地震复谱分解技术及其在烃类检测中的应用

谱分解技术在地震解释领域已得到广泛应用,但常用的谱分解方法存在两方面的不足.一是时间分辨率低,难以对薄层进行刻画;二是在烃类检测中多解性强,难以区分流体类型.为了改善该问题,本文提出一种基于地震复谱分解技术的烃类检测方法.复谱分解是指用一个包含多个不同频率Ricker子波的复子波库对地震道进行分解,从而得到时变子波频率和相位信息的过程.借助稀疏反演技术复谱分解可以获得高分辨率的时频能量谱和时频相位谱.本文首先通过拟合算例验证了复谱分解方法刻画薄层的能力以及求取子波频率和相位的准确性.然后利用基于Kelvin-Voigt模型的黏弹波动方程数值模拟对衰减引起子波相位改变的原因进行了分析.最后通过实际资料应用展示了本文方法在储层预测中的高时间分辨率优势,验证了利用子波相位信息识别气藏的有效性.     

基于复数道地震记录的匹配追踪算法及其在储层预测中的应用

匹配追踪算法是一种高精度的非线性的时频分析方法.该方法自从提出以来在地球物理学领域得到了广泛的应用.在以前的应用中,作者们都是在实信号的基础上对算法原理作了适当的简化.本文在复数地震道的基础上,基于复Morlet子波,阐述了匹配追踪算法的原理及其算法实现过程,并给出了具体的算法流程图.通过与传统的时频分析的比较,验证了该算法具有较高的时频分析精度.对于实际资料的应用表明,该算法能够很好的显示储层的位置与边界.     

利用零偏移VSP资料估计介质品质因子方法研究

利用峰值频率移动法估算零偏VSP资料的品质因子Q．该方法用Ricker子波和匹配地震子波分别逼近零相位和混合相位的震源子波,得到了峰值频率移动法估计Q值的公式．进而针对常规方法估计的地震子波峰值频率精度不高的问题,提出了估计地震子波峰值频率的特征结构法．通过合成零偏VSP资料的仿真试验,验证了峰值频率移动法估计Q值的正确性．仿真结果表明,与快速Fourier变换和Burg最大熵方法相比较,特征结构法得到的峰值频率和Q值精度高一些．仿真结果也表明,用峰值频率移动法估计Q值时需要选取恰当的子波参数,否则影响Q值估计的精度．     

基于改进的最佳匹配地震子波的地震资料衰减特性分析

简述了改进的最佳匹配地震子波的小波函数构造及参数的物理含义;根据地震波的高、低频分量在黏弹介质中传播时被地层吸收的差异,给出了一种在时-频域定性估计地震波衰减特性的方法;分别以改进的最佳匹配地震子波的小波及Morlet小波作为母小波分析地层吸收特性,并比较了两种小波函数刻画地层吸收特性的能力;测试了这种方法对噪声的敏感程度. 将文中提出的方法用于某油田的一段实测地震资料衰减分析,得到的吸收特性剖面能较好地反映油气的空间展布.     

声子波及其在地震波资料分解中的应用

声子波是由声波波动方程的解构成的一种物理子波,如果不考虑吸收和散射,声子波的传播是相当简单的;相反地,数学子波的传播即使在均匀介质中也是极其复杂的.作为波动方程的解,声子波比一般的数学子波更能有效地应用于复杂声波和地震波的分解和分析.本文从Kaiser的声子波理论出发,给出了通过分别引入点源波形的复时间函数和点源虚时间坐标来构成声子波的两种解释,并对点源模型的合成地震图和实际复杂模型的地震波资料进行了时-空域的声子波变换,说明了声子波应用于地震波资料分解的有效性.     

Ricker子波视主频的变化对混沌振子检测效果的影响

针对地震勘探资料中存在加性强随机噪声干扰,已经提出用混沌振子系统处理的方法技术.为完善该方法,需要研究诸如地震勘探同相轴完整程度、组成同相轴的地震子波变化等对系统检测效果的影响.本文以Ricker子波模拟地震子波,研究Ricker子波视主频变化的相应检测效果.研究结果：随着Ricker子波视主频的升高,检测SNR逐渐变差,在高频部分SNR的变化明显比低频部分缓慢;在通常地震勘探频率范围内,混沌振子系统检测SNR有可能部分补偿由于地震波传播引起的幅度降低;为检测由畸变子波构成的同相轴提供一定的可能.     

Ricker子波核最小二乘支持向量回归滤波方法的稳健性研究

除了信噪比、有效子波畸变等,稳健性(Robustness)也是度量滤波方法效果的一个重要的物理量,它刻画了滤波系统应对异常点值的能力.一般用影响函数作为评价稳健性的工具.支持向量机方法已较成功地应用于信号与图像的滤波中,尤其Ricker子波核方法更适于地震勘探信号处理.通过考察Ricker子波核最小二乘支持向量回归(L...     

