基于频变AVO技术对多尺度裂缝内流体属性反演与识别（英文）
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摘要
通过地震数据获取裂缝储藏中流体的性质并对流体类型进行识别,是地震勘探岩性反演的重要问题之一。由于地震波的速度、储层的密度等弹性参数对某些流体不具有很强的敏感性,使只依赖振幅信息进行流体识别的传统AVO方法面临困境。作为传统叠前振幅反演的一个拓展,频变AVO(FDAVO)技术进一步考虑了振幅对频率的依赖关系,将这种依赖关系与地下裂缝结构、流体填充对应起来,能带来更丰富的流体信息。利用该技术,本文提出了一种基于地震数据参数化Chapman模型的贝叶斯反演新方法(BIDCMP),它包含两步算法,即,FDAVO反演储层的非弹性属性和贝叶斯框架下的流体识别。首先,通过匹配观测数据和模型数据,构造差函数反演裂缝储层非弹性参数。随后,在贝叶斯框架下,使用马尔科夫随机场(MRF)作为先验模型,联合多参数场识别流体。本方法在计算过程中,除综合考虑了弹性参数场、测井资料等常规信息外,还特别地加人了第一步中反演得的非弹性参数的约束,从而充分利用了流体粘性差异,最后在最大后验概率(MAP)准则下输出最佳岩性一流体识别结果。分别对合成地震记录和模拟岩性—流体剖面验证本文方法的有效性,结果证明本文方法获得的流体识别结果准确可信。
A key problem in seismic inversion is the identification of the reservoir fluids. Elastic parameters, such as seismic wave velocity and formation density, do not have sufficient sensitivity, thus, the conventional amplitude-versus-offset(AVO) method is not applicable. The frequency-dependent AVO method considers the dependency of the seismic amplitude to frequency and uses this dependency to obtain information regarding the fluids in the reservoir fractures. We propose an improved Bayesian inversion method based on the parameterization of the Chapman model. The proposed method is based on 1) inelastic attribute inversion by the FDAVO method and 2) Bayesian statistics for fluid identification. First, we invert the inelastic fracture parameters by formulating an error function, which is used to match observations and model data. Second, we identify fluid types by using a Markov random field a priori model considering data from various sources, such as prestack inversion and well logs. We consider the inelastic parameters to take advantage of the viscosity differences among the different fluids possible. Finally, we use the maximum posteriori probability for obtaining the best lithology/fluid identification results.
A key problem in seismic inversion is the identification of the reservoir fluids. Elastic parameters, such as seismic wave velocity and formation density, do not have sufficient sensitivity, thus, the conventional amplitude-versus-offset(AVO) method is not applicable. The frequency-dependent AVO method considers the dependency of the seismic amplitude to frequency and uses this dependency to obtain information regarding the fluids in the reservoir fractures. We propose an improved Bayesian inversion method based on the parameterization of the Chapman model. The proposed method is based on 1) inelastic attribute inversion by the FDAVO method and 2) Bayesian statistics for fluid identification. First, we invert the inelastic fracture parameters by formulating an error function, which is used to match observations and model data. Second, we identify fluid types by using a Markov random field a priori model considering data from various sources, such as prestack inversion and well logs. We consider the inelastic parameters to take advantage of the viscosity differences among the different fluids possible. Finally, we use the maximum posteriori probability for obtaining the best lithology/fluid identification results.
引文
Aki,K.,and Richards,P.G.,2002,Quantitative Seismology:Univ.Science Books.
Al-Harrasi,O.H.,Kendall,J.M.,and Chapman,M.,2011,Fracture characterization using frequency-dependents hear wave anisotropy analysis of microseismic data,Geophysical Journal International.,185(2),1059–1070.
Besag,J.,1974,Spatial interaction and the statistical analysis of lattice systems:Journal of the Royal Statistical Society,36(2),192–236.
Bi,L.F.,Qian,Z.P.,Zhang,F.,Chen,X.Y.,Han,S.C.,and Chapman,M.,2011,Application of seismic anisotropy fluid detection technology in the Ken 71 well block of Shengli Oilfield:Applied Geophysics,8(2),117–124.
Biot,M.A.,1956,Theory of propagation of elastic wavesin a fluid-saturated porous solid.I.Low-frequency range:The Journal of the Acoustical Society of America,28(2),168–178.
Chapman,M.,Liu,E.,and Li,X.Y.,2005,The influence of abnormally high reservoir attenuation on the AVO signature:The Leading Edge,24(11),1120–1125.
Chapman,M.,S.Maultzsch,Liu,E.,and Li,X.Y.,2003,The effect of fluid saturation in an anisotropic multi-scaleequant porosity model:Journal of Applied Geophysics,54(3),191–202.
Chen,S.Q.,Li,X.Y.,and Wang,S.X.,2012,The analysis off requency-dependent characteristics for fluid detection:a physical model experiment:Applied Geophysics,9(2),195–206.
