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1.
A strategy for multiple removal consists of estimating a model of the multiples and then adaptively subtracting this model from the data by estimating shaping filters. A possible and efficient way of computing these filters is by minimizing the difference or misfit between the input data and the filtered multiples in a least‐squares sense. Therefore, the signal is assumed to have minimum energy and to be orthogonal to the noise. Some problems arise when these conditions are not met. For instance, for strong primaries with weak multiples, we might fit the multiple model to the signal (primaries) and not to the noise (multiples). Consequently, when the signal does not exhibit minimum energy, we propose using the L1‐norm, as opposed to the L2‐norm, for the filter estimation step. This choice comes from the well‐known fact that the L1‐norm is robust to ‘large’ amplitude differences when measuring data misfit. The L1‐norm is approximated by a hybrid L1/L2‐norm minimized with an iteratively reweighted least‐squares (IRLS) method. The hybrid norm is obtained by applying a simple weight to the data residual. This technique is an excellent approximation to the L1‐norm. We illustrate our method with synthetic and field data where internal multiples are attenuated. We show that the L1‐norm leads to much improved attenuation of the multiples when the minimum energy assumption is violated. In particular, the multiple model is fitted to the multiples in the data only, while preserving the primaries.  相似文献   

2.
基于单程波偏移算子的地表相关多次波成像   总被引:3,自引:3,他引:0       下载免费PDF全文
在常规地震资料处理中,多次反射波被视为噪声并从地震数据中去除,以免在之后的地震资料解释中造成误解.而事实上,多次波也是地震信号,是照明波场的一部分,能够对地下构造成像的精度做出贡献.本文分析了多次波在传统单程波叠前深度偏移中产生构造假象的机制和表现,为实现基于单程波偏移算子的多次波成像,修改了单程波叠前深度偏移的边界条件,即将输入的震源波场用包含多次波的记录来替代,输入的记录波场用预测出的表层相关多次波来替代,实现了基于单程波偏移算子的地表相关多次波成像,并从理论上给出了其成像依据.通过基于二范式最小能量差原则求取的匹配因子,将多次波成像结果与一次波成像结果进行匹配叠加,应用多次波成像来弥补一次波成像的不足.简单模型验证了基于单程波偏移算子的多次波成像方法的有效性,最后对Sigsbee2B模型进行了一次波与多次波联合成像试算,盐边界高陡构造成像质量得到了明显改善.  相似文献   

3.
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 fx 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 fx 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 fx domain. Synthetic and field data examples are used to evaluate the performance of the proposed algorithm.  相似文献   

4.
基于全变分原理的多震源混合数据直接偏移方法   总被引:4,自引:3,他引:1       下载免费PDF全文
多震源混合地震采集技术,即将多个震源以一定编码方式连续地激发,得到多炮混合的地震数据.该技术能减少地震采集时间,节约采集成本,但是混合数据的直接偏移会在成像剖面中引入严重的串扰噪声,影响成像效果.从数学上看,地震成像属于典型的数学物理反问题,可以采用线性反演方法求解一个正则化约束的最小二乘(LS)优化问题,获得更高质量的成像结果.全变分(TV)正则化方法是图像去噪和复原领域中广泛应用的热点技术,其能在去除噪声的过程中保留图像的边缘信息和不连续性.在对TV图像去噪复原方法原理分析的基础上,本文将多震源混合数据直接偏移成像问题转换成图像复原的极小化能量泛函问题,用TV正则化代替传统最小二乘偏移(LSM)中的L2范数正则化,提出基于全变分原理的混合数据直接偏移方法.该方法使用基于梯度的快速迭代收缩阈值与快速梯度投影组合算法——FISTA/FGP求解最优化问题,能有效压制串扰噪声,增强同相轴连续性,提高成像分辨率.理论模型测试结果表明:将本方法应用于混合数据,无论是去噪效果还是成像精度都得到显著改善.  相似文献   

5.
A recent dynamo model for Mercury assumes that the upper part of the planet's fluid core is thermally stably stratified because the temperature gradient at the core–mantle boundary is subadiabatic. Vigorous convection driven by a superadiabatic temperature gradient at the boundary of a growing solid inner core and by the associated release of light constituents takes place in a deep sub-layer and powers a dynamo. These models have been successful at explaining the observed weak global magnetic field at Mercury's surface. They have been based on the concept of codensity, which combines thermal and compositional sources of buoyancy into a single variable by assuming the same diffusivity for both components. Actual diffusivities in planetary cores differ by a large factor. To overcome the limitation of the codensity model, we solve two separate transport equations with different diffusivities in a double diffusive dynamo model for Mercury. When temperature and composition contribute comparable amounts to the buoyancy force, we find significant differences to the codensity model. In the double diffusive case convection penetrates the upper layer with a net stable density stratification in the form of finger convection. Compared to the codensity model, this enhances the poloidal magnetic field in the nominally stable layer and outside the core, where it becomes too strong compared to observation. Intense azimuthal flow in the stable layer generates a strong axisymmetric toroidal field. We find in double diffusive models a surface magnetic field of the observed strength when compositional buoyancy plays an inferior role for driving the dynamo, which is the case when the sulphur concentration in Mercury's core is only a fraction of a percent.  相似文献   

