累和开发的去噪软件已越来越多.对各种去噪方法进行分门别类，阐述其基本原理、物理意义、适用条件、发展前景，既有理论价值又有实际指导意义.本文从噪声的特征出发，首先对地震资料噪声进行了分类；然后综合评述了目前实际生产中常用的几种去噪方法，包括频率域滤波、频率波数域滤波、频率空间域滤波、Radon变换、聚束滤波、基于小波分解和重建的去噪方法等；最后还简述了去噪技术的应用及发展情况.     

叠前时间偏移技术在淮北某煤矿采区三维地震勘探中的应用与效果

淮北某煤矿采区三维地震勘探地质条件极为复杂,区内褶皱、断层构造发育,常规叠后时间偏移处理很难准确成像,给后期资料解释工作带来不利影响.针对这一问题,采用叠前时间偏移技术,结合煤田地震勘探特点,对影响叠前偏移处理质量的关键步骤（预处理、静校正、叠前去噪、时间域速度模型建立）进行了研究,取得了显著效果.利用叠前偏移数据体解释,最终圆满完成了地质任务.本文通过应用实例,说明了煤田地震勘探资料处理利用叠前时间偏移技术对复杂构造成像效果较好,信噪比提高,断点解释更可靠.     

Cross-correlation beamforming

An areal distribution of sensors can be used for estimating the direction of incoming waves through beamforming. Beamforming may be implemented as a phase-shifting and stacking of data recorded on the different sensors (i.e., conventional beamforming). Alternatively, beamforming can be applied to cross-correlations between the waveforms on the different sensors. We derive a kernel for beamforming cross-correlated data and call it cross-correlation beamforming (CCBF). We point out that CCBF has slightly better resolution and aliasing characteristics than conventional beamforming. When auto-correlations are added to CCBF, the array response functions are the same as for conventional beamforming. We show numerically that CCBF is more resilient to non-coherent noise. Furthermore, we illustrate that with CCBF individual receiver-pairs can be removed to improve mapping to the slowness domain. An additional flexibility of CCBF is that cross-correlations can be time-windowed prior to beamforming, e.g., to remove the directionality of a scattered wavefield. The observations on synthetic data are confirmed with field data from the SPITS array (Svalbard). Both when beamforming an earthquake arrival and when beamforming ambient noise, CCBF focuses more of the energy to a central beam. Overall, the main advantage of CCBF is noise suppression and its flexibility to remove station pairs that deteriorate the signal-related beampower.     

Testing the ability of surface arrays to monitor microseismic activity

Recently there has been much interest in the use of data from surface arrays in conjunction with migration‐based processing methods for passive seismic monitoring. In this study we use an example of this kind of data recorded whilst 18 perforation shots, with a variety of positions and propellant amounts, were detonated in the subsurface. As the perforation shots provide signals with known source positions and origin times, the analysis of these data is an invaluable opportunity to test the accuracy and ability of surface arrays to detect and locate seismic sources in the subsurface. In all but one case the signals from the perforation shots are not visible in the raw or preprocessed data. However, clear source images are produced for 12 of the perforation shots showing that arrays of surface sensors are capable of imaging microseismic events, even when the signals are not visible in individual traces. We find that point source locations are within typically 45 m (laterally) of the true shot location, however the depths are less well constrained (～150 m). We test the sensitivity of our imaging method to the signal‐to‐noise ratio in the data using signals embedded in realistic noise. We find that the position of the imaged shot location is quite insensitive to the level of added noise, the primary effect of increased noise being to defocus the source image. Given the migration approach, the array geometry and the nature of coherent noise during the experiment, signals embedded in noise with ratios ≥0.1 can be used to successfully image events. Furthermore, comparison of results from data and synthetic signals embedded in noise shows that, in this case, prestack corrections of traveltimes to account for near‐surface structure will not enhance event detectability. Although, the perforation shots have a largely isotropic radiation pattern the results presented here show the potential for the use of surface sensors in microseismic monitoring as a viable alternative to classical downhole methods.     

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。