微屈多次波正演模拟及其在中原油田深层地震资料解释中的应用

对微屈多次波的压制或利用是地震资料处理、解释中的一个难题。正演模拟是压制或利用微屈多次波的基础。笔者利用层状介质非线性模型理论,发展了一种正演模拟微屈多次波的方法。利用这一方法在中原油田深层地震资料解释中作了初步应用,取得了一些有用的成果。该方法也可以在地震子波分析处理和提高地震资料分辨率中发挥作用。     

陆上地震数据多次波压制策略

在陆上地震勘探中,多次波反射与其他干扰波一样,干扰了有效波反射信号并降低了资料的信噪比。根据陆上地震数据中多次波与一次波所表现的不同特点,提出利用动校正叠加技术和频率-波数(f-k)滤波方法相结合的策略以压制地震数据中的多次波。使用一次波速度的动校正叠加技术可以衰减地震数据中的一部分多次波能量;根据叠加剖面确定包含剩余多次波的CMP范围,将f-k滤波方法应用于这些CMP道集上进一步压制多次波。模型试算和实际数据处理结果表明,所提出的多次波压制策略,不仅能有效地衰减多次波能量,而且在处理过程中可以减少对有效波信号的伤害。     

海上某区二维地震多次波的识别和压制

多次波的识别和压制是陆上,特别是海洋地震勘探中需要解决的突出问题之一。首先结合某区二维深海地质资料,采用变偏移距叠加剖面、叠加速度谱、自相关分析和二维频率波数域等方法手段,对波场的特征、多次波的类型和性质进行了识别分析。然后,对于不同类型的多次波匹配地选择预测反褶积、频率波数域滤波和加权混波等方法加以压制。发挥各自方法的优点,实现了多种方法的整体综合优化,达到最大限度地压制多种类型多次波的目的。较好的实际压制效果表明上述工作思路和处理方法是有效可行的。     

地震资料数据处理中消除多次波的一种有效方法

在煤田地震勘探中经常由于多次波的干扰而影响其效果。如能在迭前设法消除这些多次波,将会提高时间剖面质量。这里介绍GSI公司TIPEX地震应用软件中的一种处理程序——DEWATER2。它对压制长周期简单的和微屈界面产生的多次波效果很好。在予处理中,对共深度点域未叠加的资料用DEWATER2程序处理,以达到压制多次波干扰,突出有效波的目的。为此,输入文件必须是CDP域的ATD文件,即:经过初步整理的CDP     

逆数据域表面多次波压制方法

基于波动方程压制表面多次波的反馈迭代方法,推导出压制表面多次波的逆数据域方法。该方法利用了一次波和表面多次波在逆数据域的可分离性质。含表面多次波的地震数据变换到逆数据域后,表面多次波的能量在逆数据域形成能量聚焦区域,可通过简单切除能量聚焦区域的信号实现表面多次波压制,避免了基于波动方程预测减去方法中的自适应相减过程,完全损伤不到一次波的能量。单道地震记录和合成炮数据模型试算表明：逆数据域多次被压制方法简单易行,可有效压制表面多次波,并保持一次波振幅不受损失。与常规的基于波动方程的表面多次被压制方法（SRME方法）对比表明,逆数据域方法能更好地应对有效波和多次波同相轴相交的情况。     

952南区多道地震多次波压制方法

多次波的压制是震资料处理中的难点和重点。特别是海上地震资料记录时间长,多次波发育。本文针对南沙海域地震地质条件。提出二维皮方法及其辅助办法,详细了二维Ｆ－Ｋ滤波的原理及演变过程,并通过对南沙海的实际资料自理得出了满意的结果。     