6.
Erratic noise often has high amplitudes and a non‐Gaussian distribution. Least‐squares–based approaches therefore are not optimal. This can be handled better with non–least‐squares approaches, for example based on Huber norm which is computationally expensive. An alternative method has been published which involves transforming the data with erratic noise to pseudodata that have Gaussian distributed noise. It can then be attenuated using traditional least‐squares approaches. This alternative method has previously been used in combination with a curvelet transform in an iterative scheme. In this paper, we introduce a median‐filtering step in this iterative scheme. The median filter is applied following the slope direction of the seismic data to maximally preserve the energy of useful signals. The new method can suppress stronger erratic noise compared with the previous iterative method, and can better deal with random noise compared with the single‐step implementation of the median filter. We apply the proposed robust denoising algorithm to a synthetic dataset and two field data examples and demonstrate its advantages over three different noise attenuation algorithms.  相似文献   

7.
Greater attention has been paid to vintage-merge processing of seismic data and extracting more valuable information by the geophysicist. A match filter is used within many important areas such as splicing seismic data, matching seismic data with different ages and sources, 4-D seismic monitoring, and so on. The traditional match filtering method is subject to many restrictions and is usually difficult to overcome the impact of noise. Based on the traditional match filter, we propose the wavelet domain L1 norm optimal matching filter. In this paper, two different types of seismic data are decomposed to the wavelet domain, different detailed effective information is extracted for L1-norm optimal matching, and ideal results are achieved. Based on the model test, we find that the L1 norm optimal matching filter attenuates the noise and the waveform, amplitude, and phase coherence of result signals are better than the conventional method. The field data test shows that, with our method, the seismic events in the filter results have better continuity which achieves the high precision seismic match requirements.  相似文献   

8.
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   

9.
An examination of the westward drift of the geomagnetic field indicates that the drift velocity is almost independent of latitude, suggesting a uniform rigid rotation of spherical shape. When the geomagnetic field is separated into standing and drifting components and expressed in a spherical harmonic series, a lack of sectorial terms is noted in the standing field. It is shown that these features are well explained by a stratified core model.The core is supposed to be stratified near the surface where toroidal fluid motions are predominant. In the deeper part, the fluid motion is two-dimensional, forming Taylor columns. A simplified core model is assumed to represent these features, in which the core is divided into two parts, an outer spherical shell that rotates westwards at a uniform rate of 0.3° y?1 and a central sphere in which the two-dimensional columnar motions reside. The toroidal motions in the outer spherical interact with the dipole field to induce the drifting field, whereas the columnar motions generate the standing field through interaction with a toroidal field. It follows that a small velocity as 5 × 10?3 cm s?1 for the stratified motion is sufficient to create the observed drifting field.  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.
基于Student′s t分布的不依赖子波最小二乘逆时偏移   总被引:1,自引:0,他引:1       下载免费PDF全文
最小二乘逆时偏移(Least-Squares Reverse Time Migration,LSRTM)与常规偏移相比具有更高的成像分辨率、振幅保真性及均衡性等优势,是当前研究的热点之一.震源子波的估计直接影响LSRTM结果的好坏,在实际情况下考虑到震源子波的空变特性,其估计十分困难.为了消除子波对LSRTM结果的影响,本文发展了基于卷积目标泛函的不依赖子波LSRTM算法.目标泛函由观测记录卷积模拟记录的参考道以及模拟记录卷积观测记录的参考道组成,由于观测子波和模拟子波在目标泛函的两项中同时存在,从而消除了子波的影响.此外,常用的基于L2范数拟合的LSRTM算法对噪声非常敏感,尤其是当地震数据中含有异常值时,常规LSRTM无法得到满意的结果.Student′s t分布相比L2范数具有更好的稳健性,本文将其推广到不依赖子波LSRTM中,提升了算法的稳健性,最后通过理论模型及实际资料试算验证了算法的有效性和对复杂模型的适应性.  相似文献   

