流体检测频变特征分析:以物理模型数据为例(英文)
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摘要
Chapman多尺度岩石物理模型研究认为,不同流体类型饱和的地震响应特征表现为不同的频率变化特征。第一类AVO类型的储层含气地震响应,频谱能量向高频移动形成"高频亮点",第三类AVO类型的储层含油气后的地震响应特征为"低频阴影"。本文以物理模型数据为例,通过频变地震响应特征分析,验证了Chapman第一类AVO响应的"高频亮点"的结果。以实际地质参数为背景,设计砂泥岩薄互层物理模型,分别进行固定炮检距和二维观测得到含不同类型流体的地震数据,采用谱分解技术分析了薄互层物理模型在含气、含水和含油时的频变地震响应特征。物理模型数据处理与分析结果表明,控制地震响应频谱特征的主要机制包括反射波调谐效应和与流体相关的衰减或频散特征。其次,通过对地震数据频变特征分析,可以将第一类AVO储层含气后的频变异常与含水或含油区分开。物理模型实例数据分析证实了不同流体充填后所产生的频谱响应特征异常,因此,通过对实际地震数据的细致分析,可以得到流体类型变化引起的频谱特征异常,实现利用地震数据进行流体检测。
According to the Chapman multi-scale rock physical model, the seismic response characteristics vary for different fluid-saturated reservoirs. For class I AVO reservoirs and gas-saturation, the seismic response is a high-frequency bright spot as the amplitude energy shifts. However, it is a low-frequency shadow for the Class III AVO reservoirs saturated with hydrocarbons. In this paper, we verified the high-frequency bright spot results of Chapman for the Class I AVO response using the frequency-dependent analysis of a physical model dataset. The physical model is designed as inter-bedded thin sand and shale based on real field geology parameters. We observed two datasets using fixed offset and 2D geometry with different fluid- saturated conditions. Spectral and time-frequency analyses methods are applied to the seismic datasets to describe the response characteristics for gas-, water-, and oil-saturation. The results of physical model dataset processing and analysis indicate that reflection wave tuning and fluid-related dispersion are the main seismic response characteristic mechanisms. Additionally, the gas saturation model can be distinguished from water and oil saturation for Class I AVO utilizing the frequency-dependent abnormal characteristic. The frequency-dependent characteristic analysis of the physical model dataset verified the different spectral response characteristics corresponding to the different fluid-saturated models. Therefore, by careful analysis of real field seismic data, we can obtain the abnormal spectral characteristics induced by the fluid variation and implement fluid detection using seismic data directly.
According to the Chapman multi-scale rock physical model, the seismic response characteristics vary for different fluid-saturated reservoirs. For class I AVO reservoirs and gas-saturation, the seismic response is a high-frequency bright spot as the amplitude energy shifts. However, it is a low-frequency shadow for the Class III AVO reservoirs saturated with hydrocarbons. In this paper, we verified the high-frequency bright spot results of Chapman for the Class I AVO response using the frequency-dependent analysis of a physical model dataset. The physical model is designed as inter-bedded thin sand and shale based on real field geology parameters. We observed two datasets using fixed offset and 2D geometry with different fluid- saturated conditions. Spectral and time-frequency analyses methods are applied to the seismic datasets to describe the response characteristics for gas-, water-, and oil-saturation. The results of physical model dataset processing and analysis indicate that reflection wave tuning and fluid-related dispersion are the main seismic response characteristic mechanisms. Additionally, the gas saturation model can be distinguished from water and oil saturation for Class I AVO utilizing the frequency-dependent abnormal characteristic. The frequency-dependent characteristic analysis of the physical model dataset verified the different spectral response characteristics corresponding to the different fluid-saturated models. Therefore, by careful analysis of real field seismic data, we can obtain the abnormal spectral characteristics induced by the fluid variation and implement fluid detection using seismic data directly.
引文
Aki, K., and Richards, P. G., 1980, Quantitative seismology:W. H. Freeman & Co.
Biot, M. A., 1956a, Theory of propagation of elastic wavesin a fluid saturated porous solid - I: low frequency range:J. Acoust. Soc. Am., 28, 168 – 178.
