滩坝砂岩储层地震预测方法及其应用
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摘要
本文针对滩坝砂岩薄层的地质和地震特征,研究了多方向分形分维方法和复数子波匹配追踪方法识别薄层砂体空间展布。同时,也研究了瞬时平均频率峰值预测滩坝砂岩薄层厚度的方法。在研究分形多种算法的基础上,针对滩坝砂的特征,研究了简化的多方向分形分维方法,经过模型论证,得到了滩坝砂薄层的横向上展布。针对多方向分形分维方法纵向上识别薄层砂岩能力较弱,研究了经过改进的复数子波匹配追踪方法。采用复数子波匹配追踪方法,经过模型论证,证明该方法能够从纵向识别滩坝砂薄层的地震信息。简化的多方向分维与改进的复数子波匹配追踪方法加快了计算速度,节省了计算时间。二者对于薄层砂体的识别相互补充,较好的识别出滩坝砂岩的空间展布。在复数子波匹配识别滩坝砂薄层的基础上,运用瞬时平均频率峰值理论预测薄层砂体的厚度,得到了较好的应用效果。
In this paper, for the geologic feature and seismic character of thinbeach-bar sand, I have studied the multi-direction fractal dimensionmethod and the matching pursuit complex wavelet method, aiming atrecognizing thespace distribution of the thin sandbody.At the same time,I have researched the instantaneous average frequency peak method topredict the thickness of thin beach-bar sandbody. For the feature ofbeach-bar sand, I have studied the simplified multi-direction fractaldimension method also, based on the research on various fractalalgorithms, and have obtained the horizontal distribution of thin beach-barsand by the proof of the model. Because of the poor ability of themulti-direction fractal dimension method in recognizing thin sand atlongitudinal direction, advanced matching pursuit complex waveletmethod is studied. After proof-texted by the model, this method can beproved that it does much better in recognizing seismic information of thinbeach-bar sand at longitudinal direction. Simplified multi-direction fractaldimension method and advanced matching pursuit complex waveletmethod compute much faster than before. Each of the methods can be a supplement to another, and do better in recognizing the space distributionof the beach-bar sand. Based on recognizing thin beach-bar sand withmatching pursuit complex wavelet method, the instantaneous averagefrequency peak method is applied to predict the thickness of thinbeach-bar sand, and preferable effect is obtained.
In this paper, for the geologic feature and seismic character of thinbeach-bar sand, I have studied the multi-direction fractal dimensionmethod and the matching pursuit complex wavelet method, aiming atrecognizing thespace distribution of the thin sandbody.At the same time,I have researched the instantaneous average frequency peak method topredict the thickness of thin beach-bar sandbody. For the feature ofbeach-bar sand, I have studied the simplified multi-direction fractaldimension method also, based on the research on various fractalalgorithms, and have obtained the horizontal distribution of thin beach-barsand by the proof of the model. Because of the poor ability of themulti-direction fractal dimension method in recognizing thin sand atlongitudinal direction, advanced matching pursuit complex waveletmethod is studied. After proof-texted by the model, this method can beproved that it does much better in recognizing seismic information of thinbeach-bar sand at longitudinal direction. Simplified multi-direction fractaldimension method and advanced matching pursuit complex waveletmethod compute much faster than before. Each of the methods can be a supplement to another, and do better in recognizing the space distributionof the beach-bar sand. Based on recognizing thin beach-bar sand withmatching pursuit complex wavelet method, the instantaneous averagefrequency peak method is applied to predict the thickness of thinbeach-bar sand, and preferable effect is obtained.
引文
[1] 刘伟，吕优良，徐徽等．东营凹陷南斜坡东段沙四上亚段沉积相与砂体展布研究．江汉石油学院学报，2004；26：23-26
[2] 张宇，唐东，周建国．东营凹陷缓坡带滩坝砂储层描述技术．油气地质与采收率，2005；4：14-15
[3] 孙锡年，刘渝，满燕．东营凹陷西部沙四段滩坝砂岩油气成藏条件．国外油田工程，2003；19：23-24
[4] 孙博玲．分形维数(Fractal dimension)及其测量方法．东北林业大学学报，2004；32：116-119
[5] B．曼得尔布洛特著．分形对象――形、机遇和维数.文志英苏虹译．北京：世界图书出版公司，1999：81-89
[6] 陈遵德．储层地震属性优化方法．北京：石油工业出版社，1998：25-34
[7] 申维．分形混沌与矿产预测．北京：地址出版社，2002：1-24
