基于正则化条件的地震数据局部信噪比估计方法

信噪比是衡量地震数据质量的重要指标之一,在地震数据处理和解释中有着重要的作用.目前已有的地震数据信噪比估计方法往往得到的是整个数据的全局信噪比,这种方法只能说明地震数据总体质量的好坏,无法直观细致地刻画地震信号的局部质量.本文提出一种基于正则化条件的局部信噪比估计方法.该方法的基本原理是使用正则化共轭梯度法求解局部信噪比最优解,正则化算子的参数将控制地震信号各点数据局部信噪比的平滑性.其中应用一种基于"过滤波"的级联信号估计方法来计算有效信号,该方法利用有效信号和噪声的相关性特征计算局部信噪比中的有效信号.局部信噪比估计方法利用了信号中每个数据点及其邻域各点的局部信息,避免了使用单个数据点而可能出现的信噪比不合理值,而且局部处理能够减少全局噪声对信噪比估算的影响,该方法可以更准确地表征地震资料信噪分布特征.另外,局部信噪比对去噪方法的评估也具有重要意义.理论模型测试和实际资料处理结果表明,局部信噪比估计方法能够准确反映任一给定地震信号剖面的局部信噪比特征,为非平稳地震数据质量评估提供了直观的评判标准.     

地震分倒频处理技术

为刻画地震信号的局部层次特征,提高复杂地质体的地震分辨率,本文利用倒谱变换能够提高分辨率的特点,结合短时傅里叶变换,构造了倒时-频变换算法,并提出地震分倒频处理技术.文中对地震分倒频处理技术的公式推导、算法设计、分倒频处理技术提高地震纵向分辨率的机理进行了详细研究.设计出了适合三维地震资料处理的软件,并从理论上阐述了地震分倒频处理技术能够提高地震分辨率.利用倒时-频变换对多分量线性调谐信号模型做倒时-频分析,可以得到良好的时频分辨率.实际三维地震资料计算表明,该方法能够提高地震纵向分辨率,且计算效率高,适合大规模三维地震资料的处理.     

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.     

伪随机编码震源信号的地震响应

常规的可控震源Chirp扫描信号的地震响应存在着相关信号旁瓣大、分辨率低的缺点.本文利用数值模拟技术研究可控震源伪随机编码信号地震响应的规律和特点.伪随机编码信号的地震响应剖面的旁瓣电平与常规的Chirp扫描信号情形相比有明显地降低,但是伪随机编码信号地震响应剖面的相关噪声仍然没有得到有效地压制.利用伪随机编码信号的周期性特点把一个长地震记录以信号周期为间隔进行分时叠加可以提高地震记录的信噪比和地震数据的利用率.     

基于构造导向的地震数据信噪比属性计算方法（英文）

目前大多数信噪比估算方法只能计算地震数据的整体信噪比,而不能计算任意局部信噪比,本文提出一种基于构造导向的地震数据信噪比属性计算方法,旨在刻画地震数据信噪比在时间和空间上的变化特征。首先利用平面波分解滤波器计算地震数据的斜率参数,再利用奇异值分解方法计算局部地震数据的信噪比,由此得到随时空变化的信噪比。该方法克服了常规整体信噪比无法表征地震数据任意局部特征的不足,将信噪比作为地震数据的一种属性更加准确地描述地震数据随时空变化的信噪能量分布特征。理论模型测试和实际资料处理结果表明:信噪比属性不仅可以用于地震数据的质量评估还可用于去噪方法的分析和评价。     

煤田采区三维地震精细构造解释方法

虽然煤田三维地震勘探已经过了十多年的发展，但构造解释问题仍是目前需要解决的主要问题之一.随着三维地震资料解释方法的不断发展，小波分析技术、相干体技术、地震属性技术、图像处理等提高解释精度的方法相继在地震勘探领域中得到应用.另一方面，由于煤矿采区三维地震勘探资料一般具有高信噪比和高分辨率的特点，为做好三维地震资料精细构造解释提供了物质基础.本文结合小波分析技术、相干体技术、地震属性技术等多种方法，结合两个采区的实例，对小断层和小规模陷落柱做了精细构造解释.解释结果显示联合使用以上几种解释技术，能提高三维地震资料的构造解释精度和可靠信.     

