The attenuated Ricker wavelet basis for seismic trace decomposition and attenuation analysis

The widely used wavelets in the context of the matching pursuit are mostly focused on the time–frequency attributes of seismic traces. We propose a new type of wavelet basis based on the classic Ricker wavelet, where the quality factor Q is introduced. We develop a new scheme for seismic trace decomposition by applying the multi-channel orthogonal matching pursuit based on the proposed wavelet basis. Compared with the decomposition by the Ricker wavelets, the proposed method could use fewer wavelets to represent the seismic signal with fewer iterations. Besides, the quality factor of the subsurface media could be extracted from the decomposition results, and the seismic attenuation could be compensated expediently. We test the availability of the proposed methods on both synthetic seismic record and field post-stack data.     

地震属性技术的研究和应用

地震属性的研究大致从上个世纪60年代开始,经历了几个阶段的发展后得到了广泛的应用.由于地震属性的解释可获得许多有关地层、断层、裂缝、岩性和相的变化的重要特征信息,我们结合地震属性特征参数的意义,从实际应用出发,把地震属性分为了振幅、频（能）谱、相位、复地震道、层序、相关六大类,并根据在地层、断裂、岩性等方面的实际应用进行了详细描述,讨论了属性分析技术原理中应注意的几个环节.最后通过对断裂、河道、火成岩、古潜山等几个实例的详细描述,证明了相干、阻抗、振幅等地震属性的应用效果,说明了地震属性在实际应用中的作用.     

Coherence algorithm with a high-resolution time–time transform and feature matrix for seismic data

Traditional coherence algorithms are often based on the assumption that seismic traces are stationary and Gaussian. However, seismic traces are actually non-stationary and non-Gaussian. A constant time window and the canonical correlation analysis in traditional coherence algorithms are not optimal for non-stationary seismic traces and cannot describe the similarity between adjacent seismic traces in detail. To overcome this problem, a new coherence algorithm using the high-resolution time–time transform and the feature matrix is designed. The high-resolution time–time transform used to replace the constant time window can produce a frequency-dependent time local series to analyse non-stationary seismic traces. The feature matrix, constructed by the frequency-dependent time local series and the related local gradients, defines a new correlation metric that enhances more details of the geological discontinuities in seismic images than does the canonical correlation analysis. Additionally, the Riemannian metric is introduced for related calculations because the feature matrices are not defined in a Euclidean space but rather in a manifold space. Application to field data illustrates that the proposed method reveals more details of structural and stratigraphic features.     

基于小波变换的地震相干体算法研究

基于计算相干体算法,提出了用模拟地震子波的小波函数(或高分辨导数小波函数)的小波变换,得到分频瞬时相位,再计算相干体的相干体算法1和用小波变换得到的实、虚部(相当Hilbert变换)计算相干体的相干体算法2. 在油田构造解释中,为了突出小断层特征,用分频计算出的相干体进行重构. 实际资料计算表明,相干体算法2较K. J. Marfurt相干体算法抗噪声能力强;相干体算法1较相干体算法2在实际应用中效果更明显.     

基于非平稳相似性系数的构造导向滤波及断层检测方法

不连续地质体（如断层）的自动检测一直以来都是叠后地震数据解释中的关键问题之一,尤其在三维情况中尤为重要.然而,大多数边缘检测和相干算法都对随机噪声很敏感,随机噪声衰减是叠后地震数据解释的另一个主要问题.针对构造保护去噪和断层检测问题,本文基于非平稳相似性系数完善一种构造导向滤波方法并且提出一种自动断层检测方法,形成了一套匹配的处理技术.该构造导向滤波既能够有效地衰减随机噪声又可以很好地保护地震资料中的断层等信息不被破坏,增强地震剖面中弯曲、倾斜同相轴的连续性.根据地震数据局部倾角走向,利用相邻道构建当前地震道的预测,通过预测道的叠加得到参考道,计算预测道与参考道之间的非平稳相似性系数可以设计出数据驱动的加权中值滤波.另一方面,预测道与原始道之间的非平稳相似性系数能够用于带有断层指示性的相干分析.这两种方法都基于构造预测和非平稳相似性系数,但是使用不同的调节参数和处理方案.理论模型和实际数据的处理结果证明了本文提出构造导向滤波和断层检测方法的有效性.     

