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1.
Vladimir Sabinin 《Geofísica Internacional》2013,52(4):311-320
New computational techniques of QVOA analysis (Quality factor Versus Offset and Azimuth) for fracture characterization are developed. The techniques are applied to synthetic surface data of reflection with noise. 相似文献
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利用横波响应进行裂缝性各向异性介质的检测在实际应用中取得了很好的效果,但技术复杂、成本较高使该方法的广泛使用受到限制,而纵波资料采集和处理技术的精细有效保持了纵波的各种属性,这为直接利用纵波资料进行裂缝检测创造了条件.地下垂直定向裂缝通常用HTI介质模型来描述,为此,本文利用射线追踪和反射率法计算了层状各向同性介质背景下的HTI介质顶、底界面的反射纵波旅行时和反射系数,并分析了这些属性随观测方位的变化规律.研究表明,HTI介质底界面反射纵波旅行时和HTI介质顶界面反射系数表现出了明显的方位各向异性;旅行时、振幅和AVO梯度属性均在0°观测方位和90°观测方位上存在最大差异,可以用多种属性联合来精确判定裂缝的发育方向. 相似文献
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电磁类地球物理方法由于极易受到各类噪声的干扰，使得估计的视电阻率曲线或相位曲线发生畸变，严重地影响了反演解译精度，如何对这类观测曲线进行合理有效地平滑，是目前数据处理中的重点，也是难点.本文把各向异性扩散（anisotropic diffusion AD）引入到曲线平滑中，提出了各向异性扩散的曲线平滑方法，以平滑点梯度值的降函数作为扩散速度，在梯度较大的位置予以较小的扩散速度以保护特征，在梯度较小的位置予以较大的扩散速度平滑噪声引起的扰动.同时为了减小“飞点”(outliers)对平滑的干扰，采用局部单调扩散进行预处理.实验结果显示，本文提出的平滑方法有效地平滑了噪声与“飞点”的干扰，恢复了曲线的基本形态，有效地保持了曲线基本特征. 相似文献
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This article utilizes Savitzky–Golay (SG) filter to eliminate seismic random noise. This is a novel method for seismic random noise reduction in which SG filter adopts piecewise weighted polynomial via leastsquares estimation. Therefore, effective smoothing is achieved in extracting the original signal from noise environment while retaining the shape of the signal as close as possible to the original one. Although there are lots of classical methods such as Wiener filtering and wavelet denoising applied to eliminate seismic random noise, the SG filter outperforms them in approximating the true signal. SG filter will obtain a good tradeoff in waveform smoothing and valid signal preservation under suitable conditions. These are the appropriate window size and the polynomial degree. Through examples from synthetic seismic signals and field seismic data, we demonstrate the good performance of SG filter by comparing it with the Wiener filtering and wavelet denoising methods. 相似文献
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长波长假设条件下,各向同性背景地层中发育一组平行排列的垂直裂缝可等效为具有水平对称轴的横向各向同性（HTI）介质.基于不同观测方位的岩石地震响应特征变化,宽方位地震数据不仅可实现裂缝岩石弹性参数与各向异性参数的预测,同时也蕴含着丰富的孔隙度等储层物性参数信息.本文结合实际地震资料提出了贝叶斯框架下岩石物理驱动的储层裂缝参数与物性参数概率地震联合反演方法,首先基于AVAZ反演裂缝岩石的弹性参数与各向异性参数,并在此基础上通过统计岩石物理模型表征孔隙度、裂缝密度等各向异性介质储层参数与裂缝岩石参数的相互关联,并采用马尔科夫链蒙特卡洛（MCMC）抽样方法进行大量样本的随机模拟,使用期望最大化（EM）算法估计后验条件概率分布,最终寻找最大后验条件概率对应的孔隙度、裂缝密度等HTI裂缝介质储层参数即为反演结果.测井及实际地震数据处理表明,该方法能够稳定合理地从方位地震资料中获取裂缝岩石弹性参数与各向异性参数,并提供了一种较为可靠的孔隙度、裂缝密度等裂缝介质储层参数概率地震反演方法. 相似文献
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在深反射地震资料处理中,当来自深部的有效弱信号和噪声干扰频带差异较小且难以区分时,传统滤波方法的应用会受到限制.谱分解方法是一种使用离散傅里叶变换,基于信号的频率-振幅谱等信息生成高分辨率地震图像的方法,通常用来识别介质物性横向分布特征,处理复杂介质内频谱变化和局部相位的不稳定性等问题,包括定位复杂断层和小尺度断裂等.S变换作为一种新的时频分析方法,具有自动调节分辨率的能力,近些年来被广泛应用到勘探地震、大地电磁等数据处理中,逐渐成为地球物理方法中噪声压制的有效方法之一.与常规石油反射地震资料相比,深反射主动源地震为了探测深部结构信息,常采用大药量激发方式、长排列观测系统等,导致深部有效信号基本湮灭在噪声干扰之中.针对深反射数据特点,本文结合谱分解和S变换技术,首先设计了简单的脉冲函数实验数据,证实S变换方法的有效性,同时说明谱分解方法的效果受所用时频分析方法影响较大,而其中决定分辨能力的变换窗函数的选取尤为重要.在此基础上,分别应用到深反射地震资料的单道和叠加剖面实际数据上,对比分析了传统变换谱分解和S变换谱分解的应用效果,单道资料对比结果表明:相比传统谱分解,S变换谱分解方法具有自动调节分辨率的能力,能够精确的标定深反射地震资料中弱信号不同时刻的频率分量;叠加剖面资料应用结果表明:由S变换谱分解得到的剖面结果与其他谱分解方法结果整体上具有较高的一致性,同时清晰地刻画出原叠加剖面上被噪声湮灭的低频细节特征,提高了剖面的分辨率及同相轴连续性;对比结果明显看出,Gabor变换谱分解方法得到的结果同相轴较为破碎,分析原因认为这是由Gabor变换的时频分解方法的定长窗函数所致,窗口大小不会随着信号频率的变化来调节长度,只能在处理的过程中根据一定的记录长度范围选取窗函数参数,而S变换谱分解方法在窗函数的选取时,通过时变信号的局部频率特征自动调节窗口长度,能够更好的刻画各个频段的细节特征,在深反射剖面成像应用中效果尤为明显.本文结果表明S变换谱分解技术在深地震叠加剖面上的应用有效地提高了来自深部弱反射信号的信噪比和分辨率,并刻画出了叠加剖面上所不具有的低频细节特征,在实际深反射地震资料处理中能有效保护低频弱信号获得更好的成像效果.本文为深地震反射资料中弱信号的保护处理找到一种有效的方法. 相似文献
