共查询到20条相似文献，搜索用时 29 毫秒
1.
Derman Dondurur 《Pure and Applied Geophysics》2010,167(10):1233-1245
Wiener deconvolution is generally used to improve resolution of the seismic sections, although it has several important assumptions. I propose a new method named Gold deconvolution to obtain Earth’s sparse-spike reflectivity series. The method uses a recursive approach and requires the source waveform to be known, which is termed as Deterministic Gold deconvolution. In the case of the unknown wavelet, it is estimated from seismic data and the process is then termed as Statistical Gold deconvolution. In addition to the minimum phase, Gold deconvolution method also works for zero and mixed phase wavelets even on the noisy seismic data. The proposed method makes no assumption on the phase of the input wavelet, however, it needs the following assumptions to produce satisfactory results: (1) source waveform is known, if not, it should be estimated from seismic data, (2) source wavelet is stationary at least within a specified time gate, (3) input seismic data is zero offset and does not contain multiples, and (4) Earth consists of sparse spike reflectivity series. When applied in small time and space windows, the Gold deconvolution algorithm overcomes nonstationarity of the input wavelet. The algorithm uses several thousands of iterations, and generally a higher number of iterations produces better results. Since the wavelet is extracted from the seismogram itself for the Statistical Gold deconvolution case, the Gold deconvolution algorithm should be applied via constant-length windows both in time and space directions to overcome the nonstationarity of the wavelet in the input seismograms. The method can be extended into a two-dimensional case to obtain time-and-space dependent reflectivity, although I use one-dimensional Gold deconvolution in a trace-by-trace basis. The method is effective in areas where small-scale bright spots exist and it can also be used to locate thin reservoirs. Since the method produces better results for the Deterministic Gold deconvolution case, it can be used for the deterministic deconvolution of the data sets with known source waveforms such as land Vibroseis records and marine CHIRP systems. 相似文献
2.
C. Schmelzbach F. ScherbaumJ. Tronicke P. Dietrich 《Journal of Applied Geophysics》2011,75(4):615-630
Enhancing the resolution and accuracy of surface ground-penetrating radar (GPR) reflection data by inverse filtering to recover a zero-phased band-limited reflectivity image requires a deconvolution technique that takes the mixed-phase character of the embedded wavelet into account. In contrast, standard stochastic deconvolution techniques assume that the wavelet is minimum phase and, hence, often meet with limited success when applied to GPR data. We present a new general-purpose blind deconvolution algorithm for mixed-phase wavelet estimation and deconvolution that (1) uses the parametrization of a mixed-phase wavelet as the convolution of the wavelet's minimum-phase equivalent with a dispersive all-pass filter, (2) includes prior information about the wavelet to be estimated in a Bayesian framework, and (3) relies on the assumption of a sparse reflectivity. Solving the normal equations using the data autocorrelation function provides an inverse filter that optimally removes the minimum-phase equivalent of the wavelet from the data, which leaves traces with a balanced amplitude spectrum but distorted phase. To compensate for the remaining phase errors, we invert in the frequency domain for an all-pass filter thereby taking advantage of the fact that the action of the all-pass filter is exclusively contained in its phase spectrum. A key element of our algorithm and a novelty in blind deconvolution is the inclusion of prior information that allows resolving ambiguities in polarity and timing that cannot be resolved using the sparseness measure alone. We employ a global inversion approach for non-linear optimization to find the all-pass filter phase values for each signal frequency. We tested the robustness and reliability of our algorithm on synthetic data with different wavelets, 1-D reflectivity models of different complexity, varying levels of added noise, and different types of prior information. When applied to realistic synthetic 2-D data and 2-D field data, we obtain images with increased temporal resolution compared to the results of standard processing. 相似文献
3.
Convolution of a minimum‐phase wavelet with an all‐pass wavelet provides a means of varying the phase of the minimum‐phase wavelet without affecting its amplitude spectrum. This observation leads to a parametrization of a mixed‐phase wavelet being obtained in terms of a minimum‐phase wavelet and an all‐pass operator. The Wiener–Levinson algorithm allows the minimum‐phase wavelet to be estimated from the data. It is known that the fourth‐order cumulant preserves the phase information of the wavelet, provided that the underlying reflectivity sequence is a non‐Gaussian, independent and identically distributed process. This property is used to estimate the all‐pass operator from the data that have been whitened by the deconvolution of the estimated minimum‐phase wavelet. Wavelet estimation based on a cumulant‐matching technique is dependent on the bandwidth‐to‐central‐frequency ratio of the data. For the cumulants to be sensitive to the phase signatures, it is imperative that the ratio of bandwidth to central frequency is at least greater than one, and preferably close to two. Pre‐whitening of the data with the estimated minimum‐phase wavelet helps to increase the bandwidth, resulting in a more favourable bandwidth‐to‐central‐frequency ratio. The proposed technique makes use of this property to estimate the all‐pass wavelet from the prewhitened data. The paper also compares the results obtained from both prewhitened and non‐whitened data. The results show that the use of prewhitened data leads to a significant improvement in the estimation of the mixed‐phase wavelet when the data are severely band‐limited. The proposed algorithm was further tested on real data, followed by a test involving the introduction of a 90°‐phase‐rotated wavelet and then recovery of the wavelet. The test was successful. 相似文献
4.