Biot, M. A., 1956b, Theory of propagation of elastic wavesin a fluid saturated porous solid - II: high frequencyrange: J. Acoust. Soc. Am., 28, 179 – 191.
Biot, M. A., 1962, Generalized theory of acoustic propagation in porous dissipative media: J. Acoust. Soc.Am., 34, 1254 – 1264.
Castagna, J. P., 1993, Petrophysical imaging using AVO:The Leading Edge, 12, 172 – 178.
Castagna, J. P., Sun, S. and Seigfried, R.W., 2003,Instantaneous spectral analysis: Detection of low-frequency shadows associated with hydrocarbons: TheLeading Edge, 22, 120 – 127.
Chapman, M., Zatsepin, S. V., and Crampin, S., 2002,Derivation of a microstructural poroelasticity model:Geophys. J. Int., 151, 427 – 451.
Chapman, M., 2003, Frequency dependent anisotropydue to meso-scale fractures in the presence of equantporosity: Geophysical Prospecting, 51, 369 – 379.
Chapman, M., Liu, E., and Li, X. Y., 2005, The influence of abnormally high reservoir attenuation on the AVOsignature: The Leading Edge, 24, 1120 – 1125.
Chapman, M., Liu, E., and Li, X. Y., 2006, The influence of fluid-sensitive dispersion and attenuation on AVOanalysis: Geophys. J. Int., 167, 89 – 105.
Ebrom, D., 2004, The low-frequency gas shadow onseismic sections: The Leading Edge, 23, 772.
Gassmann, F., 1951, über die Elastizit t poroser Medien:Veirteljahrsschrift der Naturforschenden Gesellschaft inZürich, 96, 1 – 23.
Goloshubin, G., and Schuyver, C. V., 2006, Reservoirimaging using low frequencies of seismic reflections:The Leading Edge, 25, 527 – 531.
Kan, T. K., Batzle, M. L., and Gaiser, J. E., 1983,Attenuation measured from VSP: Evidence of frequency-dependent Q: 53rd Ann. Internat. Mtg., Soc. Explor.Geophys., Expanded Abstracts, 589 – 590.
Korneev, V., Goloshubin, G., Daley, T., and Silin, D., 2004,Seismic low-frequency effects in monitoring fluid-saturated reservoirs: Geophysics, 69, 522 – 532.
Liu, E., and Chapman, M., 2006, Comparison of spectral decomposition techniques for evaluating frequency-dependent variations in seismic data: EdinburghAnisotropy Project Annual Report, Section C: Frequency-dependent anisotropy.
Mavko , G., and Nur, A., 1975, Melt squirt in the asthenosphere: J. Geophys. Res., 80, 1444 – 1448.
Murphy, W. F., 1984, Acoustic measures of partial gassaturation in tight sandstones: J. Geophys. Res., 89,11549 – 11559.
Odebeatu, E., Zhang, J., Chapman, M., Liu, E., and Li, X. Y.,2006, Application of spectral decomposition to detectionof dispersion anomalies associated with gas saturation:The Leading Edge, 25, 206 – 210.
Partyka, G., Gridley, J., and Lopez, J., 1999, Interpretationalapplications of spectral decomposition in reservoircharacterization: The Leading Edge, 18, 353 – 360.
Swan, H., 1991, Amplitude-versus-offset measure menterrors in a finely layered medium: Geophysics, 56, 41 –49.
Taner, M. T., Koehler, F., and Sheriff, R. E., 1979, Complexseismic trace analysis: Geophysics, 44, 1041 – 1063.
Wu, X., and Liu, T., 2009, Time-frequency analysis on Wigner-Ville distribution of seismic signal basedon time-frequency rearrangement: Oil GeophysicalProspecting, 44(2), 201 – 205.
Zhao, B., Johnston, D., and Gouvela, W., 2006, Spectralde composition of 4D seismic data: 76th Ann. Internat.Mtg., Soc. Expl. Geophys., Expanded Abstracts, 3235 –3239.