谱分解和C3相干联合识别煤层小断层研究

C3相干具有较好的煤层小断层识别能力,但其易受随机噪声的影响,在信噪比较低的情况下容易产生假异常.另一方面,基于S变换的谱分解可以提高地震资料的时频分辨率,并对随机噪声具有一定的压制作用.为提高煤矿采区煤层小断层解释精度,结合谱分解技术与C3相干技术,以提高煤层小断层的解释精度和可靠性.本文分别利用正演剖面和实际三维地震数据,对所提出的方法进行了验证.首先建立了含不同落差的单一煤层模型,利用正演模拟方法获得了其正演剖面和含白噪声剖面.对于这两类剖面,利用S变换获得了其对应于不同频率的谱分解剖面.通过沿煤层反射波提取C3相干属性,获得了不同剖面所对应的C3相干值.对于无噪声地震剖面来说,文中所述方法能明显提高小断层的识别率;对于含白噪声的地震剖面来说,文中所述方法能显著提高所有落差断层的识别率,并基本克服了C3相干算法在低信噪比低情况下容易产生假异常的缺点.将文中所述方法应用到济宁二号煤矿15301工作面的实际三维地震数据中,发现较高频段的谱分解剖面所计算的C3相干同样比常规剖面所计算的C3相干有更好的小断层识别能力.对于煤系地层地质构造较简单的采区来说,利用较高频段谱分解剖面计算的C3相干对落差小于3m的小断层有明显反映.经过井巷工程的实际验证,所解释小断层的可靠性和精度都较高.但当煤系地层地质构造较复杂时,识别落差小于3m小断层的难度较大,还需进一步研究.总之,将谱分解技术和C3相干技术相结合,利用较高频段谱分解剖面计算C3相干,能够明显压制低信噪比所产生的假相干异常,提高煤层小断层的识别精度和可靠性.     

方向性边界保持断层增强技术

地震数据在采集处理过程中不可避免地会受到各种因素的影响,从而导致地震资料的信噪比低,造成断层信息模糊,断层增强的目的是进一步清晰地刻画断层,同时提高地震资料的信噪比.本文提出了方向性边界保持断层增强技术,首先通过方向滤波技术估计地震同相轴的方向信息,然后结合边界保持滤波技术进行断层图像的增强,将该技术用于地震资料,可以得到断层图像更加清晰、分辨率更高的三维地震相干体,以利于进一步的构造解释以及油气输导体系的定量评价,具有重要的理论与应用价值.     

地震频发区域背景噪声提取格林函数的反褶积方法研究

针对云南这一地震频发区域记录到的地震背景噪声数据,设计了一种"最大值均一化"算法,该算法能有效地消除背景噪声中的地震信号、畸变信号及其它干扰信号。应用此算法对记录到的背景噪声数据进行预处理,对处理后的数据利用多窗谱反褶积计算方法可获得其具有较高信噪比和保留了相对幅值信息的格林函数。     

基于高通滤波的频率-空间域经验模态分解压制高频噪声

高频噪声压制是高分辨率地震数据处理中提高信噪比的关键性问题.本文针对f-x(频率-空间)反褶积空间预测滤波器无法处理非平稳、非线性信号的缺点,提出了一种基于高通滤波的频率-空间域经验模态分解(Empirical Mode Decomposition in the frequency-space domain,f-xEMD)压制地震剖面中高频噪声的方法.该方法采用全域高通滤波从原始数据中分离出含有部分有效信号的高频数据,将其变换到f-x域,然后在滑动的短窗口内提取每一个频率的空变数据序列进行EMD分解得到高频复本征模态函数(Intrinsic Mode Function,IMF)IMF1,将所有频率的IMF1序列反Fourier变换到时间域得到噪声剖面,将其与原始数据相减,达到高频噪声压制的目的.该方法可克服传统EMD分解方法中的模态混叠现象,保护陡倾角反射同相轴;压制后的噪声剖面中不包含有效信号能量,地震剖面的信噪比得到了提高.模拟数据和实际数据处理结果充分证明了该方法的有效性.     