Nonlinear structure‐enhancing filtering using plane‐wave prediction*

Attenuation of random noise and enhancement of structural continuity can significantly improve the quality of seismic interpretation. We present a new technique, which aims at reducing random noise while protecting structural information. The technique is based on combining structure prediction with either similarity‐mean filtering or lower‐upper‐middle filtering. We use structure prediction to form a structural prediction of seismic traces from neighbouring traces. We apply a non‐linear similarity‐mean filter or an lower‐upper‐middle filter to select best samples from different predictions. In comparison with other common filters, such as mean or median, the additional parameters of the non‐linear filters allow us to better control the balance between eliminating random noise and protecting structural information. Numerical tests using synthetic and field data show the effectiveness of the proposed structure‐enhancing filters.     

Wavelet‐based cepstrum decomposition of seismic data and its application in hydrocarbon detection

How to use cepstrum analysis for reservoir characterization and hydrocarbon detection is an initial question of great interest to exploration seismologists. In this paper, wavelet‐based cepstrum decomposition is proposed as a valid technology for enhancing geophysical responses in specific frequency bands, in the same way as traditional spectrum decomposition methods do. The calculation of wavelet‐based cepstrum decomposition, which decomposes the original seismic volume into a series of common quefrency volumes, employs a sliding window to move over each seismic trace sample by sample. The key factor in wavelet‐based cepstrum decomposition is the selection of the sliding‐window length as it limits the frequency ranges of the common quefrency section. Comparison of the wavelet‐based cepstrum decomposition with traditional spectrum decomposition methods, such as short‐time Fourier transform and wavelet transform, is conducted to demonstrate the effectiveness of the wavelet‐based cepstrum decomposition and the relation between these two technologies. In hydrocarbon detection, seismic amplitude anomalies are detected using wavelet‐based cepstrum decomposition by utilizing the first and second common quefrency sections. This reduces the burden of needing dozens of seismic volumes to represent the response to different mono‐frequency sections in the interpretation of spectrum decomposition in conventional spectrum decomposition methods. The model test and the application of real data acquired from the Sulige gas field in the Ordos Basin, China, confirm the effectiveness of the seismic amplitude anomaly section using wavelet‐based cepstrum decomposition for discerning the strong amplitude anomalies at a particular quefrency buried in the broadband seismic response. Wavelet‐based cepstrum decomposition provides a new method for measuring the instantaneous cepstrum properties of a reservoir and offers a new field of processing and interpretation of seismic reflection data.     

A COMPARISON OF STATISTICAL AND DETERMINISTIC WIENER DECONVOLUTION OF DEEP-TOW SEISMIC DATA*

Wiener ‘spiking’ deconvolution of seismic traces in the absence of a known source wavelet relies upon the use of digital filters, which are optimum in a least-squares error sense only if the wavelet to be deconvolved is minimum phase. In the marine environment in particular this condition is frequently violated, since bubble pulse oscillations result in source signatures which deviate significantly from minimum phase. The degree to which the deconvolution is impaired by such violation is generally difficult to assess, since without a measured source signature there is no optimally deconvolved trace with which the spiked trace may be compared. A recently developed near-bottom seismic profiler used in conjunction with a surface air gun source produces traces which contain the far-field source signature as the first arrival. Knowledge of this characteristic wavelet permits the design of two-sided Wiener spiking and shaping filters which can be used to accurately deconvolve the remainder of the trace. In this paper the performance of such optimum-lag filters is compared with that of the zero-lag (one-sided) operators which can be evaluated from the reflected arrival sequence alone by assuming a minimum phase source wavelet. Results indicate that the use of zero-lag operators on traces containing non-minimum phase wavelets introduces significant quantities of noise energy into the seismic record. Signal to noise ratios may however be preserved or even increased during deconvolution by the use of optimum-lag spiking or shaping filters. A debubbling technique involving matched filtering of the trace with the source wavelet followed by optimum-lag Wiener deconvolution did not give a higher quality result than can be obtained simply by the application of a suitably chosen Wiener shaping filter. However, cross correlation of an optimum-lag spike filtered trace with the known ‘actual output’ of the filter when presented with the source signature is found to enhance signal-to-noise ratio whilst maintaining improved resolution.     

