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水平叠加技术能够有效地压制随机噪声和多次波，但是对于由于相邻道的噪声表现出相关性和一致性而产生的某些相干干扰，常规的叠加技术容易产生假的同相轴，难以取得较高的信噪比.基于小波理论和高阶统计理论本文提出了小波域高阶相关叠加技术(HOCS)，其基本原理是将经动静校正的CMP道集变换到小波域，然后在小波域求取高阶相关系数，进而加权叠加.数值实验和实际资料计算的结果表明，此方法比常规叠加更能够有效地提高信噪比，剔除常规加权叠加无法抑制的某些相关噪声. 相似文献
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P. Gouédard L. Stehly F. Brenguier M. Campillo Y. Colin de Verdière E. Larose L. Margerin P. Roux F. J. Sánchez-Sesma N. M. Shapiro R. L. Weaver 《Geophysical Prospecting》2008,56(3):375-393
Random field cross‐correlation is a new promising technique for seismic exploration, as it bypasses shortcomings of usual active methods. Seismic noise can be considered as a reproducible, stationary in time, natural source. In the present paper we show why and how cross‐correlation of noise records can be used for geophysical imaging. We discuss the theoretical conditions required to observe the emergence of the Green's functions between two receivers from the cross‐correlation of noise records. We present examples of seismic imaging using reconstructed surface waves from regional to local scales. We also show an application using body waves extracted from records of a small‐scale network. We then introduce a new way to achieve surface wave seismic experiments using cross‐correlation of unsynchronized sources. At a laboratory scale, we demonstrate that body wave extraction may also be used to image buried scatterers. These works show the feasibility of passive imaging from noise cross‐correlation at different scales. 相似文献
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地震勘探资料噪声压制及信噪比提高是整个地震勘探信号处理过程中的重要任务,随着地震勘探深度的增加及其复杂性,人们对地震数据质量的要求越来越高.勘探环境的复杂化使得采集到的地震资料中有效信号被大量噪声淹没,无法清晰辨识,严重影响后续的数据处理与解释.小波去噪是地震勘探中常用且发展较成熟的一种方法,但是其涉及到的阈值函数选取问题一直令人困扰,虽然已有多种阈值函数被提出,但仍存在各自的缺陷.本文利用小波分解在时域及频域良好的信号细节体现特性,引入模式识别中的非负矩阵分解(NMF)谱分离思想,针对小波系数阈值优化问题,提出了一种小波域图非负矩阵分解(GNMF)消噪算法.该方法首先在小波分解基础上,利用GNMF算法实现小波分解系数谱中信号分量与噪声分量的谱分离,然后通过反变换重构各分离子谱对应的子信号,最后利用K均值聚类算法将得到的多个子信号划分为信号类及噪声类,最终得到重构信号及分离噪声.合成记录和实际地震资料的消噪结果验证了新方法在提高信号与噪声分离准确性和精度方面的有效性,同时新方法避免了阈值选取造成的噪声压制不理想或有效成分损失问题.与小波消噪结果的对比及数值分析也说明了新方法在噪声压制及有效成分保持方面的优势. 相似文献
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Topography and severe variations of near‐surface layers lead to travel‐time perturbations for the events in seismic exploration. Usually, these perturbations could be estimated and eliminated by refraction technology. The virtual refraction method is a relatively new technique for retrieval of refraction information from seismic records contaminated by noise. Based on the virtual refraction, this paper proposes super‐virtual refraction interferometry by cross‐correlation to retrieve refraction wavefields by summing the cross‐correlation of raw refraction wavefields and virtual refraction wavefields over all receivers located outside the retrieved source and receiver pair. This method can enhance refraction signal gradually as the source–receiver offset decreases. For further enhancement of refracted waves, a scheme of hybrid virtual refraction wavefields is applied by stacking of correlation‐type and convolution‐type super‐virtual refractions. Our new method does not need any information about the near‐surface velocity