基于频率域峰值属性的河道砂体定量预测及应用(英文)
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摘要
河道砂体是陆相含油气盆地最重要的储集类型之一,其边界识别和厚度定量预测是储层预测的热点难题。本文在总结现有方法技术的基础上,提出一种利用频率域峰值属性进行河道砂体边界识别和厚度定量预测的新方法。对典型河道薄砂体地震反射进行了正演模拟,构造了一种新的地震属性——峰值频率-振幅比,研究表明:峰值频率属性对地层厚度变化敏感,振幅属性对地层岩性变化敏感,两者比值突出河道砂体的边界,同时,借助峰值频率与薄层厚度间存在的定量关系进行薄砂体厚度计算。实际数据应用表明,地震峰值频率属性可以较好的刻画河道的平面展布特征;峰值频率-振幅比属性可以提高对河道砂体边界的识别能力;利用频率域地震属性进行砂体边界识别及厚度定量预测是可行的。
The boundary identification and quantitative thickness prediction of channel sand bodies are always difficult in seismic exploration.We present a new method for boundary identification and quantitative thickness prediction of channel sand bodies based on seismic peak attributes in the frequency domain.Using seismic forward modeling of a typical thin channel sand body,a new seismic attribute-the ratio of peak frequency to amplitude was constructed.Theoretical study demonstrated that seismic peak frequency is sensitive to the thickness of the channel sand bodies,while the amplitude attribute is sensitive to the strata lithology.The ratio of the two attributes can highlight the boundaries of the channel sand body.Moreover,the thickness of the thin channel sand bodies can be determined using the relationship between seismic peak frequency and thin layer thickness.Practical applications have demonstrated that the seismic peak frequency attribute can depict the horizontal distribution characteristics of channels very well.The ratio of peak frequency to amplitude attribute can improve the identification ability of channel sand body boundaries.Quantitative prediction and boundary identification of channel sand bodies with seismic peak attributes in the frequency domain are feasible.
The boundary identification and quantitative thickness prediction of channel sand bodies are always difficult in seismic exploration.We present a new method for boundary identification and quantitative thickness prediction of channel sand bodies based on seismic peak attributes in the frequency domain.Using seismic forward modeling of a typical thin channel sand body,a new seismic attribute-the ratio of peak frequency to amplitude was constructed.Theoretical study demonstrated that seismic peak frequency is sensitive to the thickness of the channel sand bodies,while the amplitude attribute is sensitive to the strata lithology.The ratio of the two attributes can highlight the boundaries of the channel sand body.Moreover,the thickness of the thin channel sand bodies can be determined using the relationship between seismic peak frequency and thin layer thickness.Practical applications have demonstrated that the seismic peak frequency attribute can depict the horizontal distribution characteristics of channels very well.The ratio of peak frequency to amplitude attribute can improve the identification ability of channel sand body boundaries.Quantitative prediction and boundary identification of channel sand bodies with seismic peak attributes in the frequency domain are feasible.
引文
Alamsyah,M. N.,Marmosuwito,S.,Sutjiningsih,W.,and Marpaung,L. P.,2008,Seismic reservoir characterization of Indonesia’s Southwest Betara Field: The Leading Edge,27(12),1598 - 1607.
Chung,H. M.,and Lawton,D. C.,1995,Amplitude responses of thin beds: Sinusoidal approximation versus Ricker approximation: Geophysics,60(3),223 - 230.
Cao,Q. R.,Li,P.,Sun,K. and Li,N.,2007,Using seismicattributes to identify channel sand body: LithologicReservoirs,19(2),93 - 96.
Connolly,P.,and Kemper,M.,2007,A simple,robust algorithm for seismic net pay estimation: The Leading Edge,26(10),1278 - 1282.
Gridley,J. A.,and Partyka,G. A.,1997,Processing and interpretational aspects of spectral decomposition: 67th Ann. Internat. Mtg.,Soc. Expl. Geophys.,Expanded Abstracts,1055 - 1058.
Ji,T. Z.,Yang,Y. J.,and Li,S. L.,2003,Application of coherence technology in the prediction of channel sand: Geophysical Prospecting for Petroleum,42(3),309 - 401.
Long,J. D.,1995,Neural network BP modeling of therelation between thin bed thickness and amplitude andfrequency: Oil Geophysical Prospecting,30(6),817 -822.
Partyka,G. A.,Gridley,J. A.,and Lopez,J. A.,1999,Interpretational aspects of spectral decomposition in reservoir characterization: The Leading Edge,18(3),353 - 360.
Ricker,N.,1953,Wavelet contraction,wavelet expansionand the control of seismic resolution: Geophysics,18(4)769 - 792.
Sun,L. P.,Zheng,X. D.,Li,J. S.,and Shou,H.,2009,Thin-bed thickness calculation formula and its approximation using peak frequency: Applied Geophysics,6(3),234 - 240.
