指数匹配追踪谱分解技术在疏松砂岩气藏检测中的应用
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摘要
疏松砂岩储层是一种重要的储层类型,此类储层具有未固结沉积特征明显,胶结物含量少,胶结程度低,砂岩呈疏松状的特点,研究难度相当大。国内外很多学者采用AVO和衰减梯度等烃类检测方法对该类型储层进行预测,结果存在很大的不确定性。以柴达木盆地三湖地区的疏松砂岩为例,比较了各种谱分解方法的分辨能力,采用高精度的指数匹配追踪谱分解技术,利用含气地层对高频能量的吸收,含气储层的主频向低频移动的特点进行气藏检测。结果表明,该方法能够准确刻画地震信号在时频空间分布特征,能够有效检测三湖地区气藏位置,提供可钻探圈闭,具有很强的实际生产价值。
Unconsolidated sandstone reservoir was an important reservoir characterized by unconsolidated sedimentary,less cement,and low cementation,therefore it was very difficult for studying the reservoir.Some geophysicists both at home and abroad tried to predict this type of reservoir by using hydrocarbon detection methods such as AVO,and attenuation gradient,yet the result was highly uncertain.By tacking unconsolidated sandstone in Sanhu Region of Qaidam Basin for example,the resolution of several spectrum decomposition methods was compared and high precision index matching tracing spectral decomposition was used for hydrocarbon detection,the gas-bearing reservoirs were detected through the absorption of high frequency energy in gas-bearing formation and the dominant frequency shifting toward the low band.The result demonstrates that this method can accurately map seismic signal in time-frequency domain,and effectively predict gas reservoir location in Sanhu Region,which is valuable for trap positioning and drilling.
Unconsolidated sandstone reservoir was an important reservoir characterized by unconsolidated sedimentary,less cement,and low cementation,therefore it was very difficult for studying the reservoir.Some geophysicists both at home and abroad tried to predict this type of reservoir by using hydrocarbon detection methods such as AVO,and attenuation gradient,yet the result was highly uncertain.By tacking unconsolidated sandstone in Sanhu Region of Qaidam Basin for example,the resolution of several spectrum decomposition methods was compared and high precision index matching tracing spectral decomposition was used for hydrocarbon detection,the gas-bearing reservoirs were detected through the absorption of high frequency energy in gas-bearing formation and the dominant frequency shifting toward the low band.The result demonstrates that this method can accurately map seismic signal in time-frequency domain,and effectively predict gas reservoir location in Sanhu Region,which is valuable for trap positioning and drilling.
引文
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[2]Peyton L,Bottjer R,Partyka G.Interpretation of incised valleys using new 3Dseismic techniques;a case history using spectral decom-position and coherency[J].The Leading Edge,1998,17(9):1294～1298.
[3]Partyka G,Gridley J,Lopez J.Interpretational applications of spectral decomposition in reservoir characterization[J].The LeadingEdge,1999,18(3):353～360.
[4]Marfurt K J,Kirlin R L.Narrow band spectral analysis and thin bed tuning[J].Geophysics,2001,66(4):1274～1283.
[5]Castagna J P,Sun S,Siegfried R W.Instantaneous spectral analysis:Detection of low frequency shadows associated with hydrocarbons[J].The Leading Edge,2003,22(2):120～127.
[6]Sinha S,Routh P,Anno P,et al.Spectral decomposition of seismic data with continuous wavelet transform[J].Geophysics,2005,70(6):19～25.
[7]姜桂凤,孔红喜,侯泽生,等.柴达木盆地生物气资源潜力评价[J].新疆石油地质,2005,26(4):363～366.
[8]王西文,徐凤银,冯云发,等.三湖地区地震资料处理中的静校正方法研究[J].石油地球物理勘探,2007,42(5):572～580.
[9]张绍胜,曾富英,孔骅.柴达木盆地三湖地区地震异常分析[J].天然气工业,2007,27(增刊A):176～177.
[10]Temlyakov V N.Weak greedy algorithms[J].Adv Comput Math,2000,12(2,3):213～227.
[11]Temlyakov V N.Nonlinear Methods of Approximation[A].IMI Research Reports[C].Columbia:University of South Carolina,2001.
[12]DeVore R,Temlyakov V.Some remarks on greedy algorithms[J].Adv Comput Math,1996,5(2,3):173～187.
[13]赵天姿,宋炜,王尚旭.基于匹配追踪算法的时频滤波去噪方法[J].石油物探,2008,47(4):367～371.
[14]刘喜武,张宁,勾永峰,等.地震勘探信号时频分析方法对比与应用分析[J].地球物理学进展,2008,23(3):743～753.
[15]张宏.地震谱分解算法对比及不确定性分析[J].天然气工业,2007,27(增刊A):329～332.
[16]张德林.三湖地区天然气藏的地震信息特征与地质条件的研讨[J].石油地球物理勘探,2000,35(7):67～73.
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