Eshelby,J.D.,1957,The determination of the elasticfield of an ellipsoidal inclusion,and related problems:Proceedings of the Royal Society of London.Series A.Mathematical and Physical Sciences,241(1226),376–396.
Gassmann,F.,1951,Elastic waves through a packing of spheres:Geophysics,16(4),673–685.
Guo,G.H.,Zhang,Z.,Jin,S.X.,Shi,S.H.,Cheng,J.W.,and Yan,J.P.,2013,Multi-scale fracture and fluid response characteristic in seismic data:Numerical simulation analysis:Chinese Journal of Geophysics,56(6),2002–2011.
Hudson,J.,Liu,E.,and Crampin,S.,1996,The mechanical properties of materials with interconnected cracks andpores:Geophysical Journal International,124(1),105–112.
Larsen,A.L.,Ulvmoen,M.,Omre,H.,and Buland,A.,2006,Bayesian lithology/fluid prediction and simulationon the basis of a Markov-chain prior model:Geophysics,71(5),R69–R78.
Ma,J.F.,2003,Forward modeling and inversion method of generalized elastic impedance in seismic exploration:Chinese Journal of Geophysics,46(1),118–124.
Mavko,G.,and Mukerji,T.,1995,Seismic pore space compressibility and Gassmann’s relation:Geophysics,60(6),1743–1749.
Morozov,I.B.,and Ma,J.,2009,Accurate poststack acoustic-impedance inversion by well-log calibration:Geophysics,74(5),R59–R67.
Perez,P.,1998,Markov random fields and images:CWI quarterly,11(4),413–437.
Qian,Z.,Chapman,M.,Li,X.Y.,Dai,H.C.,Liu,E.,Zhang,Y.,and Wang,Y.,2007,Use of multicomponentseismic data for oil-water discrimination in fractured reservoirs:The Leading Edge,26(9),1176–1184.
Schoenberg,M.,and Sayers,C.M.,1995,Seismicanisotropy of fractured rock:Geophysics,60(1),204–211.
Sun,Z.,Yang,P.,Zhou,X.,Tian,J.,and Han,J.,2013,Fluid Identification Based on P-Wave FrequencyDependent Azimuthal AVO Method in Fractured Media:75th EAGE Conference and Exhibition,London,UK.
Thomsen,L.,1986,Weak elastic anisotropy:Geophysics,51(10),1954–1966.
Tian,Y.K.,Zhou,H.,Chen,H.M.,Zou,Y.M.,and Guan,S.J.,2013,Bayesian prestack seismic inversion with a selfadaptive Huber-Markov random-field edge protection scheme:Applied Geophysics,10(4),453–460.
Tian,Y.K.,Zhou,H.,and Yuan,S.Y.,2013,Lithologic discrimination method based on Markov random-field:Chinese Journal of Geophysics,56(4),1360–1368.
Ulvmoen,M.,and Omre H.,2010,Improved resolutionin Bayesian lithology/fluid inversion from prestack seismic data and well observations:Part 1–Methodology:Geophysics,75(2),R21–R35.
Wilson,A.,Chapman,M.,and Li,X.Y.,2009,Frequency dependent AVO inversion:79th Annual International Meeting,SEG Expanded Abstracts,28,341–345.
Wu,X.,2005,Frequency dependent AVO inversion using spectral decomposition techniques:Ph D Thesis,China University of Geosciences.
Wu,X.,Chapman,M.,Angerer,E.,and Li,X.,2013,Estimation of gas saturation changes from frequency dependent AVO analysis:75th EAGE Conference & Exhibition,London,UK.
Yuan,S.Y.,and Wang,S.X.,2013,Spectral sparse Bayesian learning reflectivity inversion:Geophysical Prospecting,61(4),735–746.
Yuan,S.Y.,and Wang,S.X.,2013,Edge-preserving noise reduction based on Bayesian inversion with directional difference constraints:Journal of Geophysics and Engineering,10(2),025001.
Yuan,S.Y.,Wang,S.X.,and Li,G.F.,2012,Random noise reduction using Bayesian inversion:Journal of Geophysics and Engineering,9(1),60–68.
Al-Harrasi,O.H.,Kendall,J.M.,and Chapman,M.,2011,Fracture characterization using frequency-dependents hear wave anisotropy analysis of microseismic data,Geophysical Journal International.,185(2),1059–1070.
Besag,J.,1974,Spatial interaction and the statistical analysis of lattice systems:Journal of the Royal Statistical Society,36(2),192–236.
Bi,L.F.,Qian,Z.P.,Zhang,F.,Chen,X.Y.,Han,S.C.,and Chapman,M.,2011,Application of seismic anisotropy fluid detection technology in the Ken 71 well block of Shengli Oilfield:Applied Geophysics,8(2),117–124.
