基于时频谱特征的薄互层分析
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摘要
如何用地震勘探更真实、更细致地刻画地下地质构造,寻找地下油气储层,一直是我们地球物理工作者坚持奋斗的目标。目前对薄层或薄互层储层研究成为热点,本文分析了几种提高地震勘探分辨率的方法,并应用于实际地震资料。
首先从理论上分析了薄互地层的反射系数在时域和频域的特征,设计了几个反射系数序列模型,对其进行傅立叶变换得到其频谱。在反射系数个数比较少时,其频域特征是十分明显的,该振幅谱为一多极值的周期谱,可以通过陷频法求出其准确的时间厚度。研究表明:薄层反射波的振幅强弱由物性差异决定,振幅谱的形态、峰值频率与反射系数极性有关;反射波的频谱是由入射子波的频谱和反射系数序列频谱的乘积所决定。在反射系数序列个数比较多,组合比较复杂时,其频谱形态变化较大。
时频分析法是非平稳信号分析的有效方法,在低频时获得较高的频率分辨率,在高频时获得较高的时间分辨率,将一维时间信号变换为二维时频谱。本文选取广义S变换作为时频分析工具,是因为其良好的时窗分辨能力和适应能力,其时窗的长度和大小都可以调节,对应于不同地震信号,只要改变时窗调节因子,即可获得其理想的时频谱,因此二维时频域滤波比常规的频率域滤波更具灵活性。在地震剖面上,由于地震信号的频率一般较低,所以通过时频分解后,我们可以提取较高单频剖面,薄层可以更较清晰地显示出来,复杂构造也可以刻画得更为精细。
谱分解技术因为其准确的薄层厚度求取能力已被广泛使用,本文参考Ethan J. Nowak等(2008)提出的,从AVO响应谱中得包含纵、横波信息的截距项和梯度项地震记录,联合进行互谱分解。从楔形模型上看,其互能量谱剖面的周期个数明显增多,频率峰值、频率零点更加接近于楔形反射系数模型的频谱,这样就更加有利于反演其薄层的时间厚度。由于其包含了纵波和横波的信息,所以其对薄层的时间分辨率大大提高了,比以往仅仅靠纵波谱分解(自谱分解)的分辨率提高整整一倍。
本文结合对薄互层反射系数的研究和广义S变换时频分析,对地震剖面进行高分辨重建。首先对地震剖面作频谱分析;其次对地震剖面作广义S变换,提取适合的单频剖面;然后对单频作频率补偿,即在时间域作两次微分(相当于在频率域乘以(i w )2),这样可以同时保留低频信息和突出高频的分辨率;最后对频谱作傅立叶逆变换,即得到高分辨重建后的剖面。通过人工模型和实际地震资料的检验,该方法在薄互层高分辨处理中得到较好效果。
本文对薄层、薄互层反射模型的时、频特征作了深入研究,计算薄层模型厚度对,分析其时频谱特征,提高其地震分辨率取得较好效果。然单一方法存在其自身缺陷,只有结合多种方法优点,才能更好地提高地震薄互层的分辨率。
How to describe the subsurface geologic structure much more truly and meticulous by seismic exploration and look for underground reservoir is the insistent struggling goal of geophysicist. Now it is a hotspot to research thin-layer or thin interbed. We has analyzed several methods of improving the resolution of seismic exploration and apply them to seismic data.
Firstly, we has analyzed the characteristics in time domain and frequency domain of the reflection coefficient of thin-layer in theory, and designed some reflection coefficient models, then obtained frequency spectrum by doing FT to these models. When there are few reflection coefficients, the characteristics of frequency are very clear. Its amplitude spectrum is a period spectrum with multi-extreme value and we can estimate the thickness accurately by notches-in-thin-bed. This study has proved that the amplitude of thin-layer reflection wave is determined by the difference of their properties. The form of amplitude spectrum and frequency-extreme relate with the polarity of reflection coefficient. The frequency spectrum of reflection wave is determined by product of frequency spectrum of incident wave and reflection coefficient. When the more reflection coefficients and the more complex combination, the larger change about frequency spectrum form.