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煤层中存在的裂隙会导致介质表现为各向异性,本文以HTI型煤层为例,结合各向异性介质弹性矩阵和各向异性裂隙理论,推导出不同充填物的垂直裂隙中各向异性参数表达式,将其应用于地震波响应分析;通过改进的交错网格差分法和各向异性Christoffel方程波场分解法,得到地震波合成记录和分解后的P波和SV波记录;将Thomsen群速度与相速度公式,经过坐标轴旋转变换,得到HTI型煤层中不同各向异性参数的地震波速度响应表达式;建立不同类型煤层地质模型,分析了裂隙密度、裂隙充填物以及煤层厚度等参数变化时的地震波响应特征.研究结果为分析垂向裂隙各向异性薄煤层地震波传播规律提供工具,为选用相应地震数据进行地震波各向异性参数反演提供依据. 相似文献
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裂缝型储层表现出较强的各向异性特征.缝隙中充填不同流体时,裂缝储层的地震响应特征也不相同.本文从各向异性岩石物理模型出发,引入可有效识别缝隙流体的指示因子,并研究缝隙充填流体类型、饱和度以及缝隙纵横比与流体因子的相互关系,进而分析不同流体充填时介质的地震响应特征,并基于AVAZ反演方法估测缝隙流体指示因子.首先对缝隙流体因子的敏感性进行了分析,讨论当缝隙充填不同流体时,缝隙流体因子值的变化特征,同时研究了不同流体类型充填时裂缝储层反射系数随方位角和入射角的变化特征.某工区测井数据和复杂裂缝模型应用表明,基于各向异性岩石物理的缝隙流体因子AVAZ反演方法合理、可靠,且具有良好的抗噪性,即当对合成地震记录添加信噪比不小于1/2的随机噪声时,利用AVAZ反演方法估测所得流体因子值与真实值仍然吻合较好. 相似文献
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DC (direct current) electrical and shallow seismic methods are indispensable to the near surface geophysical exploration, but the near surface areas are very difficult environments for any geophysical exploration due to the random noise caused by near surface inhomogeneities. As a new algorithm based on higher-order statistics theory, the higher-order correlation stacking algorithm for seismic data smoothing in the wavelet domain has been developed and applied efficiently to filter some correlation noise that the conventional second-order correlation stacking could not inhibit. In this paper, this higher-order statistics correlation stacking technology is presented for DC electrical data in wavelet domain. Taking into account the single section and multiple section data, we present two new formulations of correlation stacking for DC electrical data. Synthetic examples with Gaussian noise are designed to analyze the overall efficiency of the new algorithm and to determine its efficacy. Meanwhile, comparison with the traditional least-squares optimization inversion method for field examples from electrical imaging surveys and time-domain IP measurement in China shows its significant advantages. The quality of the new algorithm also has been assessed by physical simulation experiments. This new technology in DC electrical exploration measurements provides a new application in engineering and mining investigation. 相似文献
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Fracture detection and fluid identification are important tasks for a fractured reservoir characterization. Our goal is to demonstrate a direct approach to utilize azimuthal seismic data to estimate fluid bulk modulus, porosity, and dry fracture weaknesses, which decreases the uncertainty of fluid identification. Combining Gassmann’s (Vier. der Natur. Gesellschaft Zürich 96:1–23, 1951) equations and linear-slip model, we first establish new simplified expressions of stiffness parameters for a gas-bearing saturated fractured rock with low porosity and small fracture