S. M. DEREGOWSKI 《Geophysical Prospecting》1978,26(1):252-290
In a previous paper the author showed how, by computing an inverse filter in the frequency domain, an automatic compromise could be made between the conflicting requirements to spike a wavelet and to keep the attendant noise amplification within bounds. This paper extends the technique to take account of errors in the estimated shape of the wavelet defined to the deconvolution process. The drastic effects which such errors can have if they are ignored are demonstrated. A novel form of filter–called the “self-matching filter”–is defined which allows the user to limit not only the noise amplification but also the sensitivity of the filter to random uncertainties in the estimated wavelet. This is achieved by whitening the spectrum only within automatically selected pass bands whilst suppressing other noise-dominated or uncertainly defined frequency components. Conventional Wiener filtering is shown to be a special case of this more general filter, namely one in which the wavelet uncertainty is completely ignored. The type of phase spectrum which the output pulse should be designed to possess (e.g. zero phase or minimum phase) is briefly discussed. 相似文献
5.
6.
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
7.
R. Marschall 《Surveys in Geophysics》1989,10(2-4):225-304
The desired result of an optimum seismic data processing sequence, is a broad band zerophase section, i.e. a bandpassed version of the actual reflectivity function. However, a lot of socalled zerophase-sections still carry a significant phase-error, which is due to unrealistic assumptions in the processing stream in terms of the design of standard processes as for example deconvolution. The two major issues here are the color of the reflectivity series and the misuse of prewhitening. If not properly handled they lead to a phase- and amplitude spectrum bias in the final section, preventing it from being zerophase. Whereas the reflectivity bias leads to a phase error of 50 to 90 deg, the prewhitening bias results in a phase error, which is directly proportional to the logarithm of the actual prewhitening factor.Therefore, if the spike deconvolution process is applied in a time-variant manner, as a consequence a time-variant and usually frequency dependent phase error is introduced! In this article we have made an effort to include sufficient detail to facilitate a clear understanding of the problems involved.The standard processing flow should have a minimum-delay transform and spike deconvolution prestack, followed by a zerophase transform poststack, where the residual wavelet is assumed to be minimum phase. 相似文献
8.
Bussgang算法是针对褶积盲源分离问题提出的,本文将其用于地震盲反褶积处理.由于广义高斯概率密度函数具有逼近任意概率密度函数的能力,从反射系数序列的统计特征出发,引入广义高斯分布来体现反射系数序列超高斯分布特征.依据反射系数序列的统计特征和Bussgang算法原理,建立以Kullback-Leibler距离为非高斯性度量的目标函数,并导出算法中涉及到的无记忆非线性函数,最终实现了地震盲反褶积.模型试算和实际资料处理结果表明,该方法能较好地适应非最小相位系统,能够同时实现地震子波和反射系数估计,有效地提高地震资料分辨率. 相似文献
9.
Optimum pilot sweep 总被引：3，自引：0，他引：3
The successful application of high-resolution seismic methods requires evaluating each element in the seismic system and ensuring that each part of the system contributes optimally to the success of the method. Unfortunately, unlike data processing, seismic signal generation is not carefully optimized. The purpose of our study was to optimize the source signal in order to better coordinate field operations with subsequent data processing to achieve their common objective. We developed an iterative method for a rational frequency distribution of the energy of a seismic source. The method allows the optimum amplitude spectrum of a source signal to be calculated, thus providing the best data quality at the end of the processing. We assume that the source signal is affected by a total transfer function, by the reflectivity function of a target interval, and by ambient noise, whose characteristics, if not known, can be estimated or measured in practice. The transfer function includes data processing other than the correlation stage and the final trace-optimizing filter. The variance of a reflectivity estimate is considered to be a measure of the data quality and improvement of the characteristic corresponds to a decrease in the variance. For this reason, a constrained Wiener deconvolution filter is used as the final trace-optimizing filter. It not only minimizes the variance of a reflectivity estimate but also ensures a specific signal-to-noise ratio. The method is made feasible by following the Vibroseis technique, primarily because of the versatility of the technique in controlling the signal spectrum. With the optimum amplitude spectrum obtained, the corresponding optimum pilot sweep can be readily calculated. Examples using synthetic data are presented to illustrate the method. 相似文献
10.
