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1.
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   

2.
本文基于地层反射系数非高斯的统计特性,在反褶积输出单位方差约束下,将反褶积输出的负熵表示为非多项式函数,作为盲反褶积的目标函数,然后采用粒子群算法优化目标函数寻找最佳反褶积算子,实现地震信号的盲反褶积.数值模拟和实际资料处理结果表明,与传统反褶积方法相比,本文方法同时适应于最小相位子波及混合相位子波的反褶积,能够更好地从地震数据中估计反射系数,有效拓宽地震资料的频谱,得到高分辨率的地震资料.  相似文献   

3.
This paper describes least‐squares reverse‐time migration. The method provides the exact adjoint operator pair for solving the linear inverse problem, thereby enhancing the convergence of gradient‐based iterative linear inversion methods. In this formulation, modified source wavelets are used to correct the source signature imprint in the predicted data. Moreover, a roughness constraint is applied to stabilise the inversion and reduce high‐wavenumber artefacts. It is also shown that least‐squares migration implicitly applies a deconvolution imaging condition. Three numerical experiments illustrate that this method is able to produce seismic reflectivity images with higher resolution, more accurate amplitudes, and fewer artefacts than conventional reverse‐time migration. The methodology is currently feasible in 2‐D and can naturally be extended to 3‐D when computational resources become more powerful.  相似文献   

4.
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   

5.
Cauchy priori distribution-based Bayesian AVO reflectivity inversion may lead to sparse estimates that are sensitive to large reflectivities. For the inversion, the computation of the covariance matrix and regularized terms requires prior estimation of model parameters, which makes the iterative inversion weakly nonlinear. At the same time, the relations among the model parameters are assumed linear. Furthermore, the reflectivities, the results of the inversion, or the elastic parameters with cumulative error recovered by integrating reflectivities are not well suited for detecting hydrocarbons and fuids. In contrast, in Bayesian linear AVO inversion, the elastic parameters can be directly extracted from prestack seismic data without linear assumptions for the model parameters. Considering the advantages of the abovementioned methods, the Bayesian AVO reflectivity inversion process is modified and Cauchy distribution is explored as a prior probability distribution and the time-variant covariance is also considered. Finally, we propose a new method for the weakly nonlinear AVO waveform inversion. Furthermore, the linear assumptions are abandoned and elastic parameters, such as P-wave velocity, S-wave velocity, and density, can be directly recovered from seismic data especially for interfaces with large reflectivities. Numerical analysis demonstrates that all the elastic parameters can be estimated from prestack seismic data even when the signal-to-noise ratio of the seismic data is low.  相似文献   

6.
Signal to noise ratio (SNR) and resolution are two important but contradictory characteristics used to evaluate the quality of seismic data. For relatively preserving SNR while enhancing resolution, the signal purity spectrum is introduced, estimated, and used to define the desired output amplitude spectrum after deconvolution. Since a real reflectivity series is blue rather than white, the effects of white reflectivity hypothesis on wavelets are experimentally analyzed and color compensation is applied after spectrum whitening. Experiments on real seismic data indicate that the cascade of the two processing stages can improve the ability of seismic data to delineate the geological details.  相似文献   

7.
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   

8.
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   

9.
多分辨率地震信号反褶积   总被引:11,自引:2,他引:9       下载免费PDF全文
基于二进小波变换提出了一种新的反褶积方法─-多分辨率地震信号反褶积.在地震信号二进小波变换域中的各尺度上分别进行其分辨率随小波尺度变化的反褶积,利用不同分辨率反褶积结果之间的相关性,以及测量噪声随尺度的衰减特性,从低分辨率反褶积结果逼近高分辨率反褶积结果.理论分析和实验表明,该方法有较高的精度,并且在较低信噪比情况下有好的效果.  相似文献   

10.
用遗传算法实现地震信号反褶积   总被引:3,自引:1,他引:3       下载免费PDF全文
遗传算法作为寻优手段具有全局优化和很好的稳定性.本文将遗传算法用于地震信号反褶积处理,与已往方法相比它具有更好的分辨率和稳定性我们采用Bernoulli-Gaussian模型和ARMA模型分别描述地震反射系数序列和地震子波,用最大似然和最小预测误差准则分别构造用于估计反射系数序列和地震子波的目标函数,用遗传算法优化目标函数,以实现地震信号反褶积.  相似文献   

