共查询到20条相似文献，搜索用时 31 毫秒
1.
The experimental variogram computed in the usual way by the method of moments and the Haar wavelet transform are similar in that they filter data and yield informative summaries that may be interpreted. The variogram filters out constant values; wavelets can filter variation at several spatial scales and thereby provide a richer repertoire for analysis and demand no assumptions other than that of finite variance. This paper compares the two functions, identifying that part of the Haar wavelet transform that gives it its advantages. It goes on to show that the generalized variogram of order k=1, 2, and 3 filters linear, quadratic, and cubic polynomials from the data, respectively, which correspond with more complex wavelets in Daubechies's family. The additional filter coefficients of the latter can reveal features of the data that are not evident in its usual form. Three examples in which data recorded at regular intervals on transects are analyzed illustrate the extended form of the variogram. The apparent periodicity of gilgais in Australia seems to be accentuated as filter coefficients are added, but otherwise the analysis provides no new insight. Analysis of hyerpsectral data with a strong linear trend showed that the wavelet-based variograms filtered it out. Adding filter coefficients in the analysis of the topsoil across the Jurassic scarplands of England changed the upper bound of the variogram; it then resembled the within-class variogram computed by the method of moments. To elucidate these results, we simulated several series of data to represent a random process with values fluctuating about a mean, data with long-range linear trend, data with local trend, and data with stepped transitions. The results suggest that the wavelet variogram can filter out the effects of long-range trend, but not local trend, and of transitions from one class to another, as across boundaries. 相似文献
2.
在地震记录中,随机噪声严重影响了有效信号的提取,为此必须进行消噪处理。这里首先使用小波包变换对不同频段的信号进行精细分离,有效信号和噪声经小波包分解后,其小波包系数将表现出不同特性,然后根据这种不同特性进行去噪处理,对小波包分析法处理后的剩余地震信号再进行KL(Karhunen-Loeve)变换,提取相关有效信号,最后对提取的有效信号进行中值滤波处理,进一步去除剩余噪声。经合成地震剖面和实际地震剖面处理实验证明,小波包分析、KL变换和中值滤波联合去噪方法,能有效地消除较强的随机噪声,提高地震剖面信噪比和分辨率。 相似文献
3.
This paper describes how the continuous wavelet transform is used to filter multiple waveforms in both time and frequency domains. It is well suited to process the stationary signals, and it shows the signal in both time and frequency scales. This new approach was tested first on synthetic data and then on real data. The results obtained on both cases were good. The method consists of identifying the multiples on which we apply a normal move out using the multiple velocity law. The multiples will be aligned and the primary reflections will not be aligned. This operation allows locating the multiples in the time-scale domain. We compute the continuous wavelet transform (CWT for short) in order to focus on the patterns relative to seismic events. To filter the multiples, we define a zone with frequency and time bounds. These bounds are deduced from the projection of the seismic trace. Then an automatic mask is applied to the pattern to be isolated. Filtering in time–frequency domain is done by keeping only the wavelet coefficients that are outside the mask and assigning zero to the coefficients larger than a threshold amplitude inside the defined zone. The mask shape does not matter, which is not the case in classical filtering, where both the window size and shape play a key role. The mask is defined from three parameters: time, frequency, and the wavelet coefficients. To go back to the time domain, one has to compute the wavelet transform inverse of the trace. This procedure is repeated for all traces. To reset the traces to their initial positions, we apply the dynamic correction inverse with the same velocity law as the multiples. It turns out that the attenuation of multiples by the CWT works fine, in particular, the two identified multiples were quasi eliminated (Fig. 10). 相似文献
4.
根据国内外广泛采用的波阻抗随机反演理论,提出了多道小波波阻抗反演方法,消除了噪音对反演结果的影响。针对地震剖面上不同频带和时段上有不同的信噪比,以及相邻地震道反射波有效成分在波形和能量上有较强的相关性特点,运用多道记录同时进行波阻抗反演,在迭代过程中将实际记录与模型合成记录的残差道进行小波分解,形成残差道分频小波剖面,然后利用Ｋ－Ｌ变换提取分频剖面中的相干部分用于波阻抗变化量的计算,从而避免了噪音参与波阻抗反演。展示了理论模型与实际应用的例子。 相似文献
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提高地震资料的信噪比是地震资料处理的关键,叠前去噪是进行噪声压制的主要处理技术。小波变换方法由于具有同时在时间域与频率域分析的特点,在信号的分析处理方面得到广泛的应用;笔者采用小波变换把叠前地震数据分为不同的频段,并对包含干扰波的频段采用中值滤波消除干扰,再运用小波反变换来重构去噪后的记录;该技术不仅实现了噪声压制,还达到了保持宽频带的目的,应用于实际资料处理中,取得了很好的去噪效果。 相似文献
7.
