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1.
Regularization methods are used to recover a unique and stable solution in ill-posed geophysical inverse problems. Due to the connection of homogeneous operators that arise in many geophysical inverse problems to the Fourier basis, for these operators classical regularization methods possess some limitations that one may try to circumvent by wavelet techniques.
In this paper, we introduce a two-step wavelet-based regularization method that combines classical regularization methods with wavelet transform to solve ill-posed linear inverse problems in geophysics. The power of the two-step wavelet-based regularization for linear inversion is twofold. First, regularization parameter choice is straightforward; it is obtained from a priori estimate of data variance. Second, in two-step wavelet-based regularization the basis can simultaneously diagonalize both the operator and the prior information about the model to be recovered. The latter is performed by wavelet-vaguelette decomposition using orthogonal symmetric fractional B-spline wavelets.
In the two-step wavelet-based regularization method, at the first step where fully classical tools are used, data is inverted for the Moore-Penrose solution of the problem, which is subsequently used as a preliminary input model for the second step. Also in this step, a model-independent estimate of data variance is made using nonparametric estimation and L-curve analysis. At the second step, wavelet-based regularization is used to partially recover the smoothness properties of the exact model from the oscillatory preliminary model.
We illustrated the efficiency of the method by applying on a synthetic vertical seismic profiling data. The results indicate that a simple non-linear operation of weighting and thresholding of wavelet coefficients can consistently outperform classical linear inverse methods. 相似文献
In this paper, we introduce a two-step wavelet-based regularization method that combines classical regularization methods with wavelet transform to solve ill-posed linear inverse problems in geophysics. The power of the two-step wavelet-based regularization for linear inversion is twofold. First, regularization parameter choice is straightforward; it is obtained from a priori estimate of data variance. Second, in two-step wavelet-based regularization the basis can simultaneously diagonalize both the operator and the prior information about the model to be recovered. The latter is performed by wavelet-vaguelette decomposition using orthogonal symmetric fractional B-spline wavelets.
In the two-step wavelet-based regularization method, at the first step where fully classical tools are used, data is inverted for the Moore-Penrose solution of the problem, which is subsequently used as a preliminary input model for the second step. Also in this step, a model-independent estimate of data variance is made using nonparametric estimation and L-curve analysis. At the second step, wavelet-based regularization is used to partially recover the smoothness properties of the exact model from the oscillatory preliminary model.
We illustrated the efficiency of the method by applying on a synthetic vertical seismic profiling data. The results indicate that a simple non-linear operation of weighting and thresholding of wavelet coefficients can consistently outperform classical linear inverse methods. 相似文献
2.
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. 相似文献
3.
A data analysis method is proposed to cluster and explore spatio-temporal characteristics of the 22 years of precipitation data (1982–2003) for Taiwan. The wavelet transform self-organizing map (WTSOM) framework combines the wavelet transform (WT) and a self-organizing map (SOM) neural network. WT is used to extract dynamic and multiscale features of the non-stationary precipitation time-series, and SOM is applied to objectively identify spatially homogeneous clusters on the high-dimensional wavelet-transformed feature space. Haar and Morlet wavelets are applied in the data preprocessing stage to preserve the desired characteristics of the precipitation data. A two-level SOM neural network is applied to identify clusters in the wavelet space in the clustering stage. The performance of clustering is evaluated using silhouette coefficients. The results indicate that singularities or sharp transitions are more significant than changes in the periodicity or data structure in the spatial–temporal precipitation data. The WTSOM results show that six clusters are optimal for both Haar and Morlet wavelet functions, but their corresponding geographic locations are different. The geographic locations of clusters based on the Haar wavelet, which captures the occurrence of extreme hydrological events, appear in blocks while those classified by the Morlet wavelet, which indicates periodicity changes and describes fine structures, appear in strips that cross the island of Taiwan. Principal component analysis is applied to the precipitation data of each cluster. The first principal components explain 62–90% of the total variation of data. Characteristics of precipitation data for each cluster are explored using scalogram analysis. The results show that both extreme hydrological events and periodicity changes appear in the spatial and temporal precipitation data but with different characteristics for each cluster. Recognizing homogeneous hydrologic regions and identifying the associated precipitation characteristics improves the efficiency of water resources management in adapting to climate change, preventing the degradation of the water environment, and reducing the impact of climate-induced disasters. Measures for countering the stress of precipitation variation for water resources management are provided. 相似文献
4.