11.
为了提高AVO(amplitude versus offset)反演结果的精度和横向连续性,本文提出了一种新的AVO反演约束方法,该方法结合贝叶斯原理和卡尔曼滤波算法实现了对反演参数纵向和横向的同时约束.文章首先结合反演参数的纵向贝叶斯先验概率约束和反演参数的横向连续性假设建立了与卡尔曼滤波算法对应的AVO反演系统的数学模型,然后将该数学模型代入卡尔曼滤波算法框架,利用卡尔曼滤波算法实现了双向约束AVO反演.二维模型测试和实际数据测试结果表明,相对于单纯的纵向贝叶斯先验概率约束,双向约束能更准确地刻画参数的横向变化,得到更准确、横向连续性更好的反演结果.  相似文献   

12.
基于反射地震记录变子波模型提高地震记录分辨率   总被引:6,自引:1,他引:5       下载免费PDF全文
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   

13.
The purpose of deconvolution is to retrieve the reflectivity from seismic data. To do this requires an estimate of the seismic wavelet, which in some techniques is estimated simultaneously with the reflectivity, and in others is assumed known. The most popular deconvolution technique is inverse filtering. It has the property that the deconvolved reflectivity is band-limited. Band-limitation implies that reflectors are not sharply resolved, which can lead to serious interpretation problems in detailed delineation. To overcome the adverse effects of band-limitation, various alternatives for inverse filtering have been proposed. One class of alternatives is Lp-norm deconvolution, L1norm deconvolution being the best-known of this class. We show that for an exact convolutional forward model and statistically independent reflectivity and additive noise, the maximum likelihood estimate of the reflectivity can be obtained by Lp-norm deconvolution for a range of multivariate probability density functions of the reflectivity and the noise. The L-norm corresponds to a uniform distribution, the L2-norm to a Gaussian distribution, the L1-norm to an exponential distribution and the L0-norm to a variable that is sparsely distributed. For instance, if we assume sparse and spiky reflectivity and Gaussian noise with zero mean, the Lp-norm deconvolution problem is solved best by minimizing the L0-norm of the reflectivity and the L2-norm of the noise. However, the L0-norm is difficult to implement in an algorithm. From a practical point of view, the frequency-domain mixed-norm method that minimizes the L1norm of the reflectivity and the L2-norm of the noise is the best alternative. Lp-norm deconvolution can be stated in both time and frequency-domain. We show that both approaches are only equivalent for the case when the noise is minimized with the L2-norm. Finally, some Lp-norm deconvolution methods are compared on synthetic and field data. For the practical examples, the wide range of possible Lp-norm deconvolution methods is narrowed down to three methods with p= 1 and/or 2. Given the assumptions of sparsely distributed reflectivity and Gaussian noise, we conclude that the mixed L1norm (reflectivity) L2-norm (noise) performs best. However, the problems inherent to single-trace deconvolution techniques, for example the problem of generating spurious events, remain. For practical application, a greater problem is that only the main, well-separated events are properly resolved.  相似文献   

14.
基于带状混合矩阵ICA实现地震盲反褶积   总被引:1,自引:2,他引:1       下载免费PDF全文
基于对地震反褶积本质上是一个盲过程的认识,引入高阶统计学盲源分离技术——独立分量分析(ICA)实现地震盲反褶积.在无噪声假设条件下,利用地震记录时间延迟矩阵和地震子波带状褶积矩阵,将地震褶积模型转化为一般线性混合ICA模型,采用FastICA算法,将带状性质作为先验信息,实现所谓带状ICA算法(B\|ICA),得到个数与子波算子长度相等的多个估计反射系数序列和估计子波序列,最后利用褶积模型提供的附加信息从中优选出最佳的反射系数序列及相应的地震子波.模型数据和实际二维地震道数值算例表明:对于统计性反褶积,在不对反射系数作高斯白噪假设,不对子波作最小相位假设的所谓“全盲”条件下,基于ICA方法(反射系数非高斯分布,地震子波非最小相位)可以较好解决地震盲反褶积问题,是基于二阶统计特性的地震信号统计性反褶积方法的提升,具有可行性和应用前景.  相似文献   

15.
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   

16.
用多道反褶积方法测定台站接收函数   总被引:15,自引:3,他引:15       下载免费PDF全文
本文提出了一种在时间域用多道反褶积测定台站接收函数的方法, 以提高台站接收函数的测量精度与分辨率.在单道反褶积的基础上,选取若干个质量较好的远震P波波形事件,构成多道信号,以垂直分量为输入,径向和切向分量作为期望输出,依据最小二乘,设计多道滤波器,提取接收函数.合成地震图与观测地震图的检验表明, 多道滤波方法能有效地测定台站接收函数,特别是多道反褶积能够有效地恢复地壳上地幔间断面所产生的弱转换波震相.  相似文献   