Time-Frequency analysis is a very effective way to analyze non-stationary signal, it can obtain high frequency resolution in low-frequency and high time resolution in high-frequency. It can transform one-dimension time signal to two-dimension time-frequency spectrum. This paper has selected Generalized S Transform (GST) as time-frequency analysis tool, for it has higher resolution and better adaptability time window, and its length and size can adjust. For the different seismic data, we can obtain their time-frequency spectrum only through changing the parameters of time window. So the two-dimension time-frequency domain filter is much more flexible than normal frequency domain filter. In seismic cross-section because the frequency of seismic data is lower, after we do time-frequency decomposition for them, we can extract higher single-frequency section, the thin-layer can display more clearly and the complex structure can depict more fine.
Spectral-decomposition technique was used widely for its capability of accurate thin-layer thickness estimate. This paper has referenced the theory which Ethan. J. Nowak etc. (2008) put forward and combined the P and G section which contain s-wave and p-wave information from the spectral response of AVO to carry on cross-spectral decomposition. For the wedge model, the number of periods of cross-spectral has increased obviously, its frequency-extrema and frequency-notch are more close to the frequency spectrum of reflection coefficient, which becomes more helpful to inversion the thickness of thin-layer. The time resolution of thin-layer has been improved largely for the cross-spectral contained the information of p-wave and s-wave and it was nearly double times than auto-spectral decomposition’s resolution. When we process cross-spectral decomposition using real seismic data, it is the first step to inversion the P-section and G-section from the AVO.
This article has combined the study of thin-layer reflection coefficient with GST time-frequency analysis, reconstructed the high resolution seismic cross-section. At first, analyze the frequency spectrum of the seismic cross-section; secondly, do GST to this seismic data and choose suitable single-frequency sections; thirdly, compensate frequency to these single-frequency sections, that is, derivate these sections in time domain(equal to multiply (i w )2), in this way, it can keep the continuity of low-frequency and highlight the resolution of high-frequency; The last, do inverse Fourier transform to these frequency spectrum and then we can obtain the high resolution reconstruction section. The effect of this method in high resolution processing is clear after tested by artificial model and real seismic data.
This paper has studied thin-layer and thin interbed. We get some good effect on improving the resolution of seismic and estimating the thickness of thin-layer. However, single method is not more real and suitable for processing seismic data, only by combining these advantages of several methods, can we reconstruct high resolution seismic cross-section and get satisfactory result.
首先从理论上分析了薄互地层的反射系数在时域和频域的特征,设计了几个反射系数序列模型,对其进行傅立叶变换得到其频谱。在反射系数个数比较少时,其频域特征是十分明显的,该振幅谱为一多极值的周期谱,可以通过陷频法求出其准确的时间厚度。研究表明:薄层反射波的振幅强弱由物性差异决定,振幅谱的形态、峰值频率与反射系数极性有关;反射波的频谱是由入射子波的频谱和反射系数序列频谱的乘积所决定。在反射系数序列个数比较多,组合比较复杂时,其频谱形态变化较大。
时频分析法是非平稳信号分析的有效方法,在低频时获得较高的频率分辨率,在高频时获得较高的时间分辨率,将一维时间信号变换为二维时频谱。本文选取广义S变换作为时频分析工具,是因为其良好的时窗分辨能力和适应能力,其时窗的长度和大小都可以调节,对应于不同地震信号,只要改变时窗调节因子,即可获得其理想的时频谱,因此二维时频域滤波比常规的频率域滤波更具灵活性。在地震剖面上,由于地震信号的频率一般较低,所以通过时频分解后,我们可以提取较高单频剖面,薄层可以更较清晰地显示出来,复杂构造也可以刻画得更为精细。
谱分解技术因为其准确的薄层厚度求取能力已被广泛使用,本文参考Ethan J. Nowak等(2008)提出的,从AVO响应谱中得包含纵、横波信息的截距项和梯度项地震记录,联合进行互谱分解。从楔形模型上看,其互能量谱剖面的周期个数明显增多,频率峰值、频率零点更加接近于楔形反射系数模型的频谱,这样就更加有利于反演其薄层的时间厚度。由于其包含了纵波和横波的信息,所以其对薄层的时间分辨率大大提高了,比以往仅仅靠纵波谱分解(自谱分解)的分辨率提高整整一倍。
本文结合对薄互层反射系数的研究和广义S变换时频分析,对地震剖面进行高分辨重建。首先对地震剖面作频谱分析;其次对地震剖面作广义S变换,提取适合的单频剖面;然后对单频作频率补偿,即在时间域作两次微分(相当于在频率域乘以(i w )2),这样可以同时保留低频信息和突出高频的分辨率;最后对频谱作傅立叶逆变换,即得到高分辨重建后的剖面。通过人工模型和实际地震资料的检验,该方法在薄互层高分辨处理中得到较好效果。
本文对薄层、薄互层反射模型的时、频特征作了深入研究,计算薄层模型厚度对,分析其时频谱特征,提高其地震分辨率取得较好效果。然单一方法存在其自身缺陷,只有结合多种方法优点,才能更好地提高地震薄互层的分辨率。
How to describe the subsurface geologic structure much more truly and meticulous by seismic exploration and look for underground reservoir is the insistent struggling goal of geophysicist. Now it is a hotspot to research thin-layer or thin interbed. We has analyzed several methods of improving the resolution of seismic exploration and apply them to seismic data.
