Integrating seismic attributes in the accurate modeling of geological structures and determining the storage of the gas reservoir in Gorgan Plain (North of Iran)

Three dimensional seismic operation of Gorgan Plain was studied around a well, which is situated in North of Iran following the hitting of a thin overpressure gas layer (thickness of 9.6 m), with the purpose of the accurate modeling of geological structures and determining the approximate gas storages. The geological structures of the reservoir were modeled using the seismic attributes (coherence, instantaneous amplitude and spectral decomposition (FFT)). The obtained results clearly demonstrated the shape and volume of the existing structural traps in the studied area. In order to estimate the thickness of gas layer in the 3D seismic volume and determining the gas storage, the thickness changes based on the seismic amplitudes were used because its thickness was less than the critical resolution thickness for this layer. However, due to its low thickness, the lack of indicator peak in seismic sections and strong faults of area, it was difficult to pursue this layer in the seismic volume and map its exact amplitude. Considering this issue, a new method with integrating of seismic attributes was recommended. First, the instantaneous amplitude attribute of the thin reservoir layer reflector in computed synthetic seismogram were fabricated and then the frequency regarding the highest amount (dominant frequency) was chosen by Fourier Transform. Finally, spectral decomposition (FFT) with the resulting frequency was gained over the cross-section of the layer's instantaneous amplitude attribute in the 3D seismic volume choosing a proper time window. In such a situation, an increase of its thickness was seen as its amplitude increase and the minimum gas storage of this reservoir was calculated using the area of the restricted part of high thickness (over 9.6 m).     

S变换谱分解技术在深反射地震弱信号提取中的应用

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.     

汶川MS8.0级地震前后ULF电磁辐射频谱特征研究

本文基于电磁波频谱理论研究方法,对2008年四川汶川M_S8.0地震前后金河、剑阁及郑州二砂三个电磁波台站的观测资料进行FFT和小波变换分析,研究了电磁辐射数据快速傅里叶频谱变化特征和在不同尺度下小波变化的分解,发现在汶川地震前确实有异常信息存在.结果表明:(1) FFT动态谱图像说明,地震前电磁波频谱变化特征较明显,在时间、频段上均显示了阶段性进程特征,且随着震中距的增大,辐射能量越小,异常出现的时间越晚;(2) 小波分解显示了地震前电磁波异常信号低频部分出现的时间较早;距震中较近的台站,异常信息在高频部分相对明显;距震中稍远的台站,异常信息在低频部分相对明显.     

MCZT在气枪震源信号频谱分析中的应用

气枪震源信号是短时非平稳信号,采用频谱细化算法能提高频谱分析的准确性。首先进行了改进线性调频Z变换(MCZT)和FFT两种频谱分析算法的误差仿真计算,然后进行气枪震源的水下子波信号和地震波信号的对比计算。结果表明MCZT计算误差较小、计算时间较少,能有效提高气枪震源信号频率和幅度特征提取的准确性,是气枪震源信号频谱特征分析的一个有效方法。     

基于VMD算法在地震数据时频分析中的应用

受新开发的变分模态分解(VMD)的启发,本文引入一种基于VMD的时频分析方法来分析地震数据.VMD的原理是将信号分解成具有一定中心频率的模态分量,通过这些分量来重构原始信号.这种分解方式可以降低各个模态中的残余噪声,同时进一步减少冗余的模态,很好的克服了模态混叠问题.此外,VMD是一种自适应信号分解技术,它可以非递归地将多分量信号分解为几个准正交固有模态函数,与EMD及其推广(如EEMD,CEEMD)相比,有坚实的数学基础.将VMD方法与CEEMD方法进行比较,对合成数据进行测试显示了基于VMD的时频分析方法具有更好的时频聚焦性,同时对实际数据处理也表明该方法具有突出地质特征和地层信息的潜力.     

