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1.
Wavelet‐based cepstrum decomposition of seismic data and its application in hydrocarbon detection 
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下载免费PDF全文 Ya‐juan Xue Jun‐xing Cao Ren‐fei Tian Hao‐kun Du Yao Yao 《Geophysical Prospecting》2016,64(6):1441-1453
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. 相似文献
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基于小波分析的结构损伤检测研究进展 总被引：18，自引：1，他引：17
近10几年来,在土木和机械领域结构损伤识别方法已引起不同领域的相关学者的极大研究兴趣。小波分析是一种新的数学分析和信号处理工具,可以对非稳态信号进行详细的时频分析,是传统傅里叶分析所不能及的,已广泛应用于土木、机械和航空工程领域中,特别是在结构损伤识别和健康监测中的应用尤为突出。本文回顾和总结了小波分析理论及其在结构损伤识别、损伤定位和损伤程度确定中的应用,对今后的研究进行了讨论和展望。 相似文献
3.
Estimation of structural damage from a known increase in the fundamental period of a structure after an earthquake or prediction of degradation of stiffness and strength for a known damage requires reliable correlations between these response functionals. This study proposes a modified Clough–Johnston single‐degree‐of‐freedom oscillator to establish these correlations in the case of a simple elasto‐plastic oscillator. It is assumed that the proposed oscillator closely models the response of a given multi‐degree‐of‐freedom system in its fundamental mode throughout the duration of the excitation. The proposed model considers the yield displacement level and ductility supply ratio‐related parameter as two input parameters which must be estimated over a narrow range of ductility supply ratio from a frequency degradation curve. This curve is to be identified from a set of recorded excitation and response time‐histories. Useful correlations of strength and stiffness degradation with damage have been obtained wherein a simple damage index based on maximum and yield displacements and ductility supply ratio has been considered. As an application, the proposed model has been used to demonstrate that ignoring the effects of aftershocks in the case of impulsive ground motions may lead to unsafe designs. Copyright © 2001 John Wiley & Sons, Ltd. 相似文献
4.
In this paper, a new approach to structural damage detection is presented using mode shape difference between the reference and damage states. In order to capture and display the signal of damage, wavelet transformation is performed upon the mode shape difference function. Results show that this presentation of signal is effective for damage detection. Furthermore, practical aspects of damage identification are investigated, including understanding and using the frequency contents of the mode shape difference function, the mother wavelet function and the resulting wavelet coefficients due to the band‐limited filtering of wavelet transformation. This proposition is experimented. Results are assertive of the proposed concept. Copyright © 2007 John Wiley & Sons, Ltd. 相似文献
5.
Sayed Hesammoddin Kazemeini Christopher Juhlin Kim Zinck-Jørgensen Ben Norden 《Geophysical Prospecting》2009,57(1):111-123
Conventional seismic data are band limited and therefore, provide limited geological information. Every method that can push the limits is desirable for seismic data analysis. Recently, time‐frequency decomposition methods are being used to quickly extract geological information from seismic data and, especially, for revealing frequency‐dependent amplitude anomalies. Higher frequency resolution at lower frequencies and higher temporal resolution at higher frequencies are the objectives for different time‐frequency decomposition methods. Continuous wavelet transform techniques, which are the same as narrow‐band spectral analysis methods, provide frequency spectra with high temporal resolution without the windowing process associated with other techniques. Therefore, this technique can be used for analysing geological information associated with low and high frequencies that normally cannot be observed in conventional seismic data. In particular, the continuous wavelet transform is being used to detect thin sand bodies and also as a direct hydrocarbon indicator. This paper presents an application of the continuous wavelet transform method for the mapping of potential channel deposits, as well as remnant natural gas detection by mapping low‐frequency anomalies associated with the gas. The study was carried out at the experimental CO2 storage site at Ketzin, Germany (CO2SINK). Given that reservoir heterogeneity and faulting will have significant impact on the movement and storage of the injected CO2, our results are encouraging for monitoring the migration of CO2 at the site. Our study confirms the efficiency of the continuous wavelet transform decomposition method for the detection of frequency‐dependent anomalies that may be due to gas migration during and after the injection phase and in this way, it can be used for real‐time monitoring of the injected CO2 from both surface and borehole seismics. 相似文献
6.
Xuebing Zhang Cai Liu Xuan Feng Bonan Li Kexin Li Qin You 《Geophysical Prospecting》2020,68(2):371-381
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. 相似文献
7.
Feasibility of utilizing wavelet phase to map the CO2 plume at the Ketzin pilot site,Germany 下载免费PDF全文
下载免费PDF全文 Fei Huang Christopher Juhlin Li Han Daniel Sopher Monika Ivandic Ben Norden Wubing Deng Fengjiao Zhang Thomas Kempka Stefan Lüth 《Geophysical Prospecting》2017,65(2):523-543
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. 相似文献
8.
