共查询到20条相似文献，搜索用时 609 毫秒
1.
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
2.
Tensor algebra provides a robust framework for multi-dimensional seismic data processing. A low-rank tensor can represent a noise-free seismic data volume. Additive random noise will increase the rank of the tensor. Hence, tensor rank-reduction techniques can be used to filter random noise. Our filtering method adopts the Candecomp/Parafac decomposition to approximates a N-dimensional seismic data volume via the superposition of rank-one tensors. Similar to the singular value decomposition for matrices, a low-rank Candecomp/Parafac decomposition can capture the signal and exclude random noise in situations where a low-rank tensor can represent the ideal noise-free seismic volume. The alternating least squares method is adopted to compute the Candecomp/Parafac decomposition with a provided target rank. This method involves solving a series of highly over-determined linear least-squares subproblems. To improve the efficiency of the alternating least squares algorithm, we uniformly randomly sample equations of the linear least-squares subproblems to reduce the size of the problem significantly. The computational overhead is further reduced by avoiding unfolding and folding large dense tensors. We investigate the applicability of the randomized Candecomp/Parafac decomposition for incoherent noise attenuation via experiments conducted on a synthetic dataset and field data seismic volumes. We also compare the proposed algorithm (randomized Candecomp/Parafac decomposition) against multi-dimensional singular spectrum analysis and classical prediction filtering. We conclude the proposed approach can achieve slightly better denoising performance in terms of signal-to-noise ratio enhancement than traditional methods, but with a less computational cost. 相似文献
3.
Three‐dimensional seismic survey design should provide an acquisition geometry that enables imaging and amplitude‐versus‐offset applications of target reflectors with sufficient data quality under given economical and operational constraints. However, in land or shallow‐water environments, surface waves are often dominant in the seismic data. The effectiveness of surface‐wave separation or attenuation significantly affects the quality of the final result. Therefore, the need for surface‐wave attenuation imposes additional constraints on the acquisition geometry. Recently, we have proposed a method for surface‐wave attenuation that can better deal with aliased seismic data than classic methods such as slowness/velocity‐based filtering. Here, we investigate how surface‐wave attenuation affects the selection of survey parameters and the resulting data quality. To quantify the latter, we introduce a measure that represents the estimated signal‐to‐noise ratio between the desired subsurface signal and the surface waves that are deemed to be noise. In a case study, we applied surface‐wave attenuation and signal‐to‐noise ratio estimation to several data sets with different survey parameters. The spatial sampling intervals of the basic subset are the survey parameters that affect the performance of surface‐wave attenuation methods the most. Finer spatial sampling will reduce aliasing and make surface‐wave attenuation easier, resulting in better data quality until no further improvement is obtained. We observed this behaviour as a main trend that levels off at increasingly denser sampling. With our method, this trend curve lies at a considerably higher signal‐to‐noise ratio than with a classic filtering method. This means that we can obtain a much better data quality for given survey effort or the same data quality as with a conventional method at a lower cost. 相似文献
4.
5.
深地震反射原始单炮数据是非平稳的弱能量反射信号,信噪比较低.如何提高信噪比一直是深地震反射数据前处理中的一大难题.S变换是一种适用于分析非平稳信号的时频变换方法.同其他分析时变信号的方法相比,S变换的基本小波不必满足小波在时间域均值为零的容许性条件,它的时频分辨率与分析信号的频率有关,且其在时间域的积分可以得到傅里叶频谱,其反变换也简单.因此,S变换容易表示深地震反射信号复杂的时频特性.本文在S变换的基础上,利用软阈值滤波方法对深地震反射数据进行处理,实验结果表明,该方法有效地提高了信噪比,压制了有效频带范围内的混频干扰,突出了弱反射信号,使得波组信息更加丰富,有利于连续追踪有效反射波组和识别薄地层,特别是提高了深部Moho界面反射层位的分辨率,为深地震反射剖面后续处理和准确解释奠定了基础. 相似文献
6.
针对强随机噪声地震资料背景下经典维纳滤波方法在信号的保幅及高维数据空间求解过程中产生病态矩阵的问题,提出利用核函数主分量维纳滤波压制强地震勘探随机噪声.首先利用线性核函数将地震信号映射到特征空间,再通过主分量分析方法提取地震数据主分量进行数据降维,并得到核主分量维纳滤波因子,从而进行核主分量维纳滤波（K-WPC）.正演仿真及对实际地震资料处理表明,该方法对随机噪声有较好的压制作用,保幅效果也令人满意. 相似文献
7.
