共查询到20条相似文献，搜索用时 15 毫秒
1.
One of the main objectives of seismic digital processing is the improvement of the signal-to-noise ratio in the recorded data. Wiener filters have been successfully applied in this capacity, but alternate filtering devices also merit our attention. Two such systems are the matched filter and the output energy filter. The former is better known to geophysicists as the crosscorrelation filter, and has seen widespread use for the processing of vibratory source data, while the latter is. much less familiar in seismic work. The matched filter is designed such that ideally the presence of a given signal is indicated by a single large deflection in the output. The output energy filter ideally reveals the presence of such a signal by producing a longer burst of energy in the time interval where the signal occurs. The received seismic trace is assumed to be an additive mixture of signal and noise. The shape of the signal must be known in order to design the matched filter, but only the autocorrelation function of this signal need be known to obtain the output energy filter. The derivation of these filters differs according to whether the noise is white or colored. In the former case the noise autocorrelation function consists of only a single spike at lag zero, while in the latter the shape of this noise autocorrelation function is arbitrary. We propose a novel version of the matched filter. Its memory function is given by the minimum-delay wavelet whose autocorrelation function is computed from selected gates of an actual seismic trace. For this reason explicit knowledge of the signal shape is not required for its design; nevertheless, its performance level is not much below that achievable with ordinary matched filters. We call this new filter the “mini-matched” filter. With digital computation in mind, the design criteria are formulated and optimized with time as a discrete variable. We illustrate the techniques with simple numerical examples, and discuss many of the interesting properties that these filters exhibit. 相似文献
2.
S. M. DEREGOWSKI 《Geophysical Prospecting》1971,19(4):729-768
Two distinct filters are developed in the frequency domain which represent an attempt to increase the resolution of fine structure contained in the signal whilst keeping the expected filtered noise energy within reasonable bounds. A parameter termed the White Noise Amplification is defined and used together with a measure of the deconvolved pulse width in order to provide a more complete characterisation of the filters. Each of the two main types of frequency domain filters discussed varies in properties with respect to a single adjustable parameter. This may be contrasted with a time domain Wiener filter which in general has three variables: length, delay and an adjustable noise parameter or weight. The direct frequency domain analogue of the Wiener filter is termed a gamma-Fourier filter, and is shown to have properties which span the range from those of a spiking filter with zero least square error at one extreme, to those of a matched filter at the other extreme of its variable parameter's range. The second type of filter considered—termed the modulated Gaussian filter—is similarly shown to be a perfect spiking filter at one extreme of its parameter range, but adopts the properties of an output energy filter at the other extreme. 相似文献
3.
In this paper,we analyze the time series of site coordinates of 27 continuously monitoring GPS sites covered bythe Crustal Movement Observation Network of China over the whole country.The data are obtained in the periodfrom the beginning of the observation to the November of 2005.On the basis of data processing,we analyze thepower spectrum density of coordinate component noise at each site and calculate the spectral indexes manifestingthe noise property of each component.The spectral indexes indicate that for most sites,the noise of time series ofeach coordinate component can be addressed by the model of white noise flicker noise;and for a small amountof sites,it can be described by the model of white noise flicker noise random walk noise.We also quantita-tively estimate each noise component in the model by using the criterion of maximum likelihood estimation.Theresult shows that the white noise in the time series of GPS site coordinates does not constitute the main part ofnoise.Therefore,the error estimation of site movement parameters is usually too small,or too optimistic if weconsider the white noise only.Correspondingly,if this factor is not fully considered in explaining these movementparameters,it might mislead the readers. 相似文献
4.
分析了中国地壳运动观测网络在全国布设的27个GPS连续站开始运行以来至2005年11月的站坐标时间序列. 在对数据进行清理的基础上， 分析了各站坐标分量噪声的功率谱密度， 计算了表征各分量的噪声特性的谱指数. 谱指数显示， 大部分站的各坐标分量时间序列的噪声可以用白噪声+闪烁噪声的模型来描述， 少部分则可用白噪声+闪烁噪声+随机漫步噪声的模型来描述. 采用最大似然估计准则， 定量估计了模型中的各噪声分量. 结果表明， GPS站坐标时间序列中白噪声甚至不是噪声的主要成分. 因此， 仅顾及白噪声得到的测站运动参数的误差估计， 实际上是过高的， 或者说是过于乐观的. 相应地， 对这些运动参数作出解释时， 如果不充分考虑这一因素， 有可能会对读者产生误导. 相似文献
5.