基于敲击法的碳纤维板加固钢梁脱粘检测研究

碳纤维板与钢梁之间的界面连接情况影响着钢梁的加固效果以及承载性能的发挥,为更好地判别脱粘病害,探究出一种有效的界面脱粘位置定性识别方法。首先制作碳纤维板加固钢梁后的未脱粘试件和脱粘试件,然后通过采用局部敲击指定位置的方法来获取声音信号,并采用Welch功率谱密度(PSD)估计法和快速傅里叶变换(FFT)分析声音信号中的频谱特征。结果表明：从低阶振动频率范围0～500 Hz来看,PSD估计法的2条曲线峰值差别明显,存在脱粘损伤部位的PSD曲线峰值处频率较正常部位处峰值对应频率明显向0偏移,从工况1 PSD曲线中提取得到的平均一阶振动频率从定量的角度揭示出脱粘损伤部位与正常部位频率的变化,这与界面脱粘后局部刚度降低有关;与传统常用的FFT损伤定位方法相比,PSD曲线峰值相比FFT曲线峰值差异性更大,更容易判别出该位置是否发生了脱粘损伤。文章还探究不同属性锤头对试验结果的影响,为实际工程提供有效的参考。     

基于EMD,EEMD与CEEMD的信号 时频分析技术对比研究

时频分析方法在各个领域中广泛应用起来,特别是在工程领域中对结构和构件的变形以及内部损伤检测应用较多。HHT作为一种新兴的非线性,非平稳时频分析技术在探测和勘探领域中具有广阔的前景。文中重点对EMD,EEMD和CEEMD算法进行分析,通过对合成信号进行傅里叶变换和希尔伯特-黄变换,得到信号的频谱图,希尔伯特黄谱,边际谱等数据。通过对比分析,总结了三种方法的优缺点。结果表明,EMD,EEMD和CEEMD方法是进行非线性非平稳信号分析的有效工具。      

基于希尔伯特-黄变换的九寨沟M7.0地震加速度记录时频分析

2017年8月8日四川九寨沟M7.0地震是继2008年汶川M8.0地震和2013年芦山M7.0地震之后,青藏高原东缘在不到10年的时间内发生的第3个震级M7.0以上的强震,震中位于青藏高原巴颜喀拉块体东缘东昆仑断裂带东端的塔藏断裂、岷江断裂和虎牙断裂交汇部位,四川省地震局的数字强震台网共有37个台站获取了主震的三分量强震加速度记录。由于傅里叶（Fourier）变换仅能提供强震记录的频域信息,故本文在对九寨沟M7.0地震的加速度记录进行时频分析时采用了一种基于聚类经验模态分解（EEMD）的希尔伯特-黄变换（HHT）方法提取信号时频特性,通过对震中附近台站的加速度记录进行EEMD分解和希尔伯特（Hilbert）变换及谱分析,最终有效获得了信号能量的时频分布特征,量化提取了中心频率、Hilbert能量、最大振幅对应的时间等特性,并与Fourier变换进行了对比研究。研究结果表明:对于非线性的强震记录采用EEMD能够有效抑制经验模态分解（EMD）中存在的模态混叠问题,FFT谱与Hilbert边际谱相比,它在低频处会低估地震动的幅值,随着频率的增加,FFT谱又会放大其幅值。      

Comparative Study of Microtremor Analysis Methods

-- During a multidisciplinary microzonation pilot project in the city of Heraklion (Crete, Greece), microtremor data were collected at the top of exploratory boreholes specifically designed for the purposes of the project, over a period of 5 days, for 4 h/day at 125 Hz (continuous recordings). The data were analysed with the SSR and H/V Ratio techniques, using the standard FFT (applied to long data series) and a Multi-variate Maximum Entropy (MV-MAXENT) spectral analysis method. Both techniques, implemented with both spectral analysis methods, identify the same major resonance frequency band, albeit with different amplification levels. The MV-MAXENT however is effective in handling short data lengths while yielding high resolution spectra and addressing several shortcomings of the conventional FFT (windowing, zero padding etc.). Thus, it yields competitively similar results, with only a fraction (a few minutes) of the data required by the lower resolution (FFT) method and appears to be a powerful tool for site effect investigations. Moreover, the results of both microtremor-based techniques are consistent and remarkably similar to the results of microzonation methods that require (expensive) borehole data.     

Approximation approach to the SRM based on root decomposition in the simulation of spatially varying ground motions

The spectral representation method(SRM) is widely used to simulate spatially varying ground motions.This study focuses on the approximation approach to the SRM based on root decomposition,which can improve the efficiency of the simulation.The accuracy of the approximation approach may be affected by three factors: matrix for decomposition,distribution of frequency interpolation nodes and elements for interpolation.The influence of these factors on the accuracy of this approach is examined and the following conclusions are drawn.The SRM based on the root decomposition of the lagged coherency matrix exhibits greater accuracy than the SRM based on the root decomposition of the cross spectral matrix.The equal energy distribution of frequency interpolation nodes proposed in this study is more effective than the counter pith with an equal spacing.Elements for interpolation do not have much of an effect on the accuracy,so interpolation of the elements of the decomposed matrix is recommended because it is less complicated from a computational efficiency perspective.     