Weak Seismic Signal Extraction Based on the Curvelet Transform 总被引：1，自引：1，他引：0
Seismic signal denoising is a key step in seismic data processing. Airgun signals are easy to be interfered with by noise when it travels a long distance due to the weak energy of active source signal of the airgun. Aiming to solve this problem, and considering that the conventional Curvelet transform threshold processing method does not use the seismic spectrum information, we independently process the Curvelet scale layer corresponding to valid data based on the characteristics of the Curvelet transform of multi-scale, multi-direction and capable of expressing the sparse seismic signals in order to fully excavate the information features. Combined with the Curvelet adaptive threshold denoising the algorithm, we apply the Curvelet transform to denoising seismic signals while retaining the weak information in the signal as much as possible. The simulation experiments show that the improved threshold denoising method based on Curvelet transform is superior to the frequency domain filtering, wavelet denoising and traditional Curvelet denoising method in detailed information extraction and signal denoising of low SNR signals. The calculation accuracy of the relative wave velocity variation of underground medium is improved. 相似文献
5.
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
6.
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． 相似文献
7.
简要介绍当前国内外关于天然地震与爆破、塌陷等非天然地震特征研究及事件类型识别的进展。对各类事件的定义及主要波形特征进行简要综述,重点介绍了事件类型判定的各类识别方法。与自然界天然地震不同,非天然地震由人工干预或人类活动间接引发。爆破是炸药在爆炸瞬间能量迅速释放,部分能量以地震波形式向外传播,引起地表振动而产生破坏效应的一种地震;塌陷是由于岩层崩塌陷落而形成的地震。虽然在地震台网记录到的天然地震与爆破、塌陷的波形存在一定的共性特征,但由于震源类型、波的传播路径、震源深度等不同,各类事件的波形记录在P波初动、P波与S波最大振幅比、持续时间、震相、短周期面波发育情况、发震时刻、空间位置分布以及频谱特征等方面差异明显。目前主要有两类方法来识别地震与爆破、塌陷等非天然事件。一类为直接基于波形在信号、数据方面的特征,通过定性分析来进行事件类型判定,如波形时频分析对比法、小波变换、相关系数等;另一类为统计学领域诸如模式识别等算法,利用统计算法综合考虑多个事件特征判据的定量判定阀值来实现地震与爆破、塌陷事件类型的识别,如最小距离法、改进的连续亨明方法、Fisher方法、逐步代价最小决策法、支持向量机、前馈神经网络等。两类方法本质上均为提取有效特征判据,即对数据进行降维使用,未将事件记录的全部信息用于事件判定。因此,有必要使用一种可从全部事件记录中自动提取各类信息并可组合底层特征的算法来对各类事件进行判断识别。 相似文献
8.
Klaus Bauer Ben Norden Alexandra Ivanova Manfred Stiller Charlotte M. Krawczyk 《Geophysical Prospecting》2020,68(2):466-482
At the geothermal test site near Groß Schönebeck (NE German Basin), a new 3D seismic reflection survey was conducted to study geothermal target layers at around 4 km depth and 150°C. We present a workflow for seismic facies classification and modelling which is applied to a prospective sandstone horizon within the Rotliegend formation. Signal attributes are calculated along the horizon using the continuous Morlet wavelet transform. We use a short mother wavelet to allow for the temporal resolution of the relatively short reflection signals to be analysed. Time-frequency domain data patterns form the input of a neural network clustering using self-organizing maps. Neural model patterns are adopted during iterative learning to simulate the information inherent in the input data. After training we determine a gradient function across the self-organizing maps and apply an image processing technique called watershed segmentation. The result is a pattern clustering based on similarities in wavelet transform characteristics. Three different types of wavelet transform patterns were found for the sandstone horizon. We apply seismic waveform modelling to improve the understanding of the classification results. The modelling tests indicate that thickness variations have a much stronger influence on the wavelet transform response of the sandstone horizon compared with reasonable variations of seismic attenuation. In our interpretation, the assumed thickness variations could be a result of variable paleo-topography during deposition of predominantly fluvial sediments. A distinct seismic facies distribution is interpreted as a system of thicker paleo-channels deposited within a deepened landscape. The results provide constraints for the ongoing development of the geothermal test site. 相似文献
9.