RALPH A. WIGGINS 《Geophysical Prospecting》1967,15(2):288-296
The design of least-squares optimum filters is based upon minimizing a suitably defined error criterion. The expected value of this error is easily computable after the coefficients of the filter have been determined. When a particular filtering problem is specified, there are several parameters which are specifically not included in the optimization procedure. However, the magnitude of the expected error may be quite sensitive to these parameters. The examination of the relative values of the expected error for variations of these unspecified parameters may lead to a better definition of the filter problem. The parameters which are left unspecified by the general least-square filter definition include: 1. The addition of white noise to the signal autocorrelation to stabilize the filter behavior. 2. The specification of the shape of the desired output of the filter. 3. The specification of the lag between the desired output and the input. Examples are given showing the relationship between these parameters and the value of the expected error. 相似文献
6.
7.
A. N. BOWEN 《Geophysical Prospecting》1986,34(3):366-382
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. 相似文献
8.
反馈地震计自身的噪声输出决定了它的动态范围下限.反馈地震计的噪声主要由反馈环内有源器件产生.速度传感反馈地震计的环路参数和滤波类型将会影响环内不同位置的噪声输出传递函数.本文分析了4种一阶环路滤波器和零阶环路滤波器对环内噪声传递函数的影响,开环阻尼D1较小的一阶极点高通、一阶零点高通和双一阶环路滤波在抑制前向通道噪声输出方面具有潜力;一阶极点高通在抑制反向通道低端带外噪声输出方面有较好的性能. 相似文献
9.
基于ARMA模型非因果空间预测滤波(英文) 总被引：3，自引：1，他引：2
常规频域预测滤波方法是建立在自回归(autoregressive,AR)模型基础上的,这导致滤波过程中前后假设的不一致,即首先利用源噪声的假设计算误差剖面,却又将其作为可加噪声而从原始剖面中减去来得到有效信号。本文通过建立自回归-滑动平均(autoregres sive/moving-average,ARMA)模型,首先求解非因果预测误差滤波算子,然后利用自反褶积形式投影滤波过程估计可加噪声,进而达到去除随机噪声目的。此过程有效避免了基于AR模型产生的不一致性。在此基础上,将一维ARMA模型扩展到二维空间域,实现了基于二维ARMA模型频域非因果空间预测滤波在三维地震资料随机噪声衰减中的应用。模型试验与实际资料处理表明该方法在很好保留反射信息同时,压制随机噪声更加彻底,明显优于常规频域预测去噪方法。 相似文献
10.
Scaling geology and seismic deconvolution 总被引：1，自引：0，他引：1
The reflection seismic signal observed at the surface is the convolution of a wavelet with a reflection sequence representing the geology. Deconvolution of the observations without prior knowledge of the wavelet can be done by making assumptions about the statistics of the reflection sequence. In particular, the widely used prediction error filter is obtained by assuming that the power spectra of reflection sequences are white. However, evidence from well logs suggests that the power spectra are in fact proportional to a power of the frequency,f, that is, tof
, with equal approximately to 1.We have found a simple modification to the prediction error filter that markedly improves deconvolution for reflection sequences with such scaling behaviour. We have calculated three reflection sequences from sonic logs of a well off Newfoundland and two wells in Quebec. The three values of were 0.84, 0.95, and 1.20. We made artificial seismograms from the sequences and deconvolved them with the prediction error filter and our new filters. The errors between the known reflection sequences and the recovered ones for the prediction error filter were 20%, 26%, and 31%; for the new filters 0.5%, 2.0% and 0.5%. 相似文献
11.