model, which can solve the problem of directly unmeasured virtual refraction energy from the virtual source at the surface, and extend the acquisition aperture to its maximum extent in raw seismic records. It can also reduce random noise influence in raw seismic records effectively and improve refracted waves’ signal‐to‐noise ratio by a factor proportional to the square root of the number of receivers positioned at stationary‐phase points, based on the improvement of virtual refraction's signal‐to‐noise ratio. Using results from synthetic and field data, we show that our new method is effective to retrieve refraction information from raw seismic records and improve the accuracy of first‐arrival picks. 相似文献
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针对地面地震分辨率低,不能有效识别薄层储层、薄层地层等问题,本文通过地震波衰减规律的分析,提出了一种恢复地震波高频衰减获得宽频带地震剖面的方法,从而大幅度地提高了地震分辨率.应用双井微地震测井资料对松辽盆地地震波动力学特征研究表明,地震波衰减规律是在近地表低速层和近地表低速层的近震源区地震波高频衰减巨大,而在高速层地震波高频衰减很小.药量大近震源区地震波高频衰减大,药量小近震源区地震波高频衰减小.那么,近震源区和近地表低速层对地震波的衰减是地面地震资料频带窄、分辨率低的主要原因.据此提出了如下确定性反褶积方法,用双井微地震测井资料求取近震源区、近地表低速层和虚反射等滤波因子,用其对地面地震资料作确定性反褶积处理,从而恢复近震源区、近地表低速层等几种因素的地震波衰减,将大药量激发地表接收的地面地震延拓成小药量激发高速层接收的宽频带地震.应用该方法对松辽盆地优势频带宽5~90 Hz,视主频50 Hz的地面地震资料处理后,地震剖面优势频带宽达5~360 Hz,视主频达180 Hz,使常规地震剖面分辨率提高2倍.具体的说松辽盆地中部含油组合的地面地震分辨能力由9~15 m提高到3~5 m.宽频带地震剖面与160 Hz的人工合成地震记录对比符合的很好,表明其处理结果是正确.该成果在油气勘探开发中的油气储层预测、构造学研究、沉积学研究等方面有重要的意义. 相似文献
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本文提出了一种基于模型空间压缩技术的大地电磁三维反演方法.该方法在传统大地电磁三维反演理论的基础上,通过小波变换将待反演的空间域模型参数映射到小波域进行反演,获得小波域更新模型后再通过小波逆变换得到空间域反演模型.由于小波变换具有压缩特性和多尺度分辨能力,本文反演方法可在一定程度上提高反演分辨率.为了提高反演效率,我们针对基于L_1范数的模型约束求解不易收敛的反演问题,提出了一种基于模型粗糙度的简单有效的预条件处理技术.为验证本文算法的有效性,本文首先对经典的"棋盘"模型进行三维反演测试.反演结果表明本文算法的反演效率与传统方法相当,但对于深部异常体具有更好的分辨能力.最后,我们通过对实测数据反演进一步验证本文算法的有效性. 相似文献
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在利用不同的地球物理勘探方法对地下复杂介质成像时,因观测系统的非完备性及数据本身对某些岩石物性的不敏感性,单独成像的结果存在较大的不确定性和不一致性.对于地震体波走时成像与直流电阻率成像,均面临着成像阴影区问题.对于地震走时成像,地震射线对低速区域覆盖较差形成阴影区,造成低速区域分辨率降低.对于电阻率成像,电场线在高阻区域分布较少,造成高阻区域分辨率较低.为了提高地下介质成像的精度,Gallado和Meju(2003)提出了基于交叉梯度结构约束的联合地球物理成像方法.在要求不同的物性模型拟合各自对应的数据同时,模型之间的结构要求一致,即交叉梯度趋于零.为了更有效地实现基于交叉梯度的结构约束,我们提出了一种新的交替结构约束的联合反演流程,即交替反演不同的数据而且在反演一种数据时要求对应的模型与另一个模型结构一致.新的算法能够更容易地把单独的反演系统耦合在一起,而且也更容易建立结构约束和数据拟合之间的平衡.基于新的联合反演流程,我们测试了基于交叉梯度结构约束的二维跨孔地震走时和直流电阻率联合成像.合成数据测试表明,我们提出的交替结构约束流程能够很好地实现基于交叉梯度结构约束的联合成像.与单独成像结果相比,地震走时和全通道电阻率联合成像更可靠地确定了速度和电阻率异常. 相似文献
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地震数据本质上是时变的,不仅有效同相轴表现出确定性信号的时变特征,而且复杂地表和构造条件以及深部探测环境总是引入时变的非平稳随机噪声.标准的频率-空间域预测滤波只适合压制平面波信号假设下的平稳随机噪声,而处理非平稳地震随机噪声时,需要将数据体分割为小窗口进行分析,但效果不够理想,而传统非预测类随机噪声压制方法往往适应性不高,因此开发能够保护地震信号时变特征的随机噪声压制方法具有重要的工业价值.压缩感知是近年出现的一个新的采样理论,通过开发信号的稀疏特性,已经在地震数据处理中的数据插值以及噪声压制中得到了应用.本文系统地分析了压缩感知理论框架下的地震随机噪声压制问题,建立了阈值消噪的数学反演目标函数;针对时变有效信息具有的可压缩性,利用有限差分算法求解炮检距连续方程,构建有限差分炮检距连续预测算子(FDOC),在seislet变换框架下,提出一种新的快速稀疏变换域———FDOC-seislet变换,实现地震数据的高度稀疏表征;结合非平稳随机噪声不可压缩的特征,提出了一种整形迭代消噪方法,该方法是一种广义的迭代收缩阈值(IST)算法,在无法计算稀疏变换伴随算子的条件下,仍然能够对强噪声环境中的时变有效信息进行有效恢复.通过对模型数据和实际数据的处理,验证了FDOC-seislet稀疏变换域随机噪声迭代压制方法能够在保护复杂构造地震波信息的前提下,有效地衰减原始数据中的强振幅随机噪声干扰. 相似文献
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东营凹陷西部沙四段地层叠置关系复杂,物性纵横向变化剧烈,地震反射特征差异小,给砂体识别尤其是砂体边界的识别带来了困难。针对以上问题,文中提出了基于地震信号多尺度高阶累积量的相关分析技术。在高阶统计量分析理论和小波分析理论的基础上,首先对地震记录进行高阶统计量变换计算,然后对该变换结果进行多尺度分解。为了使相关分析结果更加可靠,在对上述结果进行相关分析计算时,适当地加入了计算多尺度地震记录的包络结果。对算法从理论模型和实际资料上给出了论证,特别是在解决实际问题方面,经技术处理后,使原来较模糊甚至很弱的地震记录有了清楚的显示。在平面上,原来的地震资料中几乎不能分辨的砂体及边界得到了清晰的反映 相似文献