In order to perform a good pulse compression, the conventional spike deconvolution method requires that the wavelet is stationary. However, this requirement is never reached since the seismic wave always suffers high‐frequency attenuation and dispersion as it propagates in real materials. Due to this issue, the data need to pass through some kind of inverse‐Q filter. Most methods attempt to correct the attenuation effect by applying greater gains for high‐frequency components of the signal. The problem with this procedure is that it generally boosts high‐frequency noise. In order to deal with this problem, we present a new inversion method designed to estimate the reflectivity function in attenuating media. The key feature of the proposed method is the use of the least absolute error (L1 norm) to define both the data and model error in the objective functional. The L1 norm is more immune to noise when compared to the usual L2 one, especially when the data are contaminated by discrepant sample values. It also favours sparse reflectivity when used to define the model error in regularization of the inverse problem and also increases the resolution, since an efficient pulse compression is attained. Tests on synthetic and real data demonstrate the efficacy of the method in raising the resolution of the seismic signal without boosting its noise component. 相似文献
11.
Statistical deconvolution, as it is usually applied on a routine basis, designs an operator from the trace autocorrelation to compress the wavelet which is convolved with the reflectivity sequence. Under the assumption of a white reflectivity sequence (and a minimum-delay wavelet) this simple approach is valid. However, if the reflectivity is distinctly non-white, then the deconvolution will confuse the contributions to the trace spectral shape of the wavelet and reflectivity. Given logs from a nearby well, a simple two-parameter model may be used to describe the power spectral shape of the reflection coefficients derived from the broadband synthetic. This modelling is attractive in that structure in the smoothed spectrum which is consistent with random effects is not built into the model. The two parameters are used to compute simple inverse- and forward-correcting filters, which can be applied before and after the design and implementation of the standard predictive deconvolution operators. For whitening deconvolution, application of the inverse filter prior to deconvolution is unnecessary, provided the minimum-delay version of the forward filter is used. Application of the technique to seismic data shows the correction procedure to be fast and cheap and case histories display subtle, but important, differences between the conventionally deconvolved sections and those produced by incorporating the correction procedure into the processing sequence. It is concluded that, even with a moderate amount of non-whiteness, the corrected section can show appreciably better resolution than the conventionally processed section. 相似文献
12.
非稳态地震稀疏约束反褶积研究（英文） 总被引：1，自引：1，他引：0
传统Robinson褶积模型主要受缚于三种不合理的假设,即白噪反射系数、最小相位地震子波与稳态假设,而现代反射系数反演方法（如稀疏约束反褶积等）均在前两个假设上寻求突破的同时却忽视了一个重要事实：实际地震信号具有典型的非稳态特征,这直接冲击着反射系数反演中地震子波不随时间变化的这一基础性假设。本文首先通过实际反射系数测试证实,非稳态效应造成重要信息无法得到有效展现,且对深层影响尤为严重。为校正非稳态影响,本文从描述非稳态方面具有普适性的非稳态褶积模型出发,借助对数域的衰减曲线指导检测非稳态影响并以此实现对非稳态均衡与校正。与常规不同,本文利用对数域Gabor反褶积仅移除非稳态影响,而将分离震源子波和反射系数的任务交给具有更符合实际条件的稀疏约束反褶积处理,因此结合两种反褶积技术即可有效解决非稳态特征影响,又能避免反射系数和地震子波理想化假设的不利影响。海上地震资料的应用实际表明,校正非稳态影响有助于恢复更丰富的反射系数信息,使得与地质沉积和构造相关的细节特征得到更加清晰的展现。 相似文献
13.
Spectral sparse Bayesian learning reflectivity inversion 总被引：4，自引：0，他引：4
A spectral sparse Bayesian learning reflectivity inversion method, combining spectral reflectivity inversion with sparse Bayesian learning, is presented in this paper. The method retrieves a sparse reflectivity series by sequentially adding, deleting or re‐estimating hyper‐parameters, without pre‐setting the number of non‐zero reflectivity spikes. The spikes with the largest amplitude are usually the first to be resolved. The method is tested on a series of data sets, including synthetic data, physical modelling data and field data sets. The results show that the method can identify thin beds below tuning thickness and highlight stratigraphic boundaries. Moreover, the reflectivity series, which is inverted trace‐by‐trace, preserves the lateral continuity of layers. 相似文献
14.
15.