Wavelet transforms have been used widely to analyse environmental data. These data typically comprise a series of measurements
taken at regular intervals in time or space. The analysis offers a decomposition of the data that distinguishes components
at different spatial scales but also, unlike Fourier analysis, can resolve local intermittent features. Most wavelet methods
require the data to be sampled at regular intervals and little attention has been paid to developing methods for data that
are not. In this paper, we derive a discrete Haar wavelet transform for irregularly sampled data and show how the resulting
wavelet coefficients can be used to estimate contributions of variance. We discuss the interpretation of these statistics
using data on apparent soil electrical conductivity of soil measured across a landscape as an example. 相似文献
8.
面波以低频强能量为特征,数据处理中常用的面波衰减技术有:频率滤波、F-K滤波和速度滤波等.由于面波特殊的频散现象,使得上述方法的应用效果受到一定的影响.基于面波的特征随炮检距变化这一特点,提出一种时频～炮检距域面波衰减方法:①对单炮记录中的面波区域做Fourier变换或时频分析,了解面波频率随时间和炮检距的变化规律;②... 相似文献
9.
The Italian catalogue contains many earthquakes of moderate to high epicentral intensity which are located in areas of low seismicity and near big cities. Some of them have been inserted in the catalogue after one historical record only. This study investigates many such events in the 1000–1690 time-window showing that a great number of them are fake. Starting by an operational definition of ‘fake quake’, this paper shows the procedures adopted, and the main results which contribute in a significant way to the reassessment of seismicity and seismic hazard. 相似文献
10.
小波变换是近年来兴起的新的数学分支,并广泛应用于地震勘探领域。利用小波变换良好的局部化时频特性,可以很方便地将地震记录分解成不同的频道,分解后的各频道存在内在的分形规律。小波变换应用于煤田地震资料,提高其分辨率,具有重要意义 相似文献
11.
This paper treats the upscaling of the absolute permeability in a heterogeneous reservoir. By replacing the fine scale permeability tensor with an upscaled, or effective permeability tensor, a modelling error is introduced. An a posteriori error estimate on this modelling error is formulated and tested. An implementation of the theory, based on domain decomposition coupled with a hierarchical representation of the absolute permeability field, is given. As hierarchical basis functions we have chosen the Haar system, which leads to a wavelet representation of the permeability. The wavelet representation offers a natural upscaling technique which resembles the highcut filters commonly used in signal analysis. This procedure represents an adaptive upscaling method. The numerical results show that this method conserves both the dissipation and the mean velocity in the problem fairly well. The a posteriori error estimate on the modelling error coupled with domain decomposition methods constitutes a powerful modelling tool. 相似文献
12.
频率波数域预测和减去法压制多次波 总被引：3，自引：1，他引：3
研究了压制与海面有关的地震勘探多次反射波的两种方法。两种方法均以波动方程为基础。当地震子波已知时，可在频率波数域中通过子波反褶积方法消除与海水表面有关的多次波；在未知子波的情况下，可依据消除后波场能量最小为准则，求出一滤波因子，用它去标定估计的多次波，然后从地震记录中减去预测的多次波，达到压制它们的目的。为了降低维数，x、y的二维空间坐标用柱坐标的径向距离代替，其波数通过汉克尔变换求得。 相似文献
13.
地震数据本质上是非平稳的,如何解决复杂非平稳地震波场的数据缺失问题是地震勘探数据处理的重要环节之一。预测滤波器在地震数据处理和分析中具有重要的作用,该技术可以有效地解决地震数据缺失问题,但传统的平稳预测滤波方法无法很好地适应地震数据的非平稳特征;因此,开发高效的复杂地震波场自适应预测插值方法具有重要的工业价值。本文将预测滤波器加入"流处理"的概念,滤波器系数随着地震数据的变化同时更新,此计算过程仅需矢量点积运算,能够提高计算效率并降低内存空间;并以此为基础开发基于流预测滤波的地震数据插值方法。利用多次波的动力学信息,通过互相关技术构建虚拟一次波,有效地解决了缺失数据位置滤波系数估计不准的问题,为插值过程提供了更为合理的滤波器估计,更好地解决了非平稳地震数据的重建问题。对Sigsbee 2B模型和实际数据的测试结果表明,该方法可以合理地针对复杂地震信息完成缺失数据的重建。 相似文献
14.