F-K变换与预测反褶积压制多次波效果对比

多次波压制是地震资料处理中一个重要步骤。根据多次波发生下行反射的位置,可以把多次波分为两类:自由界面多次波和层间多次波。不同的多次波有着不同特性,一种压制多次波的方法往往只能针对特定的某一种多次波进行压制。F-K域压制多次波和预测反褶积分别利用了多次波的可分性和周期性这两种具有代表性压制多次波的处理方法。这里首先利用声波时差有限差分的方法对模型进行了正演计算,得到了包含不同类型多次波的地震数据;然后对正演数据分别应用F-K域压制多次波和预测反褶积两种压制多次波技术对自由界面多次波和层间多次波进行处理;最后对比分析了两种方法的处理效果,总结了两种方法的适用条件。F-K域多次波压制手段适用于多次波与一次波时差差异较大的情况,预测反褶积对小炮检距附近严格满足周期性的多次波去除效果较好。     

基于地震信号相似性的S变换域多次波压制技术

多次波压制是海洋地震数据处理的关键,如何保护一次反射波的同时高效准确地识别并压制多次波是地震资料处理的重点。笔者在共中心点(CMP)叠加压制多次波方法的基础上,基于CMP道集地震信号与叠加道地震信号的相似性特征在S变换域进行多次波压制。首先,利用多次波速度动校正并对CMP道集数据减去叠加道数据完成第一次多次波减除,此时,波场中残余的多次波以随机噪声的形式存在;然后,对减除多次波的地震波场应用一次波速度动校正,并以一次波速度叠加道为初始模型对CMP道集S变换谱进行相似性滤波完成第二次残余多次波去除。针对理论数据和实际数据进行了有效性测试,结果表明本文所提方法能够较好地压制多次波,提高反射波的成像精度。     

各向异性 Ｒadon 变换在深水地震多次波压制中的应用

在深海多缆、长拖缆地震勘探的各种噪音影响中,多次波对深层的有效反射影响难以消除。笔者介绍了一种高分辨率各向异性 Ｒadon 变换方法,在 Ｒadon 变换积分路径中增加非椭圆率 eta 参数,将传统 Ｒadon 变换积分曲线由慢度、偏移距两参数改为慢度、偏移距及非椭圆率三参数,更好地刻画了长偏移距下反射非双曲时差。通过对某海域实际采集的多缆长偏移距地震数据进行压制多次波处理,与传统方法相比取得了较为理想的效果,为后续深层构造成像提供了基础数据。     

三维自由表面多次波去除方法

多次波去除是地震数据处理与解释中的关键性问题,其去除结果直接影响地震数据的处理质量。笔者论述的自由表面多次波压制（SRME）是一种数据驱动理念,在不需任何地下信息和假设的情况下,利用地震数据的自身迭代就可以达到预测多次波的目的,并且相较于一些传统方法预测更加准确。面对越来越多的三维海洋地震采集,二维SRME方法暴露出其算法对三维构造的估计不足,所以有必要将SRME从二维向三维扩展。三维SRME相较于传统的二维SRME在考虑多次波贡献方面表现得更加全面,有效地计算地下每一处的多次波贡献,可以给出更准确的多次波预测。建立了三维倾斜层状速度模型,模拟含多次波的地震数据,利用3D SRME技术进行多次波预测,对比了2D SRME与3D SRME对三维地震数据的多次波预测结果,发现3D SRME的预测结果与理论多次波位置吻合;最后利用最小平方匹配减去法,实现了地震数据中多次波的去除,有效地压制了多次波信息。     

Attenuation of multiple waves using the continuous wavelet transform (CWT)