图像数字去噪处理方法研究及其应用

本文基于地震剖面的数字化图像特征,提出用光栅算子将地震剖面按产状分离成产状相对单一的多幅数字图像剖面。对每一幅产状相对单一的数字图像剖面,用向量分解技术的向量最大特征值对应基向量投影的原理获取有效相干信息的办法实现信噪分离;在结合地质、物探分析的基础上进行最终输出剖面的滤波加权重建,获得信噪比高、波组特征保持好、分辨率相对保证的剖面。实际资料处理结果表明本文提出方法的去噪应用效果显著。     

基于Curvelet变换的地震资料信噪分离技术

在地震资料中,噪声干扰严重影响了有效信号的提取,为此必须进行信噪分离处理.本文提出一种基于Curvelet变换和KL变换相结合的软硬阈值折衷处理方法.首先对地震数据进行Curvelet变换,然后对各尺度系数选取适当阈值压制噪声干扰,再利用KL变换提取数据中的相干有效信号,最后重构得到去噪后的记录.经合成记录和实际地震资料处理实验证明,该方法与小波变换法相比较,更能有效进行信噪分离,提高地震剖面信噪比和分辨率.     

SEISMIC HORIZON DETECTION USING IMAGE PROCESSING ALGORITHMS1

Seismic sections used in interpretation are actually images. We often superimpose colour-coded pictures of seismic attributes on seismic sections. Thus, it seems straightforward to use image processing algorithms to enhance the quality of the seismic images. From an image processing point of view, seismic horizons can be thought of as edges on the seismic image. We present a novel approach to detecting seismic horizons, which includes the 2D median filtering of the instantaneous phase attribute and applying an edge detection algorithm. The resulting edge magnitude picture provides a skeletonized image of the seismic section, on which the structural and stratigraphic patterns can be better recognized.     

小波变换的过零点特性与地震勘探信号的信噪比和分辨率

利用小波变换研究地震勘探信号小波变换的过零点特性，本文提出了用小波变换的过零点特性和地震勘探信号相邻道的横向相关性提高信号分辨率和信噪比的新方法．该方法包括两个主要步骤：①利用相邻地震道信号具有很好相关性，而噪音相关性差的特点以及小波变换的过零点特性得到有效反射波同相轴随空间坐标的变化信息．②利用奇异值分解和最小二乘（SVD-TLS）方法沿同相轴对振幅进行多项式拟合去噪并增加信号高频提高信号分辨率．     

Direct migration of ambient seismic data

Utilising ambient seismic energy naturally propagating in the Earth as an alternative approach to active body-wave seismic investigations has been a topic of interest for a number of decades. However, because ambient surface-wave arrivals typically are of much greater amplitude than ambient body-wave energy, significant data signal processing and long recording times are required to mitigate this and other coherent noise sources, and to correlate sufficient reflected body-wave energy to converge to a stable image. Even for these scenarios, identifying and validating imaged body-wave reflection events remain challenging. In active-source investigations, extended imaging condition gathers are used to examine velocity (in)accuracy. Herein, we develop an ambient direct migration approach that uses a novel ambient (deconvolution) extended imaging condition. We simulate synthetic ambient-wavefield seismic data for two different models and use a field data set from Lalor Lake in Manitoba, Canada, to conduct a series of numerical experiments to demonstrate the velocity sensitivity and long-term stationarity of ambient-wavefield seismic data in the migration image domain. Tests with varying global velocity perturbations show a characteristic reflector moveout in deconvolution extended imaging condition gathers that can serve as a diagnostic of reflected ambient body-wave energy. We illustrate that this imaging formalism, under idealised circumstances, gives comparable results to conventional seismic methods, which extends the use of extended imaging condition gather-based image validation to ambient-wavefield seismic data scenarios. We assert that this may be a valuable tool for the validation of ambient migration techniques that to date have yielded largely inconclusive results.     

基于压缩感知的高分辨率平面波分解方法研究

平面波分解方法是地震资料处理中的一项关键技术,它广泛地运用在平面波偏移、各类Beam偏移等成像方法中.平面波分解不仅可以提高偏移成像的效率,而且可以压制地震资料中的随机噪音,提高地震数据的信噪比.线性Radon变换（LRT）是一种常见的实现平面波分解的方法,但常规的LRT存在以下两个缺点：（1）分辨率受测不准原理限制;（2）变换结果存在很多噪音和空间假频.为了克服LRT的上述缺点,本文提出一种基于压缩感知的高分辨率平面波分解方法,并利用加权匹配追踪（WMP）技术实现了该方法.该方法将LRT视为一个参数估计问题,并将LRT结果的稀疏性作为约束条件,在压缩感知理论的指导下利用WMP方法得到高分辨率、高信噪比的平面波分解结果.另外,该方法还可以用于提取地震数据的线性信号、压制随机噪音、实现高维地震数据规则化等地震资料处理技术.数值实验结果证明：WMP方法可以有效地提取地震数据中的线性信号,提高LRT的分辨率和信噪比,从而改善平面波分解的质量.     