For years, reflection coefficients have been the main aim of traditional deconvolution methods for their significant informational content. A method to estimate seismic reflection coefficients has been derived by searching for their amplitude and their time positions without any other limitating assumption. The input data have to satisfy certain quality constraints like amplitude and almost zero phase noise—ghosts, reverberations, long period multiples, and diffracted waves should be rejected by traditional processing. The proposed algorithm minimizes a functional of the difference between the spectra of trace and reflectivity in the frequency domain. The estimation of reflection coefficients together with the consistent “wavelet’ is reached iteratively with a multidimensional Newton-Raphson technique. The residual error trace shows the behavior of the process. Several advantages are then obtainable from these reflection coefficients, like conversion to interval velocities with an optimum calibration either to the well logs or to the velocity analysis curves. The procedure can be applied for detailed stratigraphic interpretations or to improve the resolution of a conventional velocity analysis. 相似文献
16.
The amplitude spectrum of ground penetrating radar (GPR) reflection data acquired with a particular antenna set is normally concentrated over a spectral bandwidth of a single octave, limiting the resolving power of the GPR wavelet. Where variously-sized GPR targets are located at numerous depths in the ground, it is often necessary to acquire several profiles of GPR data using antennas of different nominal frequencies. The most complete understanding of the subsurface is obtained when those frequency-limited radargrams are jointly interpreted, since each frequency yields a particular response to subsurface reflectivity. The application of deconvolution to GPR data could improve image quality, but is often hindered by limited spectral bandwidth.We present multiple-frequency compositing as a means of combining data from several frequency-limited datasets and improving the spectral bandwidth of the GPR profile. A multiple-frequency composite is built by summing together a number of spatially-coincident radargrams, each acquired with antennae of different centre frequency. The goal of the compositing process is therefore to produce a composite radargram with balanced contributions from frequency-limited radargrams and obtain a composite wavelet that has properties approximating a delta function (i.e. short in duration and having a broad, uniform spectral bandwidth).A synthetic investigation of the compositing process was performed using Berlage wavelets as proxies for GPR source pulses. This investigation suggests that a balanced, broad bandwidth, effective source pulse is obtained by a compositing process that equalises the spectral maxima of frequency-limited wavelets prior to summation into the composite. The compositing of real GPR data was examined using a set of 225, 450 and 900 MHz GPR common offset profiles acquired at a site on the Waterloo Moraine in Ontario, Canada. The most successful compositing strategy involved derivation of scaling factors from a time-variant least squares analysis of the amplitude spectra of each frequency-limited dataset. Contributions to the composite from each nominal acquisition frequency are clear, and the trace averaged amplitude spectrum of the corresponding composite is broadened uniformly over a bandwidth approaching two-octaves. Improvements to wavelet resolution are clear when a composite radargram is treated with a spiking deconvolution algorithm. Such improvement suggests that multiple-frequency compositing is a useful imaging tool, and a promising foundation for improving deconvolution of GPR data. 相似文献
17.
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
18.
N. DE VOOGD 《Geophysical Prospecting》1974,22(2):354-369
Approximate deconvolution by means of Wiener filters has become standard practice in seismic data-processing. It is well-known that addition of a certain percentage of noise energy to the autocorrelation of the signal wavelet leads to a filter that does not increase, or even reduces, the noise level on the seismogram. This noise addition will, in general, cause a minimum phase signal to become mixed phase. A technique is presented for the calculation of the optimum-lag shaping filter for a contaminated signal wavelet. The advantages of this method over the more conventional approach are that it needs less arithmetic operations and that it automatically gives the filter with the optimum combination of shaping performance and noise reduction. 相似文献
19.
本文给出了地震记录变子波模型的一种近似数学表达式．基于该表达式研究了反射系数序列不满足白噪假设和子波在地下传播时发生变化这两种情况下地震道谱的组成及结构,讨论了谱白化及反褶积方法在这两种情况下效果不佳的原因．然后基于变子波模型,提出了一种新的提高地震记录分辨率的方法：第一步,用自适应于地震记录的Gabor分子窗把地震记录恰当地划分成若干片断,每段内信号近似平稳,然后将地震记录变换到时间-频率域;第二步,在变换域对每个分子窗内信号的振幅谱进行处理以拓宽频带;最后把处理后的时间-频率域函数反变换回时间域得到提高分辨率后的结果．本文提出的方法具有能较好地适用于反射系数不满足白噪假设的情况及提高分辨率后的地震记录能较好地保持原地震记录的相对能量关系等优点,模型和实际资料算例结果均表明,本文方法在拓宽地震资料频带及保持地震记录局部能量相对关系方面均明显优于谱白化方法． 相似文献
20.
预条件共轭梯度反褶积方法是结合稀疏反褶积的实现,运用优化的预条件共轭梯度法,完成反射系数的反演。用该方法处理地震资料时可提高资料频率,展宽有效频率宽度。但由于地震信号具有时变性,因此本文将该反褶积过程中的子波用多尺度时变子波代替。由数值算例可以看出,该方法可取得较好的实用效果。 相似文献