Localized identification of MDOF structures in the frequency domain

For the identification of multi-degree-of-freedom structures, it is not practical to identify all of the parameters included in the structures because enormous computation time is required and because identifiability may not be possible. In this paper, a localized identification approach through substructuring is formulated in the frequency domain. A technique of spectral smoothing is incorporated in the approach to deal with noise-corrupted data. The proposed approach can be used to identify the structural parameters in any part of interest in a structure. The numerical investigations for a lumped mass-spring-dashpot system indicate that faster convergence and higher accuracy are achieved and the noise influences on the identified results are reduced greatly by spectral smoothing. The approach also applies to whole-structure identification if the required records available and the numerical example shows that higher accuracy results are obtained with less cpu time and more poorly guessed initial values as compared with the general complete-structure identification.     

Structural response to non-stationary multiple-support random excitation

The seismic behaviour of large-size structures subjected to multiple-support excitation is studied by means of a random vibration approach. Ground motion is modelled as a non-stationary stochastic process having an evolutionary spectral density. To describe the spatial variability of the input motion a model is adopted which accounts for finite propagation velocity and for loss of correlation as a function of distance and frequency. Structural analysis is entirely performed in the frequency domain and full advantage is taken of FFT properties and capabilities. An example is given regarding the behaviour of a 800 m long viaduct. Results are shown in terms of response evolutionary spectral density, variance and reliability with respect to a fixed threshold.     

地震台阵上信号方位角和慢度的时、频域估计方法比较

地震台阵常用频率-波数分析法来估计地震信号的后方位角和慢度。尽管有关的算法是众所周知的,但不同的实现在某些情况下可能导致不同的结果。如应用在宽频带的澳大利亚WRA台阵的记录时,标准的f-k分析方法往往给出不正确的结果。本文发现错误是由FFT的频谱泄漏效应引起的,如在进行FFT之前对原始数据进行高通滤波则可以有效地避免这样的错误。进一步对在时域中直接估算信号方位角和慢度的一种算法进行了分析,比较发现时域方法的计算速度和精度都不低于频域方法,且在某些低信噪比的情况下,前者可以给出更可靠的结果。     

Spectral classification methods in monitoring small local events by the Israel seismic network

We use the dense Israel Seismic Network (ISN) to discriminate between low magnitude earthquakes and explosions in the Middle East region. This issue is important for CTBT monitoring, especially when considering small nuclear tests which may be conducted under evasive conditions. We explore the performance of efficient discriminants based on spectral features of seismograms using waveforms of 50 earthquakes and 114 quarry and underwater blasts with magnitudes 1.0–2.8, recorded by ISN short-period stations at distances up to 200 km. The single-station spectral ratio of the low and high-frequency seismic energy shows an overlap between explosions and earthquakes. After averaging over a subnet of stations, the resolving power is enhanced and the two classes of events are separated. Different frequency bands were tested; the (1–3 Hz)/(6–8 Hz) ratio provided the best discriminant performance. We also estimated normalized r.m.s. spectral amplitudes in several sequential equal frequency windows within the 1–12 Hz band and applied multiparametric automatic classification procedures (Linear Discrimination Function and Artificial Neural Network) to the amplitudes averaged over a subnetwork. A leave-one-out test showed a low rate of error for the multiparametric procedures. An innovative multi-station discriminant is proposed, based on spectral modulation associated with ripple-firing in quarry blasts and with the bubbling effect in underwater explosions. It utilizes a distinct azimuth-invariant coherency of spectral shapes for different stations in the frequency range (1–12 Hz). The coherency is measured by semblance statistics commonly used in seismic prospecting for phase correlation in the time domain. After modification, the statistics applied to the network spectra provided event separation. A new feature of all the above mentioned procedures is that they are based on smoothed (0.5 Hz window), instrument-corrected FFT spectra of the whole signal; they are robust to the accuracy of onset time estimation and, thus well suited to automatic event identification.     