经验模分解及小波分析在结构损伤识别中的应用:试验研究 总被引：2，自引：0，他引：2
本文利用一个三层剪切型结构模型在各种激励下的振动台试验，研究经验模分解（empirical mode decomposition，EMD）和小波分析（wavelet analysis，WA）在结构损伤识别中的应用。研究针对结构刚度突然损失的损伤类型，并在试验中通过连接在模型两侧的弹簧的断裂来模拟。利用EMD和WA分析试验记录到的结构加速度信号来识别结构损伤发生的时刻和位置。试验结果表明，EMD和WA方法均可利用分解信号中的尖峰准确识别结构损伤发生的时刻，并利用信号尖峰在结构上的空间分布来确定损伤位置。研究表明，EMD和WA都是进行结构在线检测的良好方法。 相似文献
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The wavelet transform techniques were applied to compute time-frequency spectra, coherence and cross-covariance functions between complex-valued polar motion and atmospheric excitation functions. These wavelet transform approaches are based on the classical wavelet transform with Morlet wavelet and the harmonic wavelet transform. The computed coherence and cross-covariance functions enable comparison of polar motion and atmospheric excitation functions data in the chosen frequency band. In the study we concentrate on short period oscillations with periods ranging from several to about 250 days. The time lag functions show frequency dependent time lags corresponding to maxima of the modules of cross-covariance functions between the polar motion and atmospheric excitation functions. 相似文献
10.
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. 相似文献
11.
A damage detection method based on harmonic structural vibrations has been applied to reconstruct typical damage patterns of reinforced concrete beams and frames vibrating in three dimensions. It has been shown that comparison of harmonic vibrations of damaged and intact structures makes it possible to formulate optimization criterion which can be solved effectively for large number of unknowns. The application of combined genetic algorithms and Levenberg–Marquardt local search enabled to reconstruct vectors of distinct stiffness distributions containing up to 32 elements with stiffness loss as low as 5% and with accuracy of 1%. To test the algorithm in more realistic environment of practical data acquisition, measuring noise with various levels has been added to the analyzed signal. Such a method of damage detection can be quite effective during post-earthquake assessment of civil engineering structures or if one wants to control the stiffness loss of a reinforced concrete structure after it was accidentally overloaded. 相似文献
12.
为了准确刻画地震信号的局部层次结构,实现高效率的三维地震资料瞬时谱分解,检测油气储层的低频阴影,构造了广义S变换.广义S变换通过引入两个参数,改造S变换的小波函数,使其小波能根据信号处理的具体应用需要而调整.模型信号的仿真发现,广义S变换具有更加优越和灵活可调的时频聚集性能.文中分析了低频阴影的机理,并利用广义S变换对三维实际地震资料进行了瞬时谱分解,它不仅能检测油气储层的低频阴影,而且可以刻画油气储层的岩性边界和空间展布,减小油气储层检测的多解性. 相似文献
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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. 相似文献
15.
S. S. Law 《地震工程与工程振动(英文版)》2009,8(1):103-114
A new method is proposed to assess the condition of structures under unknown support excitation by simultaneously detecting local damage and identifying the support excitation from several structural dynamic responses. The support excitation acting on a structure is modeled by orthogonal polynomial approximations, and the sensitivities of structural dynamic response with respect to its physical parameters and orthogonal coeffi cients are derived. The identifi cation equation is based on Taylor’s fi rst orde... 相似文献
16.
Amir Semnani Liang Wang Mehdi Ostadhassan Majid Nabi-Bidhendi Babak Nadjar Araabi 《Geophysical Prospecting》2019,67(7):1701-1719
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. 相似文献
17.
在地震资料频谱分解中,采用匹配地震子波的物理小波,依据地震信号的特征,用振幅、能量衰减率、能量延迟时间及地震子波的中心频率等四类参数构造基本小波,把地震信号分解在小波域,高频分量能够得到精细的刻画.本文以物理小波变换为工具, 给出了该变换中的核函数的选择方法,进而提出了基于物理小波变换的频谱成像方法.我们将此方法用于海上某油田河流相储层的描述,并与常规软件中的小波变换频谱成像结果进行了对比, 结果表明,本文提出的方法更能精细地刻画地质事件. 相似文献
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利用频谱分解得到的频率能量数据体进行属性提取,是烃类检测的常用手段之一.同步挤压小波变换能够提供高分辨率的时频谱,具有较好的应用潜力.本文以同步挤压小波变换为基础,提出了一套烃类检测方法,包括低频阴影检测、流体流动性估计以及高频能量衰减等,通过自适应选取优势频段,实现了多属性联合高精度刻画烃类的分布范围.实际资料处理结果与现有钻井情况吻合,具有较好的实用性,实现了对储层位置的高精度描述,对指导油气田开发具有重要的理论意义和实用价值. 相似文献
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应用小波变换法可对不同频率成分进行分解的特性,选取db4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d 3~d 6部分异常显著;小波变换法对同震效应的识别、提取和去除具有良好效果,远震在小波细节分解d 3~d 5部分异常显著,近震在小波细节分解d 1~d 3、d 6~d 8部分明显;爆破信号在小波分解d 1~d 8部分中均清晰可见,异常的宽度和幅度变化不大。因此,应用小波分解法能有效识别无法判断的干扰源。 相似文献
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Mallat decomposition algorithm of wavelet packet transform can divide broader band into narrower ones with equal bandwidth and no overlapping each other. However, order by size of frequency within signal subspace is not in accordance with that of node label of decomposition tree. Therefore, it is not easy to determine frequency range of reconstructed signal from each node. In this paper, by analyzing the relationship between Mallat decomposition algorithm of wavelet packet transform and decomposition filter and setting operation rule of binary conversion of band labels into node labels, we find the corresponding relationships between nodes of decomposition tree and frequency bands of signal subspace. Then, the conclusion is verified by analog signals. Also, it shows that the ar- ranged rule of bands of signal subspace summarized in the paper is correct. 相似文献