[8] 王才经．现代应用数学．山东东营：石油大学出版社，2004：16-29
[9] 田杰，陈杰，张宇河．基于小波变换及分形特征的目标检测与识别．北京理工大学学报，2003；23：95-99
[10] Nath S.K, Dewangan P. Detection of seismic reflections from seismicattributes through fractal analysis. GEOPHYSICALPROSPECTING,2002;50:341-360
[11] 王东生，曹磊．混沌、分形及其应用．合肥：中国科学技术大学出版社，1995：23-30
[12] 李建平．小波分析与信号处理．重庆：重庆出版社，1997：42-48
[13] 王真理，李衍达．基于小波的信号部分重构与插值．清华大学学报（自然科学版），1995（35）：67-72
[14] Luciano Telesca, Vincenzo Cuomo, Vincenzo Lapenna et al.Statistical analysis of fractal properties of point processes modelingseismic sequences. PHYSICS OF THE EARTH AND PLANETARYINTERIORS,2001;25:65-83
[15] 郑继明．分形和小波变换在油气预测中的应用．预测．1996；15：51-53
[16] Jianlei Liu,Kurt J. Marfurt et al. Thin bed thickness prediction usingpeak instantaneous frequency.SEG/New Orleans 2006 AnnualMeeting,New Orleans:SEG,2006:968-972
[17] 徐伯勋，白旭滨，于常青．地震勘探信息技术――提取、分析和预测．北京：地质出版社，2001：65-70
[18] 栗毅，王党卫，马兴义．基于匹配追踪理论的超宽带雷达目标散射特性分析及目标识别技术．自然科学进展．2006：10：1317－1325
[19] Jianlei Liu ,Kurt J. Marfurt Instantaneous spectral attributes to detectchannels,Geophysics,2007;72:23－31
[20] Yanghua Wang. Seismic time-frequency spectral decomposition bymatching pursuit. Geophysics,2007;72:13-20
[21] Avijit Chakraborty,David Okaya.Frequency-time decomposition ofseismic data using wavelet-based methods.Geophysics,1995,60:1906－1916
[22] 范虹，孟庆丰．张优云用混合编码遗传算法实现匹配追踪算法.西安交通大学学报，2005；39：295-299
[23] 高飞，玉振明，解光．匹配追踪分解算法的简化实现.广西大学梧州分校学报，2002；12：35-37
[24] 李勤学，付雷，张向君等．薄层地震响应分析及识别技术．世界地质，1999；18：91－95
[25] 窦易升．薄层厚度定量解释的振幅谱平方比法．石油地球物理勘探，1995；30（增刊）：57－65
[26] Barnes A.E.Instantaneous spectral bandwidth and dominantfrequency with applications to seismic reflection data. Geophysics,1993;58:419-428
[27] Bo Zhao.Spectral decomposition of 4D seismic data,SEG/NewOrleans 2006 Annual Meeting,New Orleans:SEG,2006:3235－3238
[28] John P,Castagna,Shengjie Sun.Comparison of spectral decompositionmethods,EAGA,2006;24:75－79
[29] Arthur E,Barnes.Instantaneous spectral bandwidth and dominantfrequency with applications to seismic reflection data.Geophysics,1993;58:419-428
[30] Jianlei liu,Kurt J,Marfurt.Matching pursuit using decompositionMorlet wavelets,SEG/Houston 2005Annual Meeting,Houston:SEG,2005:786-789
[2] 张宇，唐东，周建国．东营凹陷缓坡带滩坝砂储层描述技术．油气地质与采收率，2005；4：14-15
[3] 孙锡年，刘渝，满燕．东营凹陷西部沙四段滩坝砂岩油气成藏条件．国外油田工程，2003；19：23-24
[4] 孙博玲．分形维数(Fractal dimension)及其测量方法．东北林业大学学报，2004；32：116-119
[5] B．曼得尔布洛特著．分形对象――形、机遇和维数.文志英苏虹译．北京：世界图书出版公司，1999：81-89
[6] 陈遵德．储层地震属性优化方法．北京：石油工业出版社，1998：25-34
[7] 申维．分形混沌与矿产预测．北京：地址出版社，2002：1-24
[8] 王才经．现代应用数学．山东东营：石油大学出版社，2004：16-29
[9] 田杰，陈杰，张宇河．基于小波变换及分形特征的目标检测与识别．北京理工大学学报，2003；23：95-99
[10] Nath S.K, Dewangan P. Detection of seismic reflections from seismicattributes through fractal analysis. GEOPHYSICALPROSPECTING,2002;50:341-360
[11] 王东生，曹磊．混沌、分形及其应用．合肥：中国科学技术大学出版社，1995：23-30
[12] 李建平．小波分析与信号处理．重庆：重庆出版社，1997：42-48
[13] 王真理，李衍达．基于小波的信号部分重构与插值．清华大学学报（自然科学版），1995（35）：67-72
[14] Luciano Telesca, Vincenzo Cuomo, Vincenzo Lapenna et al.Statistical analysis of fractal properties of point processes modelingseismic sequences. PHYSICS OF THE EARTH AND PLANETARYINTERIORS,2001;25:65-83
[15] 郑继明．分形和小波变换在油气预测中的应用．预测．1996；15：51-53
[16] Jianlei Liu,Kurt J. Marfurt et al. Thin bed thickness prediction usingpeak instantaneous frequency.SEG/New Orleans 2006 AnnualMeeting,New Orleans:SEG,2006:968-972
[17] 徐伯勋，白旭滨，于常青．地震勘探信息技术――提取、分析和预测．北京：地质出版社，2001：65-70
[18] 栗毅，王党卫，马兴义．基于匹配追踪理论的超宽带雷达目标散射特性分析及目标识别技术．自然科学进展．2006：10：1317－1325
[19] Jianlei Liu ,Kurt J. Marfurt Instantaneous spectral attributes to detectchannels,Geophysics,2007;72:23－31
[20] Yanghua Wang. Seismic time-frequency spectral decomposition bymatching pursuit. Geophysics,2007;72:13-20
[21] Avijit Chakraborty,David Okaya.Frequency-time decomposition ofseismic data using wavelet-based methods.Geophysics,1995,60:1906－1916
[22] 范虹，孟庆丰．张优云用混合编码遗传算