This paper describes how the continuous wavelet transform is used to filter multiple waveforms in both time and frequency domains. It is well suited to process the stationary signals, and it shows the signal in both time and frequency scales. This new approach was tested first on synthetic data and then on real data. The results obtained on both cases were good. The method consists of identifying the multiples on which we apply a normal move out using the multiple velocity law. The multiples will be aligned and the primary reflections will not be aligned. This operation allows locating the multiples in the time-scale domain. We compute the continuous wavelet transform (CWT for short) in order to focus on the patterns relative to seismic events. To filter the multiples, we define a zone with frequency and time bounds. These bounds are deduced from the projection of the seismic trace. Then an automatic mask is applied to the pattern to be isolated. Filtering in time–frequency domain is done by keeping only the wavelet coefficients that are outside the mask and assigning zero to the coefficients larger than a threshold amplitude inside the defined zone. The mask shape does not matter, which is not the case in classical filtering, where both the window size and shape play a key role. The mask is defined from three parameters: time, frequency, and the wavelet coefficients. To go back to the time domain, one has to compute the wavelet transform inverse of the trace. This procedure is repeated for all traces. To reset the traces to their initial positions, we apply the dynamic correction inverse with the same velocity law as the multiples. It turns out that the attenuation of multiples by the CWT works fine, in particular, the two identified multiples were quasi eliminated (Fig. 10).     

干涉波场重建衰减OBC层间多次波

由于OBC(ocean bottom cable)数据的采集方式为接收电缆铺设在海底,炮点在海面,常规的层间多次波压制方法不再适用,这给实际数据的处理带来了巨大的困难。本文利用地震波场干涉重建方法,对采集到的OBC数据进行波场重建,得到炮点和检波点都位于海底的虚拟炮集记录,与常规的在地表激发、地表接收的炮集一样,把OBC数据的层间多次波转化成常规的表面相关多次波和层间多次波,再进行预测。将其结果与共聚焦点(CFP)边界算法去除层间多次波的结果进行了对比,体现干涉重建技术在OBC数据层间多次波预测方面的准确性。     

基于不同小波变换与同态滤波结合的CBERS-02B卫星CCD图像的薄云去除

卫星CCD图像的去云处理对遥感信息的增强与提取有重要的意义,尤其是在云覆盖严重的低纬度地区。为去除CBERS-02B卫星CCD图像中薄云的影响,分别使用Mallat和à trous 2种小波变换对图像进行分解;利用同态滤波对2种小波分解图像的低频系数进行处理,衰减其低频信息;将处理后的小波低频系数与分解的高频系数进行小波重构,从而达到去云的目的。定量分析基于Mallat和à trous小波变换结合同态滤波法的去云结果表明,经à trous小波变换结合同态滤波法的去云影像所包含信息量大,细节信息丰富,去云效果较好。     

Star formation and the kinematics of gas in the disk of NGC 628

The radial profile of the star-formation rate (SFR) in the galaxy NGC 628 is shown to be modulated by a spiral-density wave. The radial profile of the velocity of gas inflow into the spiral arm is similar to the radial distribution of the surface density of the SFR. The position of the corotation resonance is determined along with other parameters of the spiral-density wave via a Fourier analysis of the azimuthal distribution of the observed radial velocities in annular zones of the disk of NGC 628. The radial profile of the surface density of the SFR is determined using the empirical SFR—linear size relation for star-formation complexes (giant HII regions) and measurements of the coordinates, Hα fluxes, and the sizes of HII regions in NGC 628.     

基于小波包分析的地震资料联合去噪方法研究

在地震记录中,随机噪声严重影响了有效信号的提取,为此必须进行消噪处理。这里首先使用小波包变换对不同频段的信号进行精细分离,有效信号和噪声经小波包分解后,其小波包系数将表现出不同特性,然后根据这种不同特性进行去噪处理,对小波包分析法处理后的剩余地震信号再进行KL(Karhunen-Loeve)变换,提取相关有效信号,最后对提取的有效信号进行中值滤波处理,进一步去除剩余噪声。经合成地震剖面和实际地震剖面处理实验证明,小波包分析、KL变换和中值滤波联合去噪方法,能有效地消除较强的随机噪声,提高地震剖面信噪比和分辨率。     