Estimating observation error covariance matrix of seismic data from a perspective of image denoising
Estimating observation error covariance matrix properly is a key step towards successful seismic history matching. Typically, observation errors of seismic data are spatially correlated; therefore, the observation error covariance matrix is non-diagonal. Estimating such a non-diagonal covariance matrix is the focus of the current study. We decompose the estimation into two steps: (1) estimate observation errors and (2) construct covariance matrix based on the estimated observation errors. Our focus is on step (1), whereas at step (2) we use a procedure similar to that in Aanonsen et al. 2003. In Aanonsen et al. 2003, step (1) is carried out using a local moving average algorithm. By treating seismic data as an image, this algorithm can be interpreted as a discrete convolution between an image and a rectangular window function. Following the perspective of image processing, we consider three types of image denoising methods, namely, local moving average with different window functions (as an extension of the method in Aanonsen et al. 2003), non-local means denoising and wavelet denoising. The performance of these three algorithms is compared using both synthetic and field seismic data. It is found that, in our investigated cases, the wavelet denoising method leads to the best performance in most of the time. 相似文献
15.
V. I. Znak 《Mathematical Geology》2005,37(2):207-221
Median filters are nonlinear and a theoretical analysis of their behavior is very difficult and so are rarely used for the processing of seismic data. However, they are able to preserve steps, sharp discontinuities and edges that are lost using most other standard filters. As seismic data are mostly harmonic or frequency modulated signals in the frequency range 1 to 10 Hz, the median filter must be adapted so as to suppress noise but not unduly distort the signal. This can be accomplished by using a median filter whose length is n times that of signal period where n is even. By use of weighted-order statistics, samples of the signals closest in phase can be obtained. To illustrate the method, a signal from a frequency band of 6.3–7.5 Hz was processed and the quality of the signal enhanced two fold over the quality of the signal without processing. 相似文献
16.
The objective of this study is to find the order and coefficients of non-low-phase causal filters for ARMA (auto regressive moving average) filter model, using the Kurtosis minimization criterion. This method is based on the Kurtosis calculation of the treated sample at the input level and its identification at the output of the ARMA model. For this purpose, the order and coefficients of the AR (auto regressive) part are identified using the Yule-Walker algorithm at order two and then extended to order four. To obtain the MA (moving average) part, the AR components are calculated at first from the ARMA filter by deconvolution. Then, spectrally equivalent and minimum phase (SEMP) MA filter is identified using the Durbin algorithm at second and fourth order. Finally, the correct filter is found when the Kurtosis value of the output ARMA filter reconstituted is the closest to the Kurtosis of introduced signal. The proposed method is then tested on simulated processes and applied to real seismic data to perform blind deconvolution and obtain the reflectivity coefficients of subsoil studied. 相似文献
17.
The spatial filtering techniques that are used for the analysis and interpretation of exploration geochemical data to define regional distribution patterns or to outline anomalous areas are, in most cases, based on non-robust statistical methods. The performance of these techniques is heavily influenced by the presence of outliers that commonly exist in the data. This study describes a number of filtering techniques motivated by the development of exploratory data analysis (EDA) and robust statistical procedures. These are the median filter (MF) and the adaptive trimmed mean filter (ATM) for the smoothing of regional geochemical data to reduce spurious variations; two new filters, the fence filter (FF) and the notch filter (NF), have been developed to define geochemical anomalies.The application of the spatial filtering techniques is illustrated by Zn data from approximately 3100 stream sediment samples taken in a regional geochemical survey over 25,000 km2 of the western margin of the São Francisco Basin, Brazil. Regional distribution patterns for Zn obtained by the MF and ATM filters are clearly related to known stratigraphic units. Anomaly filtering using the FF and NF has delineated most known base metal and gold occurrences, as well as a number of anomalies located in geologically favourable environments but unrelated to any known mineralization. The two anomaly filters have, for the most part, defined the same anomalies in the study area but only the NF highlights the anomaly associated with the important Morro Agudo Pb-Zn deposit, which is too subtle to be immediately apparent in the unprocessed data. 相似文献
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Abdelkader Benaïssa Zahia Benaïssa Tahar Aïfa Amar Boudella 《Swiss Journal of Geoscience》2009,102(2):297-306
To improve the signal to noise ratio of the vertical seismic profile recordings, we used a filtering method based on pattern
recognition. It consists in recognizing along the seismic trace, corresponding to the arrivals of various events, the shape
of the P wavelet considered as the training signal. This recognition is made of projections which retain only the signals
similar in shape to the P wavelet, the others being attenuated according to their degree of resemblance to the training wavelet.
The study undertaken on synthetic and real data shows that this method acts as an effective filter. However, it still depends
on a training signal that must be well defined and identifiable. 相似文献