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Microseismic events enhancement and detection in sensor arrays using autocorrelation‐based filtering 
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下载免费PDF全文 Entao Liu Lijun Zhu Anupama Govinda Raj James H. McClellan Abdullatif Al‐Shuhail SanLinn I. Kaka Naveed Iqbal 《Geophysical Prospecting》2017,65(6):1496-1509
Passive microseismic data are commonly buried in noise, which presents a significant challenge for signal detection and recovery. For recordings from a surface sensor array where each trace contains a time‐delayed arrival from the event, we propose an autocorrelation‐based stacking method that designs a denoising filter from all the traces, as well as a multi‐channel detection scheme. This approach circumvents the issue of time aligning the traces prior to stacking because every trace's autocorrelation is centred at zero in the lag domain. The effect of white noise is concentrated near zero lag; thus, the filter design requires a predictable adjustment of the zero‐lag value. Truncation of the autocorrelation is employed to smooth the impulse response of the denoising filter. In order to extend the applicability of the algorithm, we also propose a noise prewhitening scheme that addresses cases with coloured noise. The simplicity and robustness of this method are validated with synthetic and real seismic traces. 相似文献
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Wavelet‐based cepstrum decomposition of seismic data and its application in hydrocarbon detection 下载免费PDF全文
下载免费PDF全文 Ya‐juan Xue Jun‐xing Cao Ren‐fei Tian Hao‐kun Du Yao Yao 《Geophysical Prospecting》2016,64(6):1441-1453
How to use cepstrum analysis for reservoir characterization and hydrocarbon detection is an initial question of great interest to exploration seismologists. In this paper, wavelet‐based cepstrum decomposition is proposed as a valid technology for enhancing geophysical responses in specific frequency bands, in the same way as traditional spectrum decomposition methods do. The calculation of wavelet‐based cepstrum decomposition, which decomposes the original seismic volume into a series of common quefrency volumes, employs a sliding window to move over each seismic trace sample by sample. The key factor in wavelet‐based cepstrum decomposition is the selection of the sliding‐window length as it limits the frequency ranges of the common quefrency section. Comparison of the wavelet‐based cepstrum decomposition with traditional spectrum decomposition methods, such as short‐time Fourier transform and wavelet transform, is conducted to demonstrate the effectiveness of the wavelet‐based cepstrum decomposition and the relation between these two technologies. In hydrocarbon detection, seismic amplitude anomalies are detected using wavelet‐based cepstrum decomposition by utilizing the first and second common quefrency sections. This reduces the burden of needing dozens of seismic volumes to represent the response to different mono‐frequency sections in the interpretation of spectrum decomposition in conventional spectrum