Bias aware Kalman filters: Comparison and improvements 总被引：1，自引：0，他引：1
This paper reviews two different approaches that have been proposed to tackle the problems of model bias with the Kalman filter: the use of a colored noise model and the implementation of a separate bias filter. Both filters are implemented with and without feedback of the bias into the model state. The colored noise filter formulation is extended to correct both time correlated and uncorrelated model error components. A more stable version of the separate filter without feedback is presented. The filters are implemented in an ensemble framework using Latin hypercube sampling. The techniques are illustrated on a simple one-dimensional groundwater problem. The results show that the presented filters outperform the standard Kalman filter and that the implementations with bias feedback work in more general conditions than the implementations without feedback. 相似文献
12.
J. M. MENDEL 《Geophysical Prospecting》1977,25(4):692-698
Ott and Meder's prediction error filter can be rederived so that it correctly handles input noise vectors which are of smaller dimension than the state vector. The poor performance obtained by Ott and Meder for their example can be explained by means of the error covariance matrix for the prediction error filter. 相似文献
13.
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. 相似文献
14.
Robust f‐x projection filtering for simultaneous random and erratic seismic noise attenuation 
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下载免费PDF全文 Linear prediction filters are an effective tool for reducing random noise from seismic records. Unfortunately, the ability of prediction filters to enhance seismic records deteriorates when the data are contaminated by erratic noise. Erratic noise in this article designates non‐Gaussian noise that consists of large isolated events with known or unknown distribution. We propose a robust f‐x projection filtering scheme for simultaneous erratic noise and Gaussian random noise attenuation. Instead of adopting the ?2‐norm, as commonly used in the conventional design of f‐x filters, we utilize the hybrid ‐norm to penalize the energy of the additive noise. The estimation of the prediction error filter and the additive noise sequence are performed in an alternating fashion. First, the additive noise sequence is fixed, and the prediction error filter is estimated via the least‐squares solution of a system of linear equations. Then, the prediction error filter is fixed, and the additive noise sequence is estimated through a cost function containing a hybrid ‐norm that prevents erratic noise to influence the final solution. In other words, we proposed and designed a robust M‐estimate of a special autoregressive moving‐average model in the f‐x domain. Synthetic and field data examples are used to evaluate the performance of the proposed algorithm. 相似文献
15.
地震地面运动模型的研究 总被引：1，自引：0，他引：1
地震地面运动被模拟成均值为零的两次过滤Ｇａｕｓｓ白噪声随机过程。第一次过滤削减白噪声的高频含量;第二次过滤削减白噪声的低频含量。根据地震记录的功率谱,使用非线性函数的最小二乘法,确定了两次过滤Ｇａｕｓｓ白噪声随机过程的功率谱密度函数的参数。 相似文献
16.
为克服高分辨率模拟中,对于具有陡峭山峰及深谷的区域,存在不真实降雨场预报问题,本文引入数字滤波器及水平扩散方案分别对地形及计算噪音进行处理.滤波器由不同的一维高阶低通隐式正切滤波器耦合而成,能选择性地过滤由地形坡度所引起的不同尺度的噪音.水平扩散方案是将一个通量受地形限制的线性四阶单调水平扩散项加到预报方程,去控制由数值扩散、非线性不稳定及不连续物理过程等引起的小尺度噪音.试验结果表明：地形滤波处理及水平扩散方案能消除山区降雨预报量集中在山顶,而同时山谷和背风面又无雨的现象.因而,降雨分布更真实. 相似文献
17.
The theory of statistical communication provides an invaluable framework within which it is possible to formulate design criteria and actually obtain solutions for digital filters. These are then applicable in a wide range of geophysical problems. The basic model for the filtering process considered here consists of an input signal, a desired output signal, and an actual output signal. If one minimizes the energy or power existing in the difference between desired and actual filter outputs, it becomes possible to solve for the so-called optimum, or least squares filter, commonly known as the “Wiener” filter. In this paper we derive from basic principles the theory leading to such filters. The analysis is carried out in the time domain in discrete form. We propose a model of a seismic trace in terms of a statistical communication system. This model trace is the sum of a signal time series plus a noise time series. If we assume that estimates of the signal shape and of the noise autocorrelation are available, we may calculate Wiener filters which will attenuate the noise and sharpen the signal. The net result of these operations can then in general be expected to increase seismic resolution. We show a few numerical examples to illustrate the model's applicability to situations one might find in practice. 相似文献
18.