12.
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   

13.
Parker’s two-dimensional (2D) dynamo model with an algebraic form of nonlinearity for the α-effect is considered. The model uses geostrophic distributions for the α-effect and differential rotation, which are derived from the three-dimensional (3D) convection models. The resulting configurations of the magnetic field in the liquid core are close to the solutions in Braginsky’s Z-model. The implications of the degree of geostrophy observed in the 3D dynamo models for the behavior of the mean magnetic field are explored. It is shown that the reduction in geostrophy leads to magnetic field reversals accompanied by the relative growth of the nondipole component of the field on the surface of the liquid core. The simulations with a random α-effect which causes turbulent pulsations are carried out. The approach is capable of producing realistic sequences of magnetic reversals.  相似文献   

14.
本文对误差数据在各种范数准则下的反演结果进行了详细的分析,在此基础上提出了在反演过程中利用不同范数准则压制噪声的方法,即在反演过程中先用一种范数准则建立目标泛函并求取梯度、再利用另一种范数准则计算修正步长,并在建立目标泛函和求取梯度时引入了非整数次范数准则.该方法有效地避免了在压制噪声过程中的人为干扰,提高了数据的使用率.从合成数据的反演结果可以看出,该方法对噪声具有很好的压制能力.  相似文献   

15.
We present an approach based on local‐slope estimation for the separation of scattered surface waves from reflected body waves. The direct and scattered surface waves contain a significant amount of seismic energy. They present great challenges in land seismic data acquisition and processing, particularly in arid regions with complex near‐surface heterogeneities (e.g., dry river beds, wadis/large escarpments, and karst features). The near‐surface scattered body‐to‐surface waves, which have comparable amplitudes to reflections, can mask the seismic reflections. These difficulties, added to large amplitude direct and back‐scattered surface (Rayleigh) waves, create a major reduction in signal‐to‐noise ratio and degrade the final sub‐surface image quality. Removal of these waves can be difficult using conventional filtering methods, such as an filter, without distorting the reflected signal. The filtering algorithm we present is based on predicting the spatially varying slope of the noise, using steerable filters, and separating the signal and noise components by applying a directional nonlinear filter oriented toward the noise direction to predict the noise and then subtract it from the data. The slope estimation step using steerable filters is very efficient. It requires only a linear combination of a set of basis filters at fixed orientation to synthesize an image filtered at an arbitrary orientation. We apply our filtering approach to simulated data as well as to seismic data recorded in the field to suppress the scattered surface waves from reflected body waves, and we demonstrate its superiority over conventional techniques in signal preservation and noise suppression.  相似文献   

16.
短周期密集台阵的高频背景噪声互相关函数(NCF)是探查地球浅层精细结构的重要数据.然而高频背景噪声成分复杂且容易分布不均,分析其对NCF信号提取的影响,有助于获取可靠成像结果.本文基于布设于川滇地区盐源盆地的209个短周期台站组成的盐源台阵,利用密集台阵的噪声水平评估以及基于NCF的相干噪声分析两种方法,分析了其记录到的噪声波场特征及其对NCF的影响.结果表明,盐源台阵的整体噪声水平呈现北低南高的不均匀分布,高频噪声水平的强弱受控于当地的人类活动,亦受到浅部松散沉积层的影响.台阵垂直分量NCF中主要信号为基阶Rayleigh波,且产生该信号的相干噪声源的优势方位在不同频带具有较大区别:0.3~0.5Hz的噪声源强度较强且随时间变化较为稳定,主要能量来自台阵的南侧;0.5~1Hz的相干噪声源强度较低,有两个优势方向,其中较强的一个来自于台阵南侧,可能与0.3~0.5 Hz的噪声同源,较弱的一个来自于台阵北偏东方向;1~1.5Hz的背景噪声有四个较弱的优势方向,在台阵的不同区域有不同的优势方向,可能受到不同的局部噪声源的控制.垂向NCF中Rayleigh波的信噪比主要受控于波场的复杂程度,台阵南部受人文活动及沉积层影响,噪声水平较高,且由于盆山边缘复杂的反射、散射作用,其NCF波形复杂,信噪比偏低.受高频噪声源分布不均与及复杂地质结构的共同影响,盐源台阵的高频NCF中的信号复杂,后续对面波频散特征的提取应充分考虑噪声源对NCF的影响以获取可靠结果.  相似文献   

17.
Least squares Fourier reconstruction is basically a solution to a discrete linear inverse problem that attempts to recover the Fourier spectrum of the seismic wavefield from irregularly sampled data along the spatial coordinates. The estimated Fourier coefficients are then used to reconstruct the data in a regular grid via a standard inverse Fourier transform (inverse discrete Fourier transform or inverse fast Fourier transform). Unfortunately, this kind of inverse problem is usually under‐determined and ill‐conditioned. For this reason, the least squares Fourier reconstruction with minimum norm adopts a damped least squares inversion to retrieve a unique and stable solution. In this work, we show how the damping can introduce artefacts on the reconstructed 3D data. To quantitatively describe this issue, we introduce the concept of “extended” model resolution matrix, and we formulate the reconstruction problem as an appraisal problem. Through the simultaneous analysis of the extended model resolution matrix and of the noise term, we discuss the limits of the Fourier reconstruction with minimum norm reconstruction and assess the validity of the reconstructed data and the possible bias introduced by the inversion process. Also, we can guide the parameterization of the forward problem to minimize the occurrence of unwanted artefacts. A simple synthetic example and real data from a 3D marine common shot gather are used to discuss our approach and to show the results of Fourier reconstruction with minimum norm reconstruction.  相似文献   