小波分析和RBF神经网络在地基沉降预测中的应用研究

地基沉降是一种危害很大的环境灾害。地基沉降的监测数据经常受降雨及工程施工等诸多外界因素的干扰,故而在沉降曲线中存在许多数据突变点。为此,提出基于小波分析与RBF神经网络相结合的新的地基沉降预测方法,首先采用小波分析对对原始监测数据进行数据去噪处理,进而得到反映实际变化的地基沉降曲线,然后采用径向基函数（RBF）神经网络方法对其进行预测,为工程设计提供依据。最后结合工程实例分析,通过多种小波去噪与预测结果的对比研究,表明3次B样条小波的去噪及预测效果最好,与实测值能较好地吻合,具有较好的工程应用前景。     

Performance of seismic arrays in the presence of weathering layer variations

Near-surface layer variations can degrade the desired response of seismic arrays which are typically used to attenuate horizontally traveling coherent noise and enhance vertically traveling signal. We investigate the effect of variations in the near-surface layer thickness on the performance of arrays by studying their impulse and wavelet responses. The models considered include the topographic variations and a channel in the base of weathering layer. The topographic variations include a dipping surface layer as well as a surface layer that follows a sine wave. The geological channel is assumed to be present under the entire receiver array as well as partially under a few receivers. We use Ricker wavelet and model plane wavefronts with incidence angles (90, 70, 45, 20, and 5 °) on a 12-element equally weighted array for the weathering layer models. We found that the array responses are more degraded for near-vertically traveling waves in all cases. The array responses are also found to be more degraded when channel variations are present underneath a few receivers as compared to the entire array length. We recommend designing a spatial filter or using single-sensor records after correcting for intra-array statics to preserve the reflection amplitudes in the presence of weathering layer variations.     

小波分析在试验信号消噪方面的应用

利用小波分析对试验数据进行后处理,较好的消除了系统的噪音。与Fourier变换法、10点平均滤波法比较后可知,小波分析方法能较好的保留原始数据的特征信息。对目前仍因被噪音困扰而不能正常进行的试验分析提供了一条解决途径。     

Automatic identification of fake patterns caused by short-width wavelets in seismic data

Despite the popularity of using the Haar wavelet filter in many applications, it sometimes introduces fake patterns into the multi resolution analysis (MRA) of seismic data. In this work, we compared different wavelet filters to demonstrate that these patterns are fake and not part of the original waveforms and to show that they are a result of using the Haar wavelet filter as a short-width wavelet. To achieve this, many seismic waveforms from two different sources: the Egyptian National Seismic Network (ENSN) and the High Sensitivity Seismograph Network Japan (Hi-net) are used with different wavelet filters. We propose an algorithm based on an autoregressive (AR) model to detect these patterns automatically and fully.     

Wavelets and the Generalization of the Variogram

The experimental variogram computed in the usual way by the method of moments and the Haar wavelet transform are similar in that they filter data and yield informative summaries that may be interpreted. The variogram filters out constant values; wavelets can filter variation at several spatial scales and thereby provide a richer repertoire for analysis and demand no assumptions other than that of finite variance. This paper compares the two functions, identifying that part of the Haar wavelet transform that gives it its advantages. It goes on to show that the generalized variogram of order k=1, 2, and 3 filters linear, quadratic, and cubic polynomials from the data, respectively, which correspond with more complex wavelets in Daubechies's family. The additional filter coefficients of the latter can reveal features of the data that are not evident in its usual form. Three examples in which data recorded at regular intervals on transects are analyzed illustrate the extended form of the variogram. The apparent periodicity of gilgais in Australia seems to be accentuated as filter coefficients are added, but otherwise the analysis provides no new insight. Analysis of hyerpsectral data with a strong linear trend showed that the wavelet-based variograms filtered it out. Adding filter coefficients in the analysis of the topsoil across the Jurassic scarplands of England changed the upper bound of the variogram; it then resembled the within-class variogram computed by the method of moments. To elucidate these results, we simulated several series of data to represent a random process with values fluctuating about a mean, data with long-range linear trend, data with local trend, and data with stepped transitions. The results suggest that the wavelet variogram can filter out the effects of long-range trend, but not local trend, and of transitions from one class to another, as across boundaries.