Deconvolution is an essential step for high-resolution imaging in seismic data processing. The frequency and phase of the seismic wavelet change through time during wave propagation as a consequence of seismic absorption. Therefore, wavelet estimation is the most vital step of deconvolution, which plays the main role in seismic processing and inversion. Gabor deconvolution is an effective method to eliminate attenuation effects. Since Gabor transform does not prepare the information about the phase, minimum-phase assumption is usually supposed to estimate the phase of the wavelet. This manner does not return the optimum response where the source wavelet would be dominantly a mixed phase. We used the kurtosis maximization algorithm to estimate the phase of the wavelet. First, we removed the attenuation effect in the Gabor domain and computed the amplitude spectrum of the source wavelet; then, we rotated the seismic trace with a constant phase to reach the maximum kurtosis. This procedure was repeated in moving windows to obtain the time-varying phase changes. After that, the propagating wavelet was generated to solve the inversion problem of the convolutional model. We showed that the assumption of minimum phase does not reflect a suitable response in the case of mixed-phase wavelets. Application of this algorithm on synthetic and real data shows that subtle reflectivity information could be recovered and vertical seismic resolution is significantly improved. 相似文献
10.
Stockwell等人提出的S变换虽然与Fourier谱能保持直接联系，然而，由于S变换中的基本小波不适用于地震资料处理. 为此本文采用两个步骤对S变换加以推广，得到两种新变换（统称为广义S变换）. 首先， 用带有4个待定参数的调幅简谐波来代替S变换中的基本小波,定义广义S变换1，给出对应的逆变换；然后，以第一步中的基本小波的线性组合为新的基本小波，定义广义S变换2，并构造其逆变换公式. 最后，分别使用S变换及广义S变换对几种典型的薄互层模型进行分析计算. 结果表明，后者比前者有更强的探测能力， 后者可准确地确定厚度为1/8波长的薄互层中波阻抗界面位置，但前者却不能. 文中还用实际资料处理的结果，证明了广义S变换方法的有效性. 相似文献
11.
子波相位不准对反演结果的影响(英文) 总被引：5，自引：1，他引：4
本文重点讨论在振幅谱估计准确的情况下,采用不同相位谱子波作为实际估计子波进行线性最小二乘反演,并对结果进行分析。除子波相位外,所有其它影响反演结果的因素均忽略。稀疏反射系数模型(块状波阻抗模型)反演结果表明:(1)使用不同相位谱子波进行反演,其反演结果合成的记录与原始记录都非常匹配,但反演的反射系数和声波阻抗结果与真实模型有差异;(2)反演结果的可靠程度主要与不同相位子波z变换的根的分布有关,当估计子波与真实子波Z变换的根的分布仅在单位圆附近有差异时,反演的反射系数和声波阻抗与真实模型很接近;(3)尽管反演前后地震记录都匹配了,并且评价反演结果好坏的柯西准则或改进柯西准则(反演参数没有进行自适应处理)已经达到了最优(最小),但反演结果与真实模型仍存在较大差异。最后,针对子波相位估计不准可能导致反演效果较差这个问题,我们提出采用求L1范数、丰度、变分、柯西准则(反演参数进行了自适应处理)或/和改进柯西准则(反演参数进行了自适应处理)的最优值或次优值作为评价准则的一种解决办法,理论上得到了好的效果。 相似文献
12.
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. 相似文献
13.
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． 相似文献
14.
Saman Yaghmaei-Sabegh 《Journal of Seismology》2010,14(4):715-726
This paper implements a quantitative approach to detect pulse-like ground motions based on continues wavelet transform, which
is able to clearly identify sudden jumps in time history of earthquake records by considering contribution of different levels
of frequency. These analyses were performed on a set of time series records obtained in near-fault regions of Iran. Pulse-like
ground motions frequently resulted from directivity effects in near-fault area and are of interest in the field of seismology
and also earthquake engineering for seismic performance evaluation of structures. The results of this study basically help
us to establish a suitable platform for selecting pulse-like records, while performance evaluation of structure in near-fault
area will need to account. The period of velocity pulses as a key parameter that significantly affects structural response
is simply determined by using a pseudo-period of the mother wavelets. In addition, the efficiency of different types of mother
wavelets on classification performance and the features of detected pulse are investigated by applying seven different kinds
of mother wavelets. The analyses indicate that the selection of most appropriate mother wavelet plays a significant role in
effective extraction of ground motion features and consequently in estimation of velocity pulse period. As a result, the user
should be aware of what is selected as a mother wavelet in the analysis. The comparisons given here among different mother
wavelets also show the better performance of BiorSpline (bior1.3) basis from biorthognal wavelet families for the preferred
purpose in this paper. 相似文献
15.