Wang,Z. J.,and Huang,J. B.,2006,Identification of micro-fault and sand body by using coherence technique and 3-D visualization: Oil Geophysical Prospecting,36(3),378 - 381.
Wang,J.,Chen,Y. L.,and Guo,B. X.,2005,3-D visualization interpretation technique of channels: Oil Geophysical Prospecting,40(6),677 - 681.
Widess,M. B.,1973,How thin is a thin bed: Geophysics,38,1176 - 1180.
Yao,F. C.,and Gan,L. D.,2000,Application and restriction of seismic inversion: Petroleum Exploration and Development,27(2),53 - 56.
Ye,T. R.,Su,J. Y.,and Liu,X. Y.,2008,Application of seismic frequency division interpretation technology in predicting continental sandstone reservoir in the west of Sichuan province: Geophysical Prospecting for Petroleum,47(1),72 - 76.
Yin,X. Y.,Zhang,K.,and Zhang,G. Z.,2003,Application of joint time-frequency distribution and its attribution: Oil Geophysical Prospecting,38(5),522 - 526.
Zhao,Z. Z.,Zhao,X. Z.,and Wang,Y. M.,2005,The theory and application of seismic reservoir prediction: Science Press,Beijing.
Zhang,M. Z.,Yin,X. Y.,Yang,C. C.,Tan,M. Y.,and Song,Y. F.,2007,3D seismic description for meander sediment micro-facies: Petroleum Geophysics,5(1),39 - 42.
Zhuang,D. H.,and Xiao,C. Y.,1996,Thin-bed thickness estimation using neural network: Oil Geophysical Prospecting,31(3),394 - 399.
Chung,H. M.,and Lawton,D. C.,1995,Amplitude responses of thin beds: Sinusoidal approximation versus Ricker approximation: Geophysics,60(3),223 - 230.
Cao,Q. R.,Li,P.,Sun,K. and Li,N.,2007,Using seismicattributes to identify channel sand body: LithologicReservoirs,19(2),93 - 96.
Connolly,P.,and Kemper,M.,2007,A simple,robust algorithm for seismic net pay estimation: The Leading Edge,26(10),1278 - 1282.
Gridley,J. A.,and Partyka,G. A.,1997,Processing and interpretational aspects of spectral decomposition: 67th Ann. Internat. Mtg.,Soc. Expl. Geophys.,Expanded Abstracts,1055 - 1058.
Ji,T. Z.,Yang,Y. J.,and Li,S. L.,2003,Application of coherence technology in the prediction of channel sand: Geophysical Prospecting for Petroleum,42(3),309 - 401.
Long,J. D.,1995,Neural network BP modeling of therelation between thin bed thickness and amplitude andfrequency: Oil Geophysical Prospecting,30(6),817 -822.
Partyka,G. A.,Gridley,J. A.,and Lopez,J. A.,1999,Interpretational aspects of spectral decomposition in reservoir characterization: The Leading Edge,18(3),353 - 360.
Ricker,N.,1953,Wavelet contraction,wavelet expansionand the control of seismic resolution: Geophysics,18(4)769 - 792.
Sun,L. P.,Zheng,X. D.,Li,J. S.,and Shou,H.,2009,Thin-bed thickness calculation formula and its approximation using peak frequency: Applied Geophysics,6(3),234 - 240.
Wang,Z. J.,and Huang,J. B.,2006,Identification of micro-fault and sand body by using coherence technique and 3-D visualization: Oil Geophysical Prospecting,36(3),378 - 381.
Wang,J.,Chen,Y. L.,and Guo,B. X.,2005,3-D visualization interpretation technique of channels: Oil Geophysical Prospecting,40(6),677 - 681.
Widess,M. B.,1973,How thin is a thin bed: Geophysics,38,1176 - 1180.
Yao,F. C.,and Gan,L. D.,2000,Application and restriction of seismic inversion: Petroleum Exploration and Development,27(2),53 - 56.
Ye,T. R.,Su,J. Y.,and Liu,X. Y.,2008,Application of seismic frequency division interpretation technology in predicting continental sandstone reservoir in the west of Sichuan province: Geophysical Prospecting for Petroleum,47(1),72 - 76.
Yin,X. Y.,Zhang,K.,and Zhang,G. Z.,2003,Application of joint time-frequency distribution and its attribution: Oil Geophysical Prospecting,38(5),522 - 526.
Zhao,Z. Z.,Zhao,X. Z.,and Wang,Y. M.,2005,The theory and application of seismic reservoir prediction: Science Press,Beijing.
Zhang,M. Z.,Yin,X. Y.,Yang,C. C.,Tan,M. Y.,and Song,Y. F.,2007,3D seismic description for meander sediment micro-facies: Petroleum Geophysics,5(1),39 - 42.
Zhuang,D. H.,and Xiao,C. Y.,1996,Thin-bed thickness estimation using neural network: Oil Geophysical Prospecting,31(3),394 - 399.
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