Application of sub-image multiresolution analysis of Ground-penetrating radar data in a study of shallow structures

Fourier-based algorithms originally developed for the processing of seismic data are applied routinely in the Ground-penetrating radar (GPR) data processing, but these conventional methods of data processing may result in an abundance of spurious harmonics without any geological meaning. We propose a new approach in this study based essentially on multiresolution wavelet analysis (MRA) for GPR noise suppression. The 2D GPR section is similar to an image in all aspects if we consider each data point of the GPR section to be an image pixel in general. This technique is an image analysis with sub-image decomposition. We start from the basic image decomposition procedure using conventional MRA approach and establish the filter bank accordingly. With reasonable knowledge of data and noise and the basic assumption of the target, it is possible to determine the components with high S/N ratio and eliminate noisy components. The MRA procedure is performed further for the components containing both signal and noise. We treated the selected component as an original image and applied the MRA procedure again to that single component with a mother wavelet of higher resolution. This recursive procedure with finer input allows us to extract features or noise events from GPR data more effectively than conventional process.To assess the performance of the MRA filtering method, we first test this method on a simple synthetic model and then on experimental data acquired from a control site using 400 MHz GPR system. A comparison of results from our method and from conventional filtering techniques demonstrates the effectiveness of the sub-image MRA method, particularly in removing ringing noise and scattering events. Field study was carried out in a trenched fault zone where a faulting structure was present at shallow depths ready for understanding the feasibility of improving the data S/N ratio by applying the sub-image multiresolution analysis. In contrast to the conventional methods, the MRA sub-image filtering technique provides an overall improvement in image quality of the data as shown in the field study.     

克希霍夫法VSP多波联合成像

VSP 转换波跟VSP 纵波或常规地面转换波相比，具有较高的分辨率和信噪比，但传统的VSP成像方法只利用了反射P波信息，而把转换波（反射S波、透射S波）以及透射P波当作影响成像质量的噪音.本文给出了一种VSP共炮点道集多分量地震资料克希霍夫法偏移成像的方法.本方法充分利用了多波（反射P波、反射S波、透射P波、透射S波）信息，根据转换点处四种波同时起跳，能量叠加最大的原理，从接收点分别用向绕射点延拓它们的能量，并将其叠加起来，求得的和最大的一点即反射点.通过模型试算和实际资料处理表明，此法成像精度高，信噪比高，且有利于改善剖面的频率特性.     

OPTIMUM DIGITAL FILTERS FOR SIGNAL TO NOISE RATIO ENHANCEMENT*

One of the main objectives of seismic digital processing is the improvement of the signal-to-noise ratio in the recorded data. Wiener filters have been successfully applied in this capacity, but alternate filtering devices also merit our attention. Two such systems are the matched filter and the output energy filter. The former is better known to geophysicists as the crosscorrelation filter, and has seen widespread use for the processing of vibratory source data, while the latter is. much less familiar in seismic work. The matched filter is designed such that ideally the presence of a given signal is indicated by a single large deflection in the output. The output energy filter ideally reveals the presence of such a signal by producing a longer burst of energy in the time interval where the signal occurs. The received seismic trace is assumed to be an additive mixture of signal and noise. The shape of the signal must be known in order to design the matched filter, but only the autocorrelation function of this signal need be known to obtain the output energy filter. The derivation of these filters differs according to whether the noise is white or colored. In the former case the noise autocorrelation function consists of only a single spike at lag zero, while in the latter the shape of this noise autocorrelation function is arbitrary. We propose a novel version of the matched filter. Its memory function is given by the minimum-delay wavelet whose autocorrelation function is computed from selected gates of an actual seismic trace. For this reason explicit knowledge of the signal shape is not required for its design; nevertheless, its performance level is not much below that achievable with ordinary matched filters. We call this new filter the “mini-matched” filter. With digital computation in mind, the design criteria are formulated and optimized with time as a discrete variable. We illustrate the techniques with simple numerical examples, and discuss many of the interesting properties that these filters exhibit.