选用2010年2月—2016年12月发生在北京顺义及河北三河等首都圈邻近区域的117个地震事件(包括54个天然地震事件和63个非天然地震事件——爆炸事件)作为研究对象,利用文章所提出的多尺度注意残差网络对其中的天然地震事件和爆炸事件波形进行二分类。首先,对原始地震波形进行简单预处理并截取成相同长度的地震时序数据,直接将其作为网络模型的输入;其次,选用含有残差模块的深度神经网络作为基础网络,利用深度神经网络对特征的自动提取能力,省略了传统波形分类需要提前提取时域波形的特征作为分类算法输入的步骤;然后,融合通道注意力机制(ECA)并对其进行改进,将空间维度的信息融入通道信息,优化了网络对关键信息的关注,更好地聚焦重要特征;最后,使用空间金字塔池化代替最大池化进行多尺度特征融合,得到更多的特征信息,构成多尺度注意残差网络。实验结果表明,最高分类准确率为97.11%,平均分类准确率为96.53%,证明了多尺度注意残差网络在地震波形分类任务中的有效性,为震源类型识别工作提供了一种新的方法。 相似文献
16.
对于陆相沉积环境下的复杂隐蔽岩性储层,由于观测信息不准确,如信息重叠、信息缺失和噪音污染,以及岩石物理关系模糊等原因,储层横向预测存在不惟一性、不稳定性和不确定性.基于线性假定的常规储层横向预测技术已不适用于复杂隐蔽岩性储层的勘探.本文采用一种非线性储层岩性物性褶积模型,建立波阻抗与孔隙度/泥质含量的函数关系;通过多级结构分解和双向边沿子波检测来刻画复杂岩石物理关系;通过Caianiello褶积神经网络实现确定性反演、统计反演和非线性理论三者有机结合;最后联合应用基于逆算子的反演方法和基于正算子的重建算法实现了综合地质、测井和地震波阻抗信息进行高分辨率储层物性参数反演.非线性储层物性参数反演采用多井约束机制和分频反演方式,在陆相和近海油气勘探资料的实际应用中,取得了明显应用效果. 相似文献
17.
This paper presents an analytical study of the complete transform of improved Gabor wavelets (IGWs), and discusses its application to the processing and interpretation of seismic signals. The complete Gabor wavelet transform has the following properties. First, unlike the conventional transform, the improved Gabor wavelet transform (IGWT) maps time domain signals to the time-frequency domain instead of the time-scale domain. Second, the IGW’s dominant frequency is fixed, so the transform can perform signal frequency division, where the dominant frequency components of the extracted sub-band signal carry essentially the same information as the corresponding components of the original signal, and the subband signal bandwidth can be regulated effectively by the transform’s resolution factor. Third, a time-frequency filter consisting of an IGWT and its inverse transform can accurately locate target areas in the time-frequency field and perform filtering in a given time-frequency range. The complete IGW transform’s properties are investigated using simulation experiments and test cases, showing positive results for seismic signal processing and interpretation, such as enhancing seismic signal resolution, permitting signal frequency division, and allowing small faults to be identified. 相似文献
18.
小波变换与地震信号特征分析 总被引：6，自引：0，他引：6
地震波的瞬时信号,如瞬时振幅、瞬时频率及瞬时相位等,是研究地球介质的重要参数。根据小波定义,对Morlet 小波进行了修正,并对修正后的小波形态进行了深入讨论。理论分析表明,小波变换效果受到整形参数、小波长度、中心频率、频带宽度及小波个数等参数的制约,特别是整形参数与小波中心频率及频带之间关系对小波变换起到决定性作用。在地震波信号的实际处理中,可选取恰当的整形参数,同时采用合适的小波中心频率以避免小波变换对信号产生的遗漏和冗余。文中给出了实际地震记录处理的示例。 相似文献
19.
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
20.
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