Biot, M. A., 1956a, Theory of propagation of elastic wavesin a fluid saturated porous solid - I: low frequency range:J. Acoust. Soc. Am., 28, 168 – 178.
Biot, M. A., 1956b, Theory of propagation of elastic wavesin a fluid saturated porous solid - II: high frequencyrange: J. Acoust. Soc. Am., 28, 179 – 191.
Biot, M. A., 1962, Generalized theory of acoustic propagation in porous dissipative media: J. Acoust. Soc.Am., 34, 1254 – 1264.
Castagna, J. P., 1993, Petrophysical imaging using AVO:The Leading Edge, 12, 172 – 178.
Castagna, J. P., Sun, S. and Seigfried, R.W., 2003,Instantaneous spectral analysis: Detection of low-frequency shadows associated with hydrocarbons: TheLeading Edge, 22, 120 – 127.
Chapman, M., Zatsepin, S. V., and Crampin, S., 2002,Derivation of a microstructural poroelasticity model:Geophys. J. Int., 151, 427 – 451.
Chapman, M., 2003, Frequency dependent anisotropydue to meso-scale fractures in the presence of equantporosity: Geophysical Prospecting, 51, 369 – 379.
Chapman, M., Liu, E., and Li, X. Y., 2005, The influence of abnormally high reservoir attenuation on the AVOsignature: The Leading Edge, 24, 1120 – 1125.
Chapman, M., Liu, E., and Li, X. Y., 2006, The influence of fluid-sensitive dispersion and attenuation on AVOanalysis: Geophys. J. Int., 167, 89 – 105.
Ebrom, D., 2004, The low-frequency gas shadow onseismic sections: The Leading Edge, 23, 772.
Gassmann, F., 1951, über die Elastizit t poroser Medien:Veirteljahrsschrift der Naturforschenden Gesellschaft inZürich, 96, 1 – 23.
Goloshubin, G., and Schuyver, C. V., 2006, Reservoirimaging using low frequencies of seismic reflections:The Leading Edge, 25, 527 – 531.
Kan, T. K., Batzle, M. L., and Gaiser, J. E., 1983,Attenuation measured from VSP: Evidence of frequency-dependent Q: 53rd Ann. Internat. Mtg., Soc. Explor.Geophys., Expanded Abstracts, 589 – 590.
Korneev, V., Goloshubin, G., Daley, T., and Silin, D., 2004,Seismic low-frequency effects in monitoring fluid-saturated reservoirs: Geophysics, 69, 522 – 532.
Liu, E., and Chapman, M., 2006, Comparison of spectral decomposition techniques for evaluating frequency-dependent variations in seismic data: EdinburghAnisotropy Project Annual Report, Section C: Frequency-dependent anisotropy.
Mavko , G., and Nur, A., 1975, Melt squirt in the asthenosphere: J. Geophys. Res., 80, 1444 – 1448.
Murphy, W. F., 1984, Acoustic measures of partial gassaturation in tight sandstones: J. Geophys. Res., 89,11549 – 11559.
Odebeatu, E., Zhang, J., Chapman, M., Liu, E., and Li, X. Y.,2006, Application of spectral decomposition to detectionof dispersion anomalies associated with gas saturation:The Leading Edge, 25, 206 – 210.
Partyka, G., Gridley, J., and Lopez, J., 1999, Interpretationalapplications of spectral decomposition in reservoircharacterization: The Leading Edge, 18, 353 – 360.
Swan, H., 1991, Amplitude-versus-offset measure menterrors in a finely layered medium: Geophysics, 56, 41 –49.
Taner, M. T., Koehler, F., and Sheriff, R. E., 1979, Complexseismic trace analysis: Geophysics, 44, 1041 – 1063.
Wu, X., and Liu, T., 2009, Time-frequency analysis on Wigner-Ville distribution of seismic signal basedon time-frequency rearrangement: Oil GeophysicalProspecting, 44(2), 201 – 205.
Zhao, B., Johnston, D., and Gouvela, W., 2006, Spectralde composition of 4D seismic data: 76th Ann. Internat.Mtg., Soc. Expl. Geophys., Expanded Abstracts, 3235 –3239.
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