Microseismic events enhancement and detection in sensor arrays using autocorrelation‐based filtering 下载免费PDF全文
下载免费PDF全文 Entao Liu Lijun Zhu Anupama Govinda Raj James H. McClellan Abdullatif Al‐Shuhail SanLinn I. Kaka Naveed Iqbal 《Geophysical Prospecting》2017,65(6):1496-1509
Passive microseismic data are commonly buried in noise, which presents a significant challenge for signal detection and recovery. For recordings from a surface sensor array where each trace contains a time‐delayed arrival from the event, we propose an autocorrelation‐based stacking method that designs a denoising filter from all the traces, as well as a multi‐channel detection scheme. This approach circumvents the issue of time aligning the traces prior to stacking because every trace's autocorrelation is centred at zero in the lag domain. The effect of white noise is concentrated near zero lag; thus, the filter design requires a predictable adjustment of the zero‐lag value. Truncation of the autocorrelation is employed to smooth the impulse response of the denoising filter. In order to extend the applicability of the algorithm, we also propose a noise prewhitening scheme that addresses cases with coloured noise. The simplicity and robustness of this method are validated with synthetic and real seismic traces. 相似文献
19.
Conventional time-space domain and frequency-space domain prediction filtering methods assume that seismic data consists of two parts, signal and random noise. That is, the so-called additive noise model. However, when estimating random noise, it is assumed that random noise can be predicted from the seismic data by convolving with a prediction error filter. That is, the source-noise model. Model inconsistencies, before and after denoising, compromise the noise attenuation and signal-preservation performances of prediction filtering methods. Therefore, this study presents an inversion-based time-space domain random noise attenuation method to overcome the model inconsistencies. In this method, a prediction error filter (PEF), is first estimated from seismic data; the filter characterizes the predictability of the seismic data and adaptively describes the seismic data’s space structure. After calculating PEF, it can be applied as a regularized constraint in the inversion process for seismic signal from noisy data. Unlike conventional random noise attenuation methods, the proposed method solves a seismic data inversion problem using regularization constraint; this overcomes the model inconsistency of the prediction filtering method. The proposed method was tested on both synthetic and real seismic data, and results from the prediction filtering method and the proposed method are compared. The testing demonstrated that the proposed method suppresses noise effectively and provides better signal-preservation performance. 相似文献
20.
High resolution terrain models generated from widely available Interferometric Synthetic Aperture Radar (IfSAR) and digital photogrammetry are an exciting resource for geomorphological research. However, these data contain error, necessitating pre‐processing to improve their quality. We evaluate the ability of digital filters to improve topographic representation, using: (1) a Gaussian noise removal filter; (2) the proprietary filters commonly applied to these datasets; and (3) a terrain sensitive filter, similar to those applied to laser altimetry data. Topographic representation is assessed in terms of both absolute accuracy measured with reference to independent check data and derived geomorphological variables (slope, upslope contributing area, topographic index and landslide failure probability) from a steepland catchment in northern England. Results suggest that proprietary filters often degrade or fail to improve precision. A combination of terrain sensitive and Gaussian filters performs best for both IfSAR and digital photogrammetry datasets, improving the precision of photogrammetry digital elevation models (DEMs) by more than 50 per cent relative to the unfiltered data. High‐frequency noise and high‐magnitude gross errors corrupt geomorphological variables derived from unfiltered photogrammetry DEMs. However, a terrain sensitive filter effectively removes gross errors and noise is minimized using a Gaussian filter. These improvements propagate through derived variables in a landslide prediction model, to reduce the area of predicted instability by up to 29 per cent of the study area. Interferometric Synthetic Aperture Radar is susceptible to removal of topographic detail by oversmoothing and its errors are less sensitive to filtering (maximum improvement in precision of 5 per cent relative to the raw data). Copyright © 2008 John Wiley and Sons, Ltd. 相似文献