18.
The quantitative explanation of the potential field data of three‐dimensional geological structures remains one of the most challenging issues in modern geophysical inversion. Obtaining a stable solution that can simultaneously resolve complicated geological structures is a critical inverse problem in the geophysics field. I have developed a new method for determining a three‐dimensional petrophysical property distribution, which produces a corresponding potential field anomaly. In contrast with the tradition inverse algorithm, my inversion method proposes a new model norm, which incorporates two important weighting functions. One is the L0 quasi norm (enforcing sparse constraints), and the other is depth‐weighting that counteracts the influence of source depth on the resulting potential field data of the solution. Sparseness constraints are imposed by using the L0 quasinorm on model parameters. To solve the representation problem, an L0 quasinorm minimisation model with different smooth approximations is proposed. Hence, the data space (N) method, which is much smaller than model space (M), combined with the gradient‐projected method, and the model space, combined with the modified Newton method for L0 quasinorm sparse constraints, leads to a computationally efficient method by using an N × N system versus an M × M one because N ? M. Tests on synthetic data and real datasets demonstrate the stability and validity of the L0 quasinorm spare norms inversion method. With the aim of obtaining the blocky results, the inversion method with the L0 quasinorm sparse constraints method performs better than the traditional L2 norm (standard Tikhonov regularisation). It can obtain the focus and sparse results easily. Then, the Bouguer anomaly survey data of the salt dome, offshore Louisiana, is considered as a real case study. The real inversion result shows that the inclusion the L0 quasinorm sparse constraints leads to a simpler and better resolved solution, and the density distribution is obtained in this area to reveal its geological structure. These results confirm the validity of the L0 quasinorm sparse constraints method and indicate its application for other potential field data inversions and the exploration of geological structures.  相似文献   

19.
Presence of noise in the acquisition of surface nuclear magnetic resonance data is inevitable. There are various types of noise, including Gaussian noise, spiky events, and harmonic noise that affect the signal quality of surface nuclear magnetic resonance measurements. In this paper, we describe an application of a two‐step noise suppression approach based on a non‐linear adaptive decomposition technique called complete ensemble empirical mode decomposition in conjunction with a statistical optimization process for enhancing the signal‐to‐noise ratio of the surface nuclear magnetic resonance signal. The filtering procedure starts with applying the complete ensemble empirical mode decomposition method to decompose the noisy surface nuclear magnetic resonance signal into a finite number of intrinsic mode functions. Afterwards, a threshold region based on de‐trended fluctuation analysis is defined to identify the noisy intrinsic mode functions, and then the no‐noise intrinsic mode functions are used to recover the partially de‐noised signal. In the second stage, we applied a statistical method based on the variance criterion to the signal obtained from the initial phase to mitigate the remaining noise. To demonstrate the functionality of the proposed strategy, the method was evaluated on an added‐noise synthetic surface nuclear magnetic resonance signal and on field data. The results show that the proposed procedure allows us to improve the signal‐to‐noise ratio significantly and, consequently, extract the signal parameters (i.e., and V0) from noisy surface nuclear magnetic resonance data efficiently.  相似文献   

20.
According to the features of spatial spectrum of the dynamic ocean topography (DOT),wavelet filter is proposed to reduce short-wavelength and noise signals in DOT. The surface geostrophic currents calculated from the DOT models filtered by wavelet filter in global and Kuroshio regions show more detailed information than those from the DOT models filtered by Gaussian filter. Based on a satellite gravity field model (CG01C) and a gravity field model (EGM96),combining an altimetry-derived mean sea surface height model (KMSS04),two mean DOT models are estimated. The short-wavelength and noise signals of these two DOT models are removed by using wavelet filter,and the DOT models asso-ciated global mean surface geostrophic current fields are calculated separately. Comparison of the surface geostrophic currents from CG01C and EGM96 model in global,Kuroshio and equatorial Pacific regions with that from oceanography,and comparison of influences of the two gravity models errors on the precision of the surface geostrophic currents velocity show that the accuracy of CG01C model has been greatly improved over pre-existing models at long wavelengths. At large and middle scale,the surface geostrophic current from satellite gravity and satellite altimetry agrees well with that from oceanography,which indicates that ocean currents detected by satellite measurement have reached relatively high precision.  相似文献   

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