基于非稳态多项式拟合的地震噪声衰减方法研究(英文) 总被引：1，自引：0，他引：1
基于非稳态多项式拟合理论,针对地震数据中同相轴振幅变化这一特征,我们提出了一种地震噪声衰减的新方法。非稳态多项式拟合系数是时变的,通过整形正则化约束多项式拟和系数的光滑性,自适应的估计地震数据的相干分量。基于动校正后的共中心点道集(CMP)中地震信号的相干性,利用非稳态多项式拟合估计有效信号,从而衰减随机噪声。对于线性相干噪声,如地滚波,首先利用径向道变换(RadialTraceTransform,RTT)将地震数据变换到时间一视速度域,在时间—视速度域利用非稳态多项式拟合估计出相干噪声,然后减去相干噪声。该方法可以有效的估计振幅变化的相干分量,不需要相干分量振幅为常量的假设。模拟和实际资料处理结果表明,与传统的稳态多项式拟合和低切滤波相比,该方法可以更为有效的衰减地震噪声,同时保真了地震有效信号。 相似文献
8.
宽频带地震观测数据中有效信号和干扰噪声经常发生混频效应,常规的频率域滤波方法很难将二者分离.地震波信号属于时变非平稳信号,时频分析方法能够同时得到地震波信号随着时间和频率变化的振幅和相位特征,S变换是其中较为高效的时频分析工具之一.本文以S变换为例,提出了基于相位叠加的时频域相位滤波方法.与传统叠加方法相比,相位叠加方法对强振幅不敏感,对波形一致性相当敏感,更加利于有效弱信号信息的检测.时频域相位滤波方法滤除与有效信号不相干的背景噪声,保留了相位一致的有效信号成分,显著提高了信噪比.运用理论合成的远震接收函数数据和实际的宽频带地震观测数据检验结果显示该方法较传统的带通滤波方法相比,即使在信噪较低且混频严重条件下,时频域相位滤波方法的滤波效果依然很明显,有助于识别能量较弱的有效信号. 相似文献
9.
不连续地质体（如断层）的自动检测一直以来都是叠后地震数据解释中的关键问题之一,尤其在三维情况中尤为重要.然而,大多数边缘检测和相干算法都对随机噪声很敏感,随机噪声衰减是叠后地震数据解释的另一个主要问题.针对构造保护去噪和断层检测问题,本文基于非平稳相似性系数完善一种构造导向滤波方法并且提出一种自动断层检测方法,形成了一套匹配的处理技术.该构造导向滤波既能够有效地衰减随机噪声又可以很好地保护地震资料中的断层等信息不被破坏,增强地震剖面中弯曲、倾斜同相轴的连续性.根据地震数据局部倾角走向,利用相邻道构建当前地震道的预测,通过预测道的叠加得到参考道,计算预测道与参考道之间的非平稳相似性系数可以设计出数据驱动的加权中值滤波.另一方面,预测道与原始道之间的非平稳相似性系数能够用于带有断层指示性的相干分析.这两种方法都基于构造预测和非平稳相似性系数,但是使用不同的调节参数和处理方案.理论模型和实际数据的处理结果证明了本文提出构造导向滤波和断层检测方法的有效性. 相似文献
10.
时频峰值滤波(TFPF)算法是一种非常有效的去噪方法.但是传统的TFPF采用的单一窗长,并且仅沿时间方向进行滤波,忽略了信号的空间信息,并且TFPF近似等效成一个时不变的低通滤波器,不能追踪快速变化的信号.针对这些问题,引入空间局部加权回归自适应TFPF(SLWR-ATFPF).鉴于随机噪声在各个位置的方向随机性,以及有效信号在各个位置的方向确定性,首先利用空间局部加权回归(SLWR),对含噪信号进行空间加权,从而使加权之后的信号包含空间信息.然后,再引入凸集和Viterbi的思想,对空间加权之后的信号进行自适应滤波.从而,完成时空域二维自适应滤波.将SLWR-ATFPF应用于合成记录和实际的共炮点记录,实验结果表明,改进的方法与原算法相比,能够在压制低信噪比(SNR)随机噪声的同时更好地保留有效信号. 相似文献
11.
