Random seismic noise attenuation by learning-type overcomplete dictionary based on K-singular value decomposition algorithm

The transformation of basic functions is one of the most commonly used techniques for seismic denoising,which employs sparse representation of seismic data in the transform domain. The choice of transform base functions has an influence on denoising results. We propose a learning-type overcomplete dictionary based on the K-singular value decomposition( K-SVD) algorithm. To construct the dictionary and use it for random seismic noise attenuation,we replace fixed transform base functions with an overcomplete redundancy function library. Owing to the adaptability to data characteristics,the learning-type dictionary describes essential data characteristics much better than conventional denoising methods. The sparsest representation of signals is obtained by the learning and training of seismic data. By comparing the same seismic data obtained using the learning-type overcomplete dictionary based on K-SVD and the data obtained using other denoising methods,we find that the learning-type overcomplete dictionary based on the K-SVD algorithm represents the seismic data more sparsely,effectively suppressing the random noise and improving the signal-to-noise ratio.     

High accuracy NMO correction and application for VTI media

It is difficult for normal moveout(NMO)correction of shallow long offset of vertical transversely isotropic medium,as seismic event after conventional NMO correction experienced strong stretching and distortion due to interleaving of signal.Even using higher order non-hyperbolic NMO correction,it still cannot get the right results.This paper aims to improve the accuracy of NMO correction.Based on the analysis of conventional NMO correction method and previous optimization move-out equation,we use longitudinal optimization method to correct seismic event.The results of the theoretical model and the real data show that our method can completely remove NMO stretching and greatly improve correction accuracy.     

高精度广义KL变换波场分离与去噪

KL滤波是地震数据处理中的重要方法技术之一。针对在实际中如何有效地应用好KL变换的问题，结合有效波同相轴高精度拾取和排齐技术，采用奇异值分解（SVD）算法实现KL变换，使KL滤波适用于任意弯曲同相轴的分离与消除。理论模型计算和实际资料处理试验表明，使甬该方法能有效地分离相干噪声和随机噪声，提高地震记录的信噪比，简单实用．便于操作。     

APPlication of suPPressing random noise in seismic data based on Trivashrink and DTCWT

In Process of seismic exPloration,the noise of seismic signals Produces serious interference. Conven-tional methods of wavelet threshold denoising cannot fully use the characteristics of seismic signal...     

Seislet transform denoising based on total variation minimization

Attenuation of noise is a persistent problem in seismic exploration. The authors use conventional denoising method to remove noise which may cause vibration near the discontinuity called pseudo-Gibbs artifact.In order to remove the artifact,the study proposed a method combining the seislet transform and total variation minimization. Firstly,the data are converted into the seislet transform domain. Secondly,the hard threshold was used for eliminating the noise and keep useful signal,which is the initial input for the next step. Finally,total variation minimization dealed with denoised data to recover boundary information and further eliminated the noise. Synthetic data examples show that the method has feasibility in eliminating random noise and protecting detailed signal,and also shows better results than the classic f-x deconvolution. The field data example also shows effective in practice. It can remove the noise and preserve the discontinuity signal at the same time.     

Improvement of S/N ratio of seismic data by hyperbolic filter algorithm

This paper deals with the implementation of the hyperbolic filter algorithm for noise suppression of seismic data. Known the velocity of reflection event, utilizes the resemblance of reflection signal in each seismic trace, the hyperbolic filter algorithm is effective in enhance reflection event and suppress the random noise. This algorithm is used to CDP gathers also is compared with the algorithm of τ-p transform. Simulation shows the hyperbolic filter is effective and better than τ-p transform.     