Biot,M.A.,1956,Theory of propagation of elastic wavesin a fluid-saturated porous solid.I.Low-frequency range:The Journal of the Acoustical Society of America,28(2),168–178.
Chapman,M.,Liu,E.,and Li,X.Y.,2005,The influence of abnormally high reservoir attenuation on the AVO signature:The Leading Edge,24(11),1120–1125.
Chapman,M.,S.Maultzsch,Liu,E.,and Li,X.Y.,2003,The effect of fluid saturation in an anisotropic multi-scaleequant porosity model:Journal of Applied Geophysics,54(3),191–202.
Chen,S.Q.,Li,X.Y.,and Wang,S.X.,2012,The analysis off requency-dependent characteristics for fluid detection:a physical model experiment:Applied Geophysics,9(2),195–206.
Eshelby,J.D.,1957,The determination of the elasticfield of an ellipsoidal inclusion,and related problems:Proceedings of the Royal Society of London.Series A.Mathematical and Physical Sciences,241(1226),376–396.
Gassmann,F.,1951,Elastic waves through a packing of spheres:Geophysics,16(4),673–685.
Guo,G.H.,Zhang,Z.,Jin,S.X.,Shi,S.H.,Cheng,J.W.,and Yan,J.P.,2013,Multi-scale fracture and fluid response characteristic in seismic data:Numerical simulation analysis:Chinese Journal of Geophysics,56(6),2002–2011.
Hudson,J.,Liu,E.,and Crampin,S.,1996,The mechanical properties of materials with interconnected cracks andpores:Geophysical Journal International,124(1),105–112.
Larsen,A.L.,Ulvmoen,M.,Omre,H.,and Buland,A.,2006,Bayesian lithology/fluid prediction and simulationon the basis of a Markov-chain prior model:Geophysics,71(5),R69–R78.
Ma,J.F.,2003,Forward modeling and inversion method of generalized elastic impedance in seismic exploration:Chinese Journal of Geophysics,46(1),118–124.
Mavko,G.,and Mukerji,T.,1995,Seismic pore space compressibility and Gassmann’s relation:Geophysics,60(6),1743–1749.
Morozov,I.B.,and Ma,J.,2009,Accurate poststack acoustic-impedance inversion by well-log calibration:Geophysics,74(5),R59–R67.
Perez,P.,1998,Markov random fields and images:CWI quarterly,11(4),413–437.
Qian,Z.,Chapman,M.,Li,X.Y.,Dai,H.C.,Liu,E.,Zhang,Y.,and Wang,Y.,2007,Use of multicomponentseismic data for oil-water discrimination in fractured reservoirs:The Leading Edge,26(9),1176–1184.
Schoenberg,M.,and Sayers,C.M.,1995,Seismicanisotropy of fractured rock:Geophysics,60(1),204–211.
Sun,Z.,Yang,P.,Zhou,X.,Tian,J.,and Han,J.,2013,Fluid Identification Based on P-Wave FrequencyDependent Azimuthal AVO Method in Fractured Media:75th EAGE Conference and Exhibition,London,UK.
Thomsen,L.,1986,Weak elastic anisotropy:Geophysics,51(10),1954–1966.
Tian,Y.K.,Zhou,H.,Chen,H.M.,Zou,Y.M.,and Guan,S.J.,2013,Bayesian prestack seismic inversion with a selfadaptive Huber-Markov random-field edge protection scheme:Applied Geophysics,10(4),453–460.
Tian,Y.K.,Zhou,H.,and Yuan,S.Y.,2013,Lithologic discrimination method based on Markov random-field:Chinese Journal of Geophysics,56(4),1360–1368.
Ulvmoen,M.,and Omre H.,2010,Improved resolutionin Bayesian lithology/fluid inversion from prestack seismic data and well observations:Part 1–Methodology:Geophysics,75(2),R21–R35.
Wilson,A.,Chapman,M.,and Li,X.Y.,2009,Frequency dependent AVO inversion:79th Annual International Meeting,SEG Expanded Abstracts,28,341–345.
Wu,X.,2005,Frequency dependent AVO inversion using spectral decomposition techniques:Ph D Thesis,China University of Geosciences.
Wu,X.,Chapman,M.,Angerer,E.,and Li,X.,2013,Estimation of gas saturation changes from frequency dependent AVO analysis:75th EAGE Conference & Exhibition,London,UK.
Yuan,S.Y.,and Wang,S.X.,2013,Spectral sparse Bayesian learning reflectivity inversion:Geophysical Prospecting,61(4),735–746.
Yuan,S.Y.,and Wang,S.X.,2013,Edge-preserving noise reduction based on Bayesian inversion with directional difference constraints:Journal of Geophysics and Engineering,10(2),025001.
Yuan,S.Y.,Wang,S.X.,and Li,G.F.,2012,Random noise reduction using Bayesian inversion:Journal of Geophysics and Engineering,9(1),60–68.
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