In land seismic surveys, the seismic data are mostly contaminated by ground-roll noise, high amplitude and low frequency. Since the ground-roll is coherent with reflections and depends on the source, the spectral band of seismic signal and ground-roll always overlap, which can be clearly seen in the spectral domain. So, separating them in time or frequency domain commonly causes waveform distortions and information missing due to cut-off effects. Therefore, the combination of these factors leads to search for alternative filtering methods or processes. We applied the conventional Wiener–Levinson algorithm to extract ground-roll from the seismic data. Then, subtracting it from the seismic data arithmetically performs the ground-roll suppression. To set up the algorithm, linear or nonlinear sweep signals are used as reference noise trace. The frequencies needed in creating a reference noise trace using analytical sweep signal can be approximately estimated in spectral domain. The application of the proposed method based on redesigning of Wiener–Levinson algorithm differs from the usual frequency filtering techniques since the ground-roll is suppressed without cutting signal spectrum. The method is firstly tested on synthetics and then is applied to a shot data from the field. The result obtained from both synthetics and field data show that the ground-roll suppression in this way causes no waveform distortion and no reduction of frequency bandwidth of the data. 相似文献
12.
由于金属矿区地震记录中随机噪声性质复杂且信噪比低,常规降噪方法难以达到预期的滤波效果.时频峰值滤波(TFPF)方法是实现低信噪比地震勘探记录中随机噪声压制的有效方法,但其在复杂地震勘探随机噪声下时窗参数优化问题仍难以解决.本文充分利用地震勘探噪声的统计特性,结合Shapiro-Wilk(SW)统计量辨识地震勘探记录中的微弱有效信号,提出基于SW统计量的自适应时频峰值滤波降噪方法(S-TFPF).在S-TFPF方案中,对于有效信号集中区,S-TFPF方法根据信号频率特征,选择有利于信号保持的较短时窗长度;对于噪声集中区,按噪声方差自适应增加时窗长度,增强随机噪声压制能力.S-TFPF应用于合成记录和共炮点记录的滤波结果表明,与传统时频峰值滤波方法相比,S-TFPF方法可以有效抑制低信噪比地震勘探记录中的随机噪声,更好地恢复出同相轴. 相似文献
13.
Bin Liu Chao Fu Yuxiao Ren Qingsong Zhang Xinji Xu Yangkang Chen 《Geophysical Prospecting》2020,68(5):1509-1522
Random noise attenuation utilizing predictive filtering achieves great performance in denoising seismic data. Conventional predictive filtering methods are based on fixed filter operators and neglect the complexity of structures. In this way, the denoised data cannot meet the requirement of balancing the signal preservation and noise removal. In this study, we proposed a structural complexity-guided predictive filtering method that utilizes an adapted filter operator to adjust the changes of structural complexity. The proposed structural complexity-guided predictive filtering mainly consists of two stages. A slope field information is acquired according to plane-wave destruction to assess the structural complexity. In addition, an adaptive filter operator is obtained to denoise the seismic data according to the adaptive factor. Both synthetic data and real seismic profiles are employed to examine the denoising capacity and flexibility of the refined predictive filtering using adaptive lengths. The analysis of the predicted results shows that adaptive predictive filtering is powerful and has the ability to eliminate random noises with negligible distortions. 相似文献
14.
15.
利用数字图像处理技术提高地震剖面图像信噪比 总被引：1，自引：2，他引：1
提出了利用数字图像处理技术提高地震剖面信噪比的新方法，首先根据数字图像处理要求的格式，对地震剖面数据进行转换，得到地震剖面图像，分析了地震数据特点和初步地震图像的实验结果后，设计了新的预处理方法——“二维沿层滤波”，在此基础上，利用可以计算帧间运动速度及其变化都较大的改进的光流分析技术，计算出多幅地震剖面对应点的偏移量，然后应用图像积累技术对这多幅地震剖面进行积累，实现对三维地震数据体提高信噪比的处理，该方法充分利用了三维地震信息，不但可以提高整个数据体的信噪比，而且可以减少信号能量的损失，并保持原来的信号能量关系，使地震剖面的质量得到明显提高，为地震解释奠定良好的基础。 相似文献
16.