Firstly, we has analyzed the characteristics in time domain and frequency domain of the reflection coefficient of thin-layer in theory, and designed some reflection coefficient models, then obtained frequency spectrum by doing FT to these models. When there are few reflection coefficients, the characteristics of frequency are very clear. Its amplitude spectrum is a period spectrum with multi-extreme value and we can estimate the thickness accurately by notches-in-thin-bed. This study has proved that the amplitude of thin-layer reflection wave is determined by the difference of their properties. The form of amplitude spectrum and frequency-extreme relate with the polarity of reflection coefficient. The frequency spectrum of reflection wave is determined by product of frequency spectrum of incident wave and reflection coefficient. When the more reflection coefficients and the more complex combination, the larger change about frequency spectrum form.
Time-Frequency analysis is a very effective way to analyze non-stationary signal, it can obtain high frequency resolution in low-frequency and high time resolution in high-frequency. It can transform one-dimension time signal to two-dimension time-frequency spectrum. This paper has selected Generalized S Transform (GST) as time-frequency analysis tool, for it has higher resolution and better adaptability time window, and its length and size can adjust. For the different seismic data, we can obtain their time-frequency spectrum only through changing the parameters of time window. So the two-dimension time-frequency domain filter is much more flexible than normal frequency domain filter. In seismic cross-section because the frequency of seismic data is lower, after we do time-frequency decomposition for them, we can extract higher single-frequency section, the thin-layer can display more clearly and the complex structure can depict more fine.
Spectral-decomposition technique was used widely for its capability of accurate thin-layer thickness estimate. This paper has referenced the theory which Ethan. J. Nowak etc. (2008) put forward and combined the P and G section which contain s-wave and p-wave information from the spectral response of AVO to carry on cross-spectral decomposition. For the wedge model, the number of periods of cross-spectral has increased obviously, its frequency-extrema and frequency-notch are more close to the frequency spectrum of reflection coefficient, which becomes more helpful to inversion the thickness of thin-layer. The time resolution of thin-layer has been improved largely for the cross-spectral contained the information of p-wave and s-wave and it was nearly double times than auto-spectral decomposition’s resolution. When we process cross-spectral decomposition using real seismic data, it is the first step to inversion the P-section and G-section from the AVO.
This article has combined the study of thin-layer reflection coefficient with GST time-frequency analysis, reconstructed the high resolution seismic cross-section. At first, analyze the frequency spectrum of the seismic cross-section; secondly, do GST to this seismic data and choose suitable single-frequency sections; thirdly, compensate frequency to these single-frequency sections, that is, derivate these sections in time domain(equal to multiply (i w )2), in this way, it can keep the continuity of low-frequency and highlight the resolution of high-frequency; The last, do inverse Fourier transform to these frequency spectrum and then we can obtain the high resolution reconstruction section. The effect of this method in high resolution processing is clear after tested by artificial model and real seismic data.
This paper has studied thin-layer and thin interbed. We get some good effect on improving the resolution of seismic and estimating the thickness of thin-layer. However, single method is not more real and suitable for processing seismic data, only by combining these advantages of several methods, can we reconstruct high resolution seismic cross-section and get satisfactory result.
引文
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