decomposition methods. The model test and the application of real data acquired from the Sulige gas field in the Ordos Basin, China, confirm the effectiveness of the seismic amplitude anomaly section using wavelet‐based cepstrum decomposition for discerning the strong amplitude anomalies at a particular quefrency buried in the broadband seismic response. Wavelet‐based cepstrum decomposition provides a new method for measuring the instantaneous cepstrum properties of a reservoir and offers a new field of processing and interpretation of seismic reflection data. 相似文献
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激电法是金属矿产勘查中一种十分重要的电法勘探分支方法,但是各种电磁干扰的存在限制了激电法在大规模探测中的应用.近年来,国内外先后实现了三维分布式全波形激电探测仪器系统的研发和推广,全波形数据记录为激电信号的抗干扰处理提供了新的空间.本文针对多周期全波形采样的激电数据提出了一套基于统计分析的时间序列抗干扰数据处理方法,主要包括：经验模态分解用于分离低频趋势项干扰;相关分析用于消除突发性强噪声干扰;稳健统计用于多周期时间序列叠加;分段稳健平均和低频相对相位谱用于时/频域激电参数提取.将上述数据处理方法应用于由国产分布式电法系统实测的三维全波形激电数据,并与线性拟合、均值叠加等常处理方法进行对比,发现新方法可以有效识别和压制激电数据中的强噪声干扰,提高大供电极距和低频点探测时的激电数据质量,从而进一步推动激电法在深部矿产资源勘查中的应用. 相似文献
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In this paper, we propose a non-local, transform domain noise suppression framework to improve the quality of seismic reflection data. The original non-local means (NLM) algorithm measures similarities in the data domain and we generalize it in the nonsubsampled contourlet transform (NSCT) domain. NSCT gives a multiscale, multiresolution and anisotropy representation of the noisy input. The redundancy information in NSCT subbands can be utilized to enhance the structures in the original seismic data. Like the wavelet transform, NSCT coefficients in each subband follow the generalized Gaussian distribution and the parameters can be estimated using appropriate techniques. These parameters are used to construct our proposed NSCT domain filtering algorithm. Applications for synthetic and real seismic data of the proposed algorithm demonstrate its effectiveness on seismic data random noise suppression. 相似文献
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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
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基于小波分析的去噪方法在地震资料叠前处理中得到了广泛应用.本文主要介绍利用小波变换的分频特性来压制相干噪声.通过小波分频技术将叠前地震信号分解为不同频带,然后利用有效波和相干干扰波的频谱差异来区分有效信号和噪声,最后利用加权方法去掉不需要的噪声信息来达到去除相干噪声的目的.实际资料的处理结果表明：基于小波分频方法能很好地压制相干噪声,从而提高地震资料信噪比和分辨率. 相似文献
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多尺度形态学在地震去噪中的应用 总被引：3，自引：0，他引：3
In this paper, multi-scaled morphology is introduced into the digital processing domain for land seismic data. First, we describe the basic theory of multi-scaled morphology image decomposition of exploration seismic waves; second, we illustrate how to use multi-scaled morphology for seismic data processing using two real examples. The first example demonstrates suppressing the surface waves in pre-stack seismic records using multi-scaled morphology decomposition and reconstitution and the other example demonstrates filtering different interference waves on the seismic record. Multi-scaled morphology filtering separates signal from noise by the detailed differences of the wave shapes. The successful applications suggest that multi-scaled morphology has a promising application in seismic data processing. 相似文献