Hilbert-Huang变换在密频结构阻尼识别中的应用

Hilbert—Huang变换是一种新的数据处理方法，由经验模分解(Empirical Mode Decomposition)技术及Hilbert变换两部分组成。本文研究此方法对于密频结构阻尼识别的应用。首先对于两自由度系统模型，说明该方法用于阻尼识别的步骤。进而研究存在频率密集现象的高层建筑的阻尼识别问题。上述结果与理论值及由半功率带宽法的识别值进行了比较，对比显示Hilbert．Huang方法较传统方法具有良好的识别密频结构阻尼的性能，适用于大型结构的系统识别。     

基于实测重力异常和地形数据确定重力梯度的研究

本文利用澳大利亚北领地West Arnhem Land 地区实测重力异常数据并联合DEM(9")和SRTM3(3")地形高程数据,使用移去-恢复技术和Stokes积分方法计算了该地区两条剖面的重力梯度及其功率谱密度,使用FFT方法解算了整个地区的重力梯度值,结果证明了联合重力异常数据和高分辨率地形高程数据能有效地提高重力梯度的解算精度;功率谱密度的计算结果与国外成熟的重力梯度功率谱密度模型相吻合,表明高于0.3 Hz频率范围的功率谱密度可看做噪声,为重力梯度数据处理中噪声的辨别和剔除提供了借鉴,另外对重力梯度辅助导航基准图的构建以及重力梯度测量系统的标定提供了有益的探索.     

时频域油气储层低频阴影检测

为了准确刻画地震信号的局部层次结构,实现高效率的三维地震资料瞬时谱分解,检测油气储层的低频阴影,构造了广义S变换.广义S变换通过引入两个参数,改造S变换的小波函数,使其小波能根据信号处理的具体应用需要而调整.模型信号的仿真发现,广义S变换具有更加优越和灵活可调的时频聚集性能.文中分析了低频阴影的机理,并利用广义S变换对三维实际地震资料进行了瞬时谱分解,它不仅能检测油气储层的低频阴影,而且可以刻画油气储层的岩性边界和空间展布,减小油气储层检测的多解性.     

Statistical Analysis and Modeling of the Local Ionospheric Critical Frequency: A Mid-latitude Single-Station Model for Use in Forecasting

The hourly values of the F-layer critical frequency from the ionospheric sounder in Dourbes (50.1°N, 4.6°E) during the time interval from 1957 to 2010, comprising five solar cycles, were analyzed for the effects of the solar activity. The hourly time series were reduced to hourly monthly medians which in turn were used for fitting a single station foF₂ monthly median model. Two functional approaches have been investigated: a statistical approach and a spectral approach. The solar flux F_10.7 is used to model the dependence of foF₂ on the solar activity and is incorporated into both models by a polynomial expression. The statistical model employs polynomial functions to fit the F-layer critical frequency while the spectral model is based on spectral decomposition of the measured data and offers a better physical interpretation of the fitting parameters. The daytime and nighttime foF₂ values calculated by both approaches are compared during high and low solar activity. In general, the statistical model has a slightly lower uncertainty at the expense of the larger number of fitting parameters. However, the spectral approach is superior for modeling the periodic effects and performs better when comparing the results for high and low solar activity. Comparison with the International Reference Ionosphere (IRI 2012) shows that both local models are better at describing the local values of the F-layer critical frequency.     

New algorithms of emission tomography for passive seismic monitoring of a producing hydrocarbon deposit: Part I. Algorithms of processing and numerical simulation

Two new algorithms of seismic emission tomography and the results of their numerical testing are presented. The algorithms allow eliminating of the screening effect caused by spatially correlated noise, and imaging of deep weak sources. Both algorithms invoke spatial filters, calculated on the basis of singular decomposition of the spectral matrix of the wave field. The key parameter of such a filter is the number of eigenvectors of the spectral matrix, which must be rejected in the process of seismic emission imaging in order to eliminate the screening effect. Consecutive increasing in the number of rejected eigenvectors enables imaging of ever weaker seismic sources.     

New algorithms of emission tomography for passive seismic monitoring of a producing hydrocarbon deposit: Part II. Results of real data processing

Two new algorithms of seismic emission tomography and the results of their numerical testing are presented. The algorithms allow eliminating of the screening effect caused by spatially correlated noise, and imaging of deep weak sources. Both algorithms invoke spatial filters, calculated on the basis of singular decomposition of the spectral matrix of the wave field. The key parameter of such a filter is the number of eigenvectors of the spectral matrix, which must be rejected in the process of seismic emission imaging in order to eliminate the screening effect. Consecutive increasing in the number of rejected eigenvectors enables imaging of ever weaker seismic sources.