Study of formation boundary and dip attribute extraction based on edge detection technology

In the seismic profile interpretation process,as the seismic data are big and the small geological fea-tures are difficult to identify,improvement of the efficiency is needed.In this study,structure tensor method in computer image edge detection processing is applied into the 2D seismic profile.Coherent attribute is used to extract formation edge.At the same time,extracting the eigenvalues and eigenvectors to calculate the seismic geometric properties which include dip and apparent dip,automatic identification is achieved.Testing the Gaussian kernel function with synthetic models and comparing the coherent attribute and dip attribute extraction results before and after,the conclusion that Gaussian filter can remove the random noise is obtained.     

基于CEEMDAN和小波变换的地震信号随机噪声压制新方法

提出一种结合自适应噪声完备集合经验模态分解（CEEMDAN）和小波变换（WT）的地震信号去噪新方法CEEMDAN-WT。首先利用CEEMDAN将地震信号自适应地分解为若干个固有模态函数（IMF）和余量;然后计算各分量与原始信号的皮尔森相关系数,对处在不同相关系数阈值区间内的分量分别作小波滤波、维持原状及直接剔除等处理,并进行线性重构;最后构建样本熵变化量、互信息、信噪比等指标体系,定量评估去噪效果。模拟实验与实测数据（青海玛多地震）计算结果表明,与EMD、EEMD等方法相比,CEEMDAN-WT方法能有效抑制随机噪声的影响,提高信噪比,并且地震信号的精细化重构效果较好,信号有效成分得到较大保留。     

地震背景噪声中Lg波的提取

以鄂、湘、粤地区27个宽频带测震台站2 a的连续波形数据为例,对单台每日的连续波形数据进行去除仪器响应、去趋势、去均值、剔除地震事件和干扰及滤波（2.5~8 s）处理后,在互相关叠加数据中识别出了清晰的Lg波。另外,尝试通过叠加时间长度校正及用双台双震源法对几何扩散、噪声源强度的方位角变化和场地效应进行校正,并计算Q值。研究结果表明,对传统的地震背景噪声数据处理方法作适当修改后,噪声互相关叠加数据中可以提取出Lg波。     

十字交叉排列面波压制方法及应用

考虑面波特征和古龙断陷区地震资料面波强的特点,提出面波压制的十字交叉排列法.该方法将地震资料中的炮点线和检波点线重排后,进行三维Fourier变换;在频率—波数域滤波后,进行Fourier反变换,实现面波压制处理.古龙断陷区地震资料面波压制结果表明,十字交叉排列面波压制方法具有很好的保幅性和实用性,能够为地震资料保幅处理提供较好的叠前预处理方法,可以在深层地震资料处理中推广应用.     

线性Radon变换噪音压制法及其在古龙断陷中的应用

针对松辽盆地北部古龙断陷地震资料信噪比低、线性干扰强特点,提出应用线性Radon变换进行叠前线性噪音压制的预处理方法,Radon变换可在炮集和CMP道集上进行运算,算法简单,易于编程实现,其积分路径的特点适合线性噪音压制.模拟数据和实际地震资料应用结果表明,线性Radon变换法能够实现保幅的线性噪音压制,是叠前提高地震资料信噪比的实用方法,在地震资料预处理中具有应用前景.     

基于分数阶最优控制网络的复杂勘探随机噪声消减方法

在实际勘探记录处理过程中,复杂随机噪声的出现严重影响了有效反射信息的提取,并对资料后续处理带来了不利影响。随着非常规油气资源开发,对勘探记录质量提出了更高的要求,常规方法在处理能力方面需要持续提升。为了解决复杂噪声消减问题,笔者将最优控制网络引入随机噪声消减领域。与传统的单一尺度消噪网络不同,FOC-NET具有分层结构,能够利用不同尺度信息并结合信息融合处理实现地震勘探数据潜在特征的高精度提取,克服了传统去噪网络单一尺度信息提取造成的有效特征损失问题。同时,在面对低信噪比勘探记录和弱反射同相轴时,多尺度特征交互方式同样可以有效提高噪声压制和信号恢复能力。合成记录和实际数据处理结果均表明,即使在低信噪比条件下,FOC-NET仍能有效地抑制随机噪声并准确重构出有效反射信息,极大提升勘探资料的质量。      