多尺度快速匹配追踪多域联合地震反演方法

多尺度快速匹配追踪多域联合地震反演是一种通过地震数据多尺度分解的迭代反演方法.与此同时,在快速匹配追踪算法中引入低频模型约束,有效提高了收敛精度,使反演结果具有丰富的高低频信息.首先通过对大尺度地震资料进行反演得到低频背景.在此基础上,采用中尺度与小尺度地震数据进行逐级迭代用以获得高频数据,因而有效缓解了常规反演方法对于初始模型精度的依赖.最后利用理论模型与实际地震数据进行测试,通过与常规时间域反演方法的反演结果进行对比可以看出,本文方法在地层连续变化处依然可以对变化地层进行精确刻画,且在纵向分辨率提升的同时保持了较好的横向连续性.     

Time-frequency decomposition of seismic signals via quantum swarm evolutionary matching pursuit

Matching pursuit belongs to the category of spectral decomposition approaches that use a pre-defined discrete wavelet dictionary in order to decompose a signal adaptively. Although disengaged from windowing issues, matching point demands high computational costs as extraction of all local structure of signal requires a large size dictionary. Thus in order to find the best match wavelet, it is required to search the whole space. To reduce the computational cost of greedy matching pursuit, two artificial intelligence methods, (1) quantum inspired evolutionary algorithm and (2) particle swarm optimization, are introduced for two successive steps: (a) initial estimation and (b) optimization of wavelet parameters. We call this algorithm quantum swarm evolutionary matching pursuit. Quantum swarm evolutionary matching pursuit starts with a small colony of population at which each individual, is potentially a transformed form of a time-frequency atom. To attain maximum pursuit of the potential candidate wavelets with the residual, the colony members are adjusted in an evolutionary way. In addition, the quantum computing concepts such as quantum bit, quantum gate, and superposition of states are introduced into the method. The algorithm parameters such as social and cognitive learning factors, population size and global migration period are optimized using seismic signals. In applying matching pursuit to geophysical data, typically complex trace attributes are used for initial estimation of wavelet parameters, however, in this study it was shown that using complex trace attributes are sensitive to noisy data and would have lower rate of convergence. The algorithm performance over noisy signals, using non-orthogonal dictionaries are investigated and compared with other methods such as orthogonal matching pursuit. The results illustrate that quantum swarm evolutionary matching pursuit has the least sensitivity to noise and higher rate of convergence. Finally, the algorithm is applied to both modelled seismograms and real data for detection of low frequency anomalies to validate the findings.     

零偏移距VSP资料层Q反演及其应用研究(英文)

地层品质因子Q的可用于地震资料高分辨率处理,而从VSP资料下行直达波更容易获取准确的地层品质因子。通过对零偏移距VSP资料的监控子波和下行初至波的频谱进行综合分析,仿照Ricker子波频谱的表达式,本文提出了震源子波频谱新的表达式。在震源子波频谱新的表达式基础上,我们介绍了改进的频谱拟合法和改进的谱比法的层Q值反演方法及相应的处理流程。基于本文提出的层Q值反演方法,利用实际的零偏移距VSP资料的下行直达波,反演稳定的层Q值,并用于零偏移距VSP资料及井旁地面地震资料的反Q滤波振幅补偿处理,提高了地震资料的分辨率。     

改进的高精度匹配追踪方法研究及应用

本文在常规算法的基础上,提出了一种改进的匹配追踪方法.该方法通过引入新的完备库构建策略,并以雷克子波作为原子,利用原始地震数据最大相关性估计完备库的原子的位置和能量,使得分解精度进一步提高,极大地提高了算法的适应性;为避免原子间隔过小问题,引进了最小原子间距,使得分解效率和分解质量进一步提高.模型试算和实际资料应用表明,本文算法不仅提高了信号稀疏表示的质量,加快了收敛速度,而且算法的适应性和分解精度也得到提高;该方法能够较好地挖掘地震有效信息,提高地震解释精度.     

AVO信息约束匹配追踪技术在富煤储层刻画中的应用

针对西湖凹陷富煤环境下储层刻画精度低问题,本文结合煤层AVO截距、梯度特征,提出一种基于AVO信息约束的匹配追踪技术,压制煤层强反射引起的岩性假象,凸显储层真实、有效信号。该方法首先利用煤层4类AVO负强截距P、正强梯度G特点,构建煤层地震敏感因子P - G,放大煤层地震响应,并压制非煤层强振幅影响,实现煤层位置精细定位;在此基础上,将该煤层地震信息作为匹配追踪需要分解、重构的原始信号,利用复地震道分析技术提高信号快速匹配分解的效率,完成煤层强反射解耦。模型试算及实际资料应用表明:匹配追踪技术在精细定位煤层地震响应基础上,提高了匹配追踪算法去煤层强振幅效率;煤层解耦后地震数据较好地凸显储层横向展布变化,提高主力气层的纵向刻画精度。      

地震资料处理中小波函数的选取研究

本文给出了常见地震子波的一个模拟公式，可以很好地模拟零相位及混合相位子波，在一定意义上也可以近似模拟最大相位及最小相位子波．模拟出的子波加上适当的修正项后满足允许条件，可用作小波函数．与Ｍｏｒｌｅｔ小波类似，在实际应用中这些修正项在一定条件下可以略去，文中对Ｍｏｒｌｅｔ小波作了改造，使其能更好地适应于地震资料处理．研究了反射波能量及噪声等干扰波在时间－尺度域的分布特征与所选基本小波的关系．提出用地震子波（或与地震子波相近的函数）作为基本小波，对地震资料进行去噪及分频解释的方法．最后用实例证明方法的有效性．     

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.     