压制空间非平稳地震勘探随机噪声的ROAD径向时频峰值滤波算法

径向时频峰值滤波算法是一种有效保持低信噪比地震勘探记录中反射同相轴的随机噪声压制方法,但该算法对空间非平稳地震勘探随机噪声压制效果不理想.本文研究空间非平稳地震勘探随机噪声,即各道噪声功率不同的地震勘探随机噪声,其在径向滤波轨线上表征近似脉冲噪声,在径向时频峰值滤波过程中干扰相邻道滤波结果.为了减小空间非平稳随机噪声的影响,本文提出一种基于绝对级差统计量(ROAD)的径向时频峰值滤波随机噪声压制方法.该方法首先根据径向轨线上信号的绝对级差统计量检测空间非平稳地震勘探随机噪声,然后结合局部时频峰值滤波和径向时频峰值滤波压制地震勘探记录中的随机噪声.将ROAD径向时频峰值滤波方法应用于合成记录和实际共炮点地震记录,结果表明ROAD径向时频峰值滤波方法可以压制空间非平稳地震勘探随机噪声且不损害有效信号,有效抑制随机噪声空间非平稳对滤波结果的影响.与径向时频峰值滤波相比,ROAD径向时频峰值滤波方法更适用于空间非平稳地震勘探随机噪声压制.     

多小波方法及其在深地震测深数据去噪中的应用

在宽角反射/折射地震测深数据处理中,仍多用基于傅里叶变换的滤波方法和小波去噪方法。鉴于傅里叶方法对稳态信号很有效但对非稳态的地震信号效果不佳的状况以及小波不能同时具有正交性、紧支性、对称性,本文给出了基于多小波的去噪方法,多小波具有正交性、对称性、紧支性,克服了传统小波的缺陷。编写了多小波去噪方法的人机交互软件。该软件可以方便快捷地显示宽角反射/折射地震记录截面,进行多小波域的阈值去噪。实例计算结果表明,本文所述方法和编写的软件有效且可行。     

局部相关加权中值滤波技术及其在叠后随机噪声衰减中的应用

随机噪声的衰减和同相轴连续性的提高可以极大地改善地震资料解释的精度.本文提出一种新的滤波技术,既能够有效地衰减随机噪声又可以很好地保护地震资料中的断层等信息不被破坏,增强地震剖面中弯曲、倾斜同相轴的连续性.该方法结合新的加权中值滤波技术和两种构造信息保护滤波策略,实现基于预测数据体和基于倾角走向的加权中值滤波.通过设计...     

Dip‐adaptive singular‐value decomposition filtering for seismic reflection enhancement

We present a singular value decomposition (SVD) filtering method for the enhancement of coherent reflections and for attenuation of noise. The method is applied in two steps. First normal move‐out (NMO) correction is applied to shot or CMP records, with the purpose of flattening the reflections. We use a spatial SVD filter with a short sliding window to enhance coherent horizontal events. Then the data are sorted in common‐offset panels and the local dip is estimated for each panel. The next SVD filtering is performed on a small number of traces and a small number of time samples centred around the output sample position. Data in a local window are corrected for linear moveout corresponding to the dips before SVD. At the central time sample position, we sum over the dominant eigenimages of a few traces, corresponding to SVD dip filtering. We illustrate the method using land seismic data from the Tacutu basin, located in the north‐east of Brazil. The results show that the proposed method is effective and is able to reveal reflections masked by ground‐roll and other types of noise.     

小波分析法在海拉尔地震台前兆数据处理中的应用研究

应用小波变换法可对不同频率成分进行分解的特性,选取d b4小波基函数,尺度为1～8阶,对海拉尔地震台前兆资料进行分析研究.结果表明,应用小波变换方法可较容易地识别和剔除气压、场地环境干扰等影响海拉尔地震台伸缩仪观测资料精度的诸多因素,气压和场地环境干扰在小波细节分解d3～d6部分异常显著;小波变换法对同震效应的识别、提...     

Coherence estimation algorithm using Kendall’s concordance measurement on seismic data

The coherence method is always used to describe the discontinuity and heterogeneity of seismic data. In traditional coherence methods, a linear correlation coefficient is always used to measure the relationship between two random variables (i.e., between two seismic traces). However, mathematically speaking, a linear correlation coefficient cannot be applied to describe nonlinear relationships between variables. In order to overcome this limitation of liner correlation coefficient. We proposed an improved concordance measurement algorithm based on Kendall’s tau. That mainly concern the sensitivity of the liner correlation coefficient and concordance measurements on the waveform. Using two designed numerical models tests sensitivity of waveform similarity affected by these two factors. The analysis of both the numerical model results and real seismic data processing suggest that the proposed method, combining information divergence measurement, can not only precisely characterize the variations of waveform and the heterogeneity of an underground geological body, but also does so with high resolution. In addition, we verified its effectiveness by the actual application of real seismic data from the north of China.     