density, and then we derive a novel PP-wave reflection coefficient in terms of dry background rock properties (P-wave and S-wave moduli, and density), fracture (dry fracture weaknesses), porosity, and fluid (fluid bulk modulus). A Bayesian Markov chain Monte Carlo nonlinear inversion method is proposed to estimate fluid bulk modulus, porosity, and fracture weaknesses directly from azimuthal seismic data. The inversion method yields reasonable estimates in the case of synthetic data containing a moderate noise and stable results on real data. 相似文献
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R.-G. FERBER 《Geophysical Prospecting》1985,33(2):212-223
A main problem in computing reflection coefficients from seismograms is the instability of the inversion procedure due to noise. This problem is attacked for two well-known inversion schemes for normal-incidence reflection seismograms. The crustal model consists of a stack of elastic, laterally homogeneous layers between two elastic half-spaces. The first method, which directly computes the reflection coefficients from the seismogram is called “Dynamic Deconvolution”. The second method, here called “Inversion Filtering”, is a two-stage procedure. The first stage is the construction of a causal filter by factorization of the spectral function via Levinson-recursion. Filtering the seismogram is the second stage. The filtered seismogram is a good approximation for the reflection coefficients sequence (unless the coefficients are too large). In the non-linear terms of dynamic deconvolution and Levinson-recursion the noise could play havoc with the computation. In order to stabilize the algorithms, the bias of these terms is estimated and removed. Additionally incorporated is a statistical test for the reflection coefficients in dynamic deconvolution and the partial correlation coefficients in Levinson-recursion, which are set to zero if they are not significantly different from noise. The result of stabilization is demonstrated on synthetic seismograms. For unit spike source pulse and white noise, dynamic deconvolution outperforms inversion filtering due to its exact nature and lesser computational burden. On the other hand, especially in the more realistic bandlimited case, inversion filtering has the great advantage that the second stage acts linearly on the seismogram, which allows the calculation of the effect of the inversion procedure on the wavelet shape and the noise spectrum. 相似文献
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A synthetic seismogram that closely resembles a seismic trace recorded at a well may not be at all reliable for, say, stratigraphic interpretation around the well. The most accurate synthetic seismogram is, in general, not the one that displays the smallest errors of fit to the trace but the one that best estimates the noise on the trace. If the match is confined to a short interval of interest or if the seismic reflection wavelet is allowed to be unduly long, there is considerable danger of forcing a spurious fit that treats the noise on the trace as part of the seismic reflection signal instead of making a genuine match with the signal itself. This paper outlines tests that allow an objective and quantitative evaluation of the accuracy