Klauder wavelet removal before vibroseis deconvolution

The spiking deconvolution of a field seismic trace requires that the seismic wavelet on the trace be minimum phase. On a dynamite trace, the component wavelets due to the effects of recording instruments, coupling, attenuation, ghosts, reverberations and other types of multiple reflection are minimum phase. The seismic wavelet is the convolution of the component wavelets. As a result, the seismic wavelet on a dynamite trace is minimum phase and thus can be removed by spiking deconvolution. However, on a correlated vibroseis trace, the seismic wavelet is the convolution of the zero-phase Klauder wavelet with the component minimum-phase wavelets. Thus the seismic wavelet occurring on a correlated vibroseis trace does not meet the minimum-phase requirement necessary for spiking deconvolution, and the final result of deconvolution is less than optimal. Over the years, this problem has been investigated and various methods of correction have been introduced. In essence, the existing methods of vibroseis deconvolution make use of a correction that converts (on the correlated trace) the Klauder wavelet into its minimum-phase counterpart. The seismic wavelet, which is the convolution of the minimum-phase counterpart with the component minimum-phase wavelets, is then removed by spiking deconvolution. This means that spiking deconvolution removes both the constructed minimum-phase Klauder counterpart and the component minimum-phase wavelets. Here, a new method is proposed: instead of being converted to minimum phase, the Klauder wavelet is removed directly. The spiking deconvolution can then proceed unimpeded as in the case of a dynamite record. These results also hold for gap predictive deconvolution because gap deconvolution is a special case of spiking deconvolution in which the deconvolved trace is smoothed by the front part of the minimum-phase wavelet that was removed.     

Ricker子波核支持向量回归的Mercer条件拓展问题研究

Ricker子波核支持向量回归方法是消减地震勘探记录强随机噪声的新滤波技术.用判定支持向量允许核函数的Mercer条件探讨Ricker子波核函数的有效性,经过数值计算相应的核矩阵的最小特征值,发现在一个较大范围内存在极小的负值带,数量级为10^-13~10^-16,且在正值带中亦存在10^-13~10^-15数量级的量.考虑到正负极小量值的计算误差机理相近,认为判定核函数有效性的Mercer条件在工程应用时有可能适当放宽,即核矩阵不严格半正定,接近半正定亦可.为了将Ricker子波核支持向量回归滤波方法向实际应用发展,本文对不同的理论模型的Ricker子波核滤波和小波变换滤波、自适应维纳滤波这三种技术的效果进行了比较,包括时域波形、频域振幅谱、滤波前后的信噪比以及均方误差等方面.结果表明,Ricker子波核滤波方法优于另两种方法.为实际应用Ricker子波核滤波方法奠定基础.     

利用基于子波估计的频谱校正方法提高Q值估计精度(英文)

用Q值刻画的地震衰减在地震信号处理和解释中具有很广泛的应用。利用反射地震资料进行Q值估计需要解决地震子波和反射系数序列耦合的问题。从反射地震资料中去除反射系数序列的影响,这个过程称为频谱校正。本文提出了一种基于子波估计的求取Q值的方法,进而设计了一个反Q滤波器。该方法利用反射地震资料的高阶统计量进行子波估计,并利用所估计子波实现频谱校正。我们利用合成数据实验给出了质心频移法与频谱比法这两种常用的Q值估计方法在不同参数设置下的性能。人工合成数据和实际数据处理表明,利用本文提出的方法进行频谱校正后,可以得到可靠的Q值估计。经过反Q滤波,地震数据的高频部分得到了有效地恢复。     

High‐definition frequency decomposition

Spectral decomposition is a widely used technique in analysis and interpretation of seismic data. According to the uncertainty principle, there exists a lower bound for the joint time–frequency resolution of seismic signals. The highest temporal resolution is achieved by a matching pursuit approach which uses waveforms from a dictionary of functions (atoms). This method, in its pure mathematical form can result in atoms whose shape and phase have no relation to the seismic trace. The high‐definition frequency decomposition algorithm presented in this paper interleaves iterations of atom matching and optimization. It divides the seismic trace into independent sections delineated by envelope troughs, and simultaneously matches atoms to all peaks. Co‐optimization of overlapping atoms ensures that the effects of interference between them are minimized. Finally, a second atom matching and optimization phase is performed in order to minimize the difference between the original and the reconstructed trace. The fully reconstructed traces can be used as inputs for a frequency‐based reconstruction and red–green–blue colour blending. Comparison with the results of the original matching pursuit frequency decomposition illustrates that high‐definition frequency decomposition based colour blends provide a very high temporal resolution, even in the low‐energy parts of the seismic data, enabling a precise analysis of geometrical variations of geological features.     

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.