Spectral factorization technique for estimation of an ARMA operator for multichannel deconvolution of seismic data

A new spectral factorization method is presented for the estimation of a causal as well as a causally invertible ARMA operator from the correlation sequence of seismic traces. The method has been implemented for multichannel deconvolution of seismic traces with the aim of exploiting the trace-to-trace correlation that exists within seismograms. A layered earth model with a small reflectivity sequence has been considered, and the seismic traces have been considered as the output of a linear system driven by white noise reflection coefficient sequences. The present method is the concatenation of three algorithms, namely Kung's method for state variable ( F , G , H ) realization using a singular value decomposition (SVD) algorithm, Faurre's technique for computation of the strong spectral factor and Leverrier's algorithm for ARMA representation of the spectral factor. The inverted ARMA operator is used as a recursive filter for deconvolution of seismic traces. In the example shown, two traces with a covariance sequence of 160 ms length have been considered for multichannel deconvolution of stacked seismic traces. The results presented, when compared with those obtained from a conventional deconvolution algorithm, have shown encouraging prospects.     

多尺度奇异性检测及其在地震相分析中的应用

本文从地震道的奇异属性出发,利用连续小波变换求取地震道的小波变换模极大值曲线,并沿此曲线提取地震道的小波变换系数,称之为小波变换模极大值连线振幅.此属性不仅可以代表信号本身,而且可以最大程度的区别于相邻道,并且具有地震道多尺度的特征,即兼具时频域的特征.由此结合自组织神经网络,我们提出了一种新的地震相分析方法.通过模型合成地震记录实验分析,证明此方法是可行的,且对地质层位的解释误差具有一定的容许度.最后,将此方法应用于了实际资料,取得了良好的效果.     

深地震反射剖面构造信息识别研究

随着我国深部探测计划的实施,近年来在中国大陆地区实施了多条深地震反射剖面,获得了大量揭示地壳上地幔精细结构的宝贵资料. 为了更充分地挖掘这些资料中所包含的深部构造信息,本文在研究和总结前人工作的基础上,提出一种快速识别深地震反射剖面构造格架的方法. 该方法通过数据预处理、强振幅提取、中值滤波、对象识别、连续性计算和连续性滤波实现对深地震反射剖面构造格架识别. 同时,该方法还可通过对象倾角计算对复杂区域进行属性分析.     

Feasibility of utilizing wavelet phase to map the CO2 plume at the Ketzin pilot site,Germany

Spectral decomposition is a powerful tool that can provide geological details dependent upon discrete frequencies. Complex spectral decomposition using inversion strategies differs from conventional spectral decomposition methods in that it produces not only frequency information but also wavelet phase information. This method was applied to a time‐lapse three‐dimensional seismic dataset in order to test the feasibility of using wavelet phase changes to detect and map injected carbon dioxide within the reservoir at the Ketzin carbon dioxide storage site, Germany. Simplified zero‐offset forward modelling was used to help verify the effectiveness of this technique and to better understand the wavelet phase response from the highly heterogeneous storage reservoir and carbon dioxide plume. Ambient noise and signal‐to‐noise ratios were calculated from the raw data to determine the extracted wavelet phase. Strong noise caused by rainfall and the assumed spatial distribution of sandstone channels in the reservoir could be correlated with phase anomalies. Qualitative and quantitative results indicate that the wavelet phase extracted by the complex spectral decomposition technique has great potential as a practical and feasible tool for carbon dioxide detection at the Ketzin pilot site.     

东营凹陷王庄--宁海地区馆陶组储层预测

在研究地质资料、测井资料的基础上,针对胜利油田王庄宁海地区馆陶组地层的变化特征规律,制定了新的储层预测技术方法.（1）精细构造技术研究：利用原始地震资料、地震道积分资料及小波分解资料,结合地质平面层序地层单元分析方法,划分出地质单元边界.（2）反演测井声波时差技术研究：利用地震小波变换属性、测井声波时差资料,采用稳健回归方法直接反演声波时差,进而计算孔隙度.该方法,可提高反演的分辨率,增加了反演结果的可靠性.结合研究区地质资料,把这种研究技术方法应用到王庄宁海地区馆陶组储层的预测研究,取得了良好的效果.     

重力场实数尺度小波分解及其应用

重力异常的多尺度分解是利用重力资料进行地质解释的重要环节,以往的小波多尺度分解,其小波细节尺度都是2的正整数次幂,这虽然非常有效,但在某些情况下,细节还是不够细致.因此,本文提出用无理数槡2的正整数次幂为尺度细节进行多尺度分解,以便取关于地壳三维密度结构的更多细节.中国陆地布格重力异常的实例表明,该方法得到的异常细节更为细致,新增加的无理尺度小波细节为我们提取了更多地壳构造信息,可对地质构造解释发挥更有力的作用.