of any match and illustrates their application with practical examples. The accuracy of estimation is summarized by the normalized mean square error (NMSE) in the estimated reflection signal, which is shown to be (/n)(PN/PS) where PS/PN is the signal-to-noise power ratio and n is the spectral smoothing factor. That is, the accuracy varies directly with the ratio of the power in the signal (taken to be the synthetic) to that in the noise on the seismic trace, and the smoothing acts to improve the accuracy of the predicted signal. The construction of confidence intervals for the NMSE is discussed. Guidelines for the choice of the spectral smoothing factor n are given. The variation of wavelet shape due to different realizations of the noise component is illustrated, and the use of confidence intervals on wavelet phase is recommended. Tests are described for examining the normality and stationarity of the errors of fit and their independence of the estimated reflection signal. 相似文献
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Acoustic inversion in one-dimension gives impedance as a function of travel time. Inverting the reflection response is a linear problem. Recursive methods, from top to bottom or vice versa, are known and use a fundamental wave field that is computed from the reflection response. An integral over the solution to the Marchenko equation, on the other hand, retrieves the impedance at any vertical travel time instant. It is a non-recursive method, but requires the zero-frequency value of the reflection response. These methods use the same fundamental wave field in different ways. Combining the two methods leads to a non-recursive scheme that works with finite-frequency bandwidth. This can be used for target-oriented inversion. When a reflection response is available along a line over a horizontally layered medium, the thickness and wave velocity of any layer can be obtained together with the velocity of an adjacent layer and the density ratio of the two layers. Statistical analysis over 1000 noise realizations shows that the forward recursive method and the Marchenko-type method perform well on computed noisy data. 相似文献
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基于可靠地估计反射方位和边界的构造约束保边滤波(英文) 总被引：2，自引：1，他引：1
本文给出一种既能有效衰减地震噪音又可保护地层及构造的不连续性的新方法。构造约束保边平滑技术需要已知反射局部方位和边界信息,通常这些信息由全频率地震资料估算获得,但在资料信噪比很低的情况下,噪音往往会降低估算的可靠度。对于信噪比极低的地震资料,其主频成分相对非主频成分信噪比高,所以由主频资料获取的方位和边界信息比由其它频率成分获取的更可靠。方位和边界信息通常用倾角和相干值差异来描述。由于不同频率所引起的倾角和相干值差异的变化均比地震记录的变化缓慢,所以由主频资料获取的倾角及边界信息能够近似代表所有频率成分的倾角及边界信息。Ricker子波广泛用于地震勘探,Marr小波与Ricker子波在时间和频率域均具有相同的形态,所以选用Marrl小波变换将地震数据按照倍频程分为几个分频体。扫描主频分频体,用不等权二次曲面拟合并求解极大值来获取视倾角,通过比较9个滑动窗口的相干值来确定反射边界。将这些信息用构造约束保边平滑技术可选择性地（selectively）对主频、低频、高频分频体做平滑处理,最后将平滑后的各频段地震记录合成为滤波去噪后的地震记录。理论模型和实际资料处理效果表明该方法能有效压制噪音,保护边界,保护同相轴的连续性,且灵活地保留地震记录中的有用信息。 相似文献
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随机噪声的影响在地震勘探中是不可避免的,常规的随机噪声压制方法在处理中往往会破坏具有时空变化特征的非平稳有效地震信号,影响地震数据的准确成像.当前油气勘探的目标已经转变为“两宽一高”,随着数据量的增大,对去噪方法的处理效率也提出了更高的要求.因此,开发高效的非平稳地震数据随机噪声压制方法具有重要意义.预测滤波技术广泛用于地震随机噪声的衰减,本文基于流式处理框架提出一种新的f-x域流式预测滤波方法,通过在频率域建立预测自回归方程,运用直接复数矩阵逆运算代替迭代算法求解非平稳滤波器系数,实现时空变地震同相轴预测,提高自适应预测滤波的计算效率.通过与工业标准的FXDECON方法和f-x域正则化非平稳自回归(RNA)方法进行对比,理论模型和实际数据的测试结果表明,提出的f-x域流式预测滤波方法能更好地平衡时空变有效信号保护、随机噪声压制和高效计算三者之间的关系,获得合理的处理效果. 相似文献
17.