17.
The Kevitsa mafic-ultramafic intrusion, located within the Central Lapland Greenstone Belt in northern Finland, hosts a large, disseminated Ni–Cu–PGE sulphide deposit. A three-dimensional seismic reflection survey was conducted over the Kevitsa intrusion in 2010 primarily for open-pit mine planning and for deep mineral exploration purposes. In the Kevitsa three-dimensional seismic data, laterally continuous reflections are observed within a constrained region within the intrusion. In earlier studies, it has been suggested that this internal reflectivity mainly originates from contacts between the tops and more sulphide-rich bottoms of smaller scale, internally differentiated magma layers that represent a spectrum of olivine pyroxenites. However, this interpretation is not unequivocally supported by the borehole data. In this study, data mining, namely the Self-Organizing Map analysis, of extensive Kevitsa borehole data is used to investigate the possible causes for the observed internal reflectivity within the Kevitsa intrusion. Modelling of the effect of mineralization and alteration on the reflectivity properties of Kevitsa rock types, based on average modal compositions of the rock types, is presented to support the results of the Self-Organizing Map analysis. Based on the results, we suggest that the seismic reflectivity observed within the Kevitsa intrusion can possibly be attributed to alteration, and may also be linked to the presence of sulphide minerals.  相似文献   

18.
基于稀疏约束的地震数据高效采集方法理论研究   总被引:2,自引:1,他引:1       下载免费PDF全文
随着地震勘探目标复杂化和精细化程度的提高以及"两宽一高"等采集技术的广泛应用,当前地震数据采集的时间越来越长、成本越来越高.针对此问题,本文基于压缩感知理论开展了地震数据高效采集方法的改进和探索研究.根据波动方程解的一般表示式,从波场传播的角度给出了地震数据具有稀疏性的数学物理依据及寻找适应地震数据稀疏变换的一般方案;在稀疏性先验信息的指导下,发展了具有"蓝色噪声"频谱特征的改进的分段采样方法,并基于最优化理论提出了地震数据重建方法.地震数据的稀疏性理论、稀疏约束下的高效采集方法以及地震数据的重建方法构成了相对完善的地震数据高效采集理论.把该理论用于指导地震数据采集,即利用稀疏约束的随机采样方法改变常规规则密集测网中炮点和检波点(或二者之一)的分布,设计了三种随机且均匀的高效采集测网,提出了利用相应测网获取的地震数据重建为常规规则密集测网地震数据的针对性方案,并使用重建精度、高效采集数据的直接成像和重建后再成像的结果对比证明了上述重建方案的有效性.基于Marmousi模型的高效采集试验检验了本文构建的基于稀疏约束的地震数据高效采集方法理论框架在提高当前地震数据采集效率、降低勘探成本上的优势以及方法的有效性和可行性.  相似文献   

19.
基于贝叶斯理论的AVO三参数波形反演   总被引:24,自引:7,他引:24       下载免费PDF全文
在实际的AVO反演问题中,叠前数据体中的噪声或其他因素严重影响了AVO反演问题的适定性,而采用先验地质信息作为AVO反演问题的约束条件是解决AVO反演问题不适定的一种可行方法. 文中的似然函数采用了[WTBX]ι[WTBX]p范数的解,并用Cauchy分布表示先验模型参数的分布. 以此为基础,在反演中建立了测井数据的参数协方差矩阵对反演过程进行约束,并采用了共轭梯度算法实现多参数非线性的反演过程. 同时,为了提高反演精度,避免动校正拉伸及依赖于炮检距的调谐效应对参数估计的影响,反演采用动校前地震数据进行参数估计. 从应用效果分析来看,即使叠前道集的信噪比不高,反演的结果也能较好地与实际情况相匹配,为识别储层流体性质提供了新的手段.  相似文献   

20.
预条件共轭梯度反褶积的改进及其应用   总被引:9,自引:9,他引:0       下载免费PDF全文
预条件共轭梯度反褶积方法是结合盲反褶积的实现,运用基于Krylov子空间上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.但由于地震数据对不同频带的信噪比有差异,若直接运用该反褶积处理常伴随分辨率提高的同时出现信噪比显著降低的现象.对于此,本文采取如下方法的改进措施:①在时间域上,当地震数据的振幅较大时,对应的反褶积数据的振幅取值与原地震数据的振幅相等;②在频率域上,当地震数据的频谱幅值大于一定阀值时,对应的反褶积数据的频谱取做原地震数据的频谱.由本文所给的数值算例可以看出,此两项改进方法可取得较好的实用效果.  相似文献   

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