基于提升小波的单历元GPS变形监测信号的去噪

介绍提升小波阈值收缩法去噪的基本原理和方法,利用该方法对含噪的GPS单历元变形监测数据进行去噪,提取真实变形信息。实际数据处理结果表明,相比第一代小波,提升小波变换去噪效果更好,计算速度更快。     

Influence of non-dimensional strength parameters on the seismic stability of cracked slopes

Cracks in rock or soil slopes influence the stability and durability of the slopes. Seismic forces can trigger slope disasters, particularly in the cracked slopes. Considering the nonlinear characteristics of materials, the more generalized nonlinear failure criterion proposed by Baker is adopted. The influence of non-dimensional strength parameters on the stability of cracked slopes under earthquakes is performed using the upper bound limit analysis. The seismic displacement is calculated by adopting the logarithmic spiral failure surface according to the sliding rigid block model. Based on the existing studies, two methods for the stability analysis of cracked slopes under earthquakes are introduced: the pseudo-static method(with the factor of safety(Fs) as an evaluation index), and the displacement-based method(with the seismic displacement as an evaluation index). The pseudo-static method can only determine the instantaneous stability state of the cracked slope, yet the displacement-based methodreflects the stability variation of cracked slopes during earthquakes. The results indicate that the nondimensional strength parameters affect the factor of safety and seismic displacement of slopes significantly. The non-dimensional strength parameter(n) controlling the curvature of strength function shapes on the slope stability is affected by other parameters. Owing to cracks, the effect of non-dimensional strength parameters on seismic displacement becomes more significant.     

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高速岩体反射地震探测中的数据采集与处理

为了调查内蒙古阿拉善某高放废物地质处置库预选场址中目标花岗岩体的空间展布、内部结构和边界接触关系,应用人工反射地震探测技术,采集数据并进行处理,获得了针对大型高速岩体的近地表速度剖面和地震反射波法成像剖面。针对崎岖地表工区近地表速度建模与层析静校正、强散射干扰波压制等问题,引进基于MSFM射线追踪算法的初至波旅行时层析反演与层析静校正技术、改进的矢量分解压噪方法等,并在常规高分辨反射地震数据处理流程的基础上形成了适合于高速岩体地震探测的精细数据处理流程。     

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基于数学形态学的地震带图像识别分析

本文通过“滑动窗口”的方法将离散的地震点分布转化为反映其密度分布的灰度图像,再以数学形态学中骨架提取方法来提取地震带位置。首先对地震分布密度的灰度图像进行连通分析,认为主要的连通成分即对应了地震密集分布的地震带所处位置,之后对主要连通成分通过Fourier滤波来平滑图像内部及边缘的噪声,对经过Fourier滤波的图像运用数学形态学骨架提取方法来提取出骨架,以识别地震带的位置。本方法在使用模拟数据检验方法的有效性之后,应用于大华北地区的地震记录,对提取出的骨架采用GIS中的缓冲分析方法进行统计检验,同时结合地震专家划分的地震带进行比较,结果令人满意。     

可控震源参数选择及在煤田勘探中的应用

介绍了如何选择可控震源的扫描长度和震源台数、振动次数以及扫描频宽等参数 ,指出采用数台可控震源组合 ,增加扫描的总时间和利用相关技术是提高可控震源地震资料信噪比的有效方法 ,也是可控震源取得成功的关键。     

单道地震资料处理关键技术研究及在长岛海域的应用

单道地震作为海上地震勘探测量方式的一种,采用自激自收的测量方式,具有施工效率高、资料处理解释快速的优点,广泛应用于海上地质调查。本文对单道地震资料处理方法进行了研究,提出了一整套处理流程,重点是采用SRME算法对多次波进行压制,提高数据信噪比。将上述算法应用于长岛海域单道地震资料处理,取得了良好的效果。