Singular value decomposition (SVD) is applied to the identification of seismic reflections by using two different models: the impulse response model, where a seismic trace is assumed to consist of a known signal pulse convolved with a reflection coefficient series plus noise, and the delayed pulse model, where the seismic signal is assumed to consist of a small number of delayed pulses of known shape and with unknown amplitudes and arrival times. SVD clearly shows how least-squares estimation of the reflection coefficients may become unstable, since a division by the singular values is required. Two methods for stabilizing this procedure are investigated. The inverse of the singular values may be replaced by zeros when they are less than a given threshold. This is called the SVD cut-off method. Alternatively, we may use ridge regression which in filter design corresponds to assuming white noise. Statistical methods are used to compute an optimal SVD cut-off level and also to compute an optimal weighting parameter in ridge regression. Numerical studies indicate that the use of SVD cut-off or ridge regression stabilizes the least-squares procedure, but that the results are inferior to maximum-likelihood estimation where the noise is assumed to be filtered white noise. For the delayed pulse model, we use a linearization procedure to iteratively update the estimates of both the reflection amplitudes and the arrival times. In each step, the optimal SVD cut-off method is used. Confidence regions for the estimated reflection amplitudes and arrival times are also computed. Synthetic data examples demonstrate the effectiveness of this method. In a real data example, the maximum-likelihood method assuming an impulse response model is first used to obtain initial estimates of the number of reflections and their amplitudes and traveltimes. Then the iterative procedure is used to obtain improved estimates of the reflection amplitudes and traveltimes. 相似文献
18.
鉴于地震数据不连续性检测的重要性,本文提出了一种保持和检测地震图像不连续性(如:岩层,断层,河道等)的方法.通常在图象不连续的地方,象素值会有较大的差异,文中用4×4的方向模板计算目标点周围六个方向上的差值,当最大差值超过某个门限值时,则可认为该点为不连续点,由此来检测地震图像的不连续性.由于包含重要信息的区域受噪声的影响通常比其他地方严重,而且基于差值的不连续性检测算法对噪声较为敏感,所以在不连续性检测之前降低地震图像的噪声是很重要的.普通的平滑去噪方法会造成边缘模糊,不利于不连续性检测.本文采用旋转模板的非线性平滑方法,用四个六边形和一个八边形模板在目标像素周围旋转,用与目标像素标准差最小(最同类)的模板内那些点的均值代替目标像素的值,从而实现对地震图象的保边缘平滑去噪处理.理论模型和实际数据处理结果表明:与Y、Luo等人提出的保边缘平滑方法相比,本文的保边缘平滑处理方法提高了计算效率和峰值信噪比;将文中提出的保边缘平滑方法和基于方向模板的不连续性检测方法结合使用,得到的不连续性检测结果比直接检测更清晰.地震数据解释人员可根据检测到的不连续性来识别断层、岩层、河道等. 相似文献
19.
基于稀疏反演的地震插值方法是一种重要的插值方法,然而大多数这类方法只针对无噪声数据或者高信噪比数据插值.实际上,地震数据含有各种噪声,使得插值问题变得更加困难.凸集投影方法是一种高效的插值算法,但是对于含噪声数据的插值效果不理想,针对含噪声数据提出的加权凸集投影方法能够实现同时插值和去噪,但是除了最小阈值需要认真选取外,增加一个权重因子来实现去噪功能.本文由迭代阈值算法推导出加权凸集投影方法,证明其是解无约束优化问题的一种方法,加权因子可以看作拟合误差项的系数.本文还提出了一种改进的凸集投影方法,与原始凸集投影方法相比该方法不需要增加任何计算量,只要通过阈值的选择来进行插值和去噪.数值模拟证明了该算法的计算效率,并且对含噪声数据能够实现较好的插值效果;先插值后去噪的结果证明了同时去噪和插值算法的可靠性和稳定性. 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