自适应非局部均值地震随机噪声压制(英文) 总被引：2，自引：1，他引：1
非局部均值滤波是一种基于图像信息冗余的去噪方法,其认为图像自身的有效结构具有一定的重复性,而随机噪声则不具备这一特点,通过利用图像本身的自相似性来达到压制随机噪声的目的,是一种全局的去噪方法。本文把这一思想引入地震数据随机噪声压制中,针对传统非局部均值滤波计算量过大的问题,文章采用分块非局部均值的方式来减少计算量;针对滤波参数选取会影响非局部均值滤波效果的问题,提出一种简单的自适应滤波参数地震数据分块非局部均值算法。模型和实际数据处理结果表明:相对于传统的去噪算法(如f-x反褶积),该方法在压制随机噪声的同时对有效信号保护地更好,具有更高的保真度,更有利于后续的处理和解释工作。 相似文献
17.
随机噪声是影响地震勘探有效信号的主要因素,其存在大大降低了地震记录的信噪比.在噪声压制方法不断被改进的同时,对随机噪声特性进行研究,了解噪声的产生机制是对其进行压制的先决条件,目前对噪声的研究主要是特性研究以寻找规律性,对其进行定性定量的分析还比较少.本文根据塔里木沙漠地区实际采集环境,考虑到噪声的连续性给计算带来的不便,假设各类噪声源以点源的形式分布在检波器周围,依据相应理论确定各类噪声源的源函数,其激发的噪声经由波动方程传播,将随机噪声作为各类噪声源共同作用的综合波场,建立随机噪声的理论模型.通过分析不同种噪声对地震记录的影响,选取合适的滤波方法对其进行压制,实验结果表明,通过建立沙漠地区随机噪声的理论模型,为选择有效的滤波方法,提高地震记录信噪比起到理论指导作用. 相似文献
18.
叠前地震资料中,高频分量和低频分量随传播距离的衰减特性不同.本文给出了一种在小波域定性估计叠前地震资料衰减参数的方法.该方法利用连续小波变换提取共反射点道集的高、低频分量,以低频分量和高频分量之差定性反映地震波的衰减.通过累加不同偏移距的衰减,提高了估计的稳定性;采用幅度归一化方法,降低了信号幅值对衰减参数估计的影响.将本文提出方法与常用的基于叠后地震资料衰减估计方法用于某油田的地震资料处理,结果表明,本文方法得到的衰减估计结果能够更好地反映油气的空间展布. 相似文献
19.
经验模态分解算法(EMD)是一种基于有效波和噪声尺度差异进行波场分离的随机噪声压制方法,但由于实际地震数据波场复杂,导致模态混叠较严重,仅凭该方法进行去噪很难达到理想效果.本文基于EMD算法对信号多尺度的分解特性,结合Hausdorff维数约束条件,提出一种用于地震随机噪声衰减的新方法.首先对地震数据进行EMD自适应分解,得到一系列具有不同尺度的、分形自相似性的固有模态分量(IMF);在此基础上,基于有效信号和随机噪声的Hausdorff维数差异,识别混有随机噪声的IMF分量,对该分量进行相关的阈值滤波处理,从而实现有效信号和随机噪声的有效分离.文中从仿真信号试验出发,到模型地震数据和实际地震数据的测试处理,同时与传统的EMD处理结果相对比.结果表明,本文方法对地震随机噪声的衰减有更佳的压制效果. 相似文献
20.
径向道变换(Radial Trace Transform)是将地震道集振幅值从偏移距一双程旅行时坐标系变换到视速度-双程旅行时坐标系,通过这种坐标系的变换,使相干噪声与有效信号在视速度和频率方面都有效分离.本文在介绍RT变换基本原理基础上,分析了RT变换中两种常用插值方法及其特点.并利用对模拟地震资料的处理,证明了RT域模拟-相减法较其带通滤波法在相干噪声压制与反射信号保持方面具有明显优势.最后,根据噪声特点,通过选择合理RT滤波参数,对实际地震资料进行处理试验,获得了较好的去噪效果,明显提高了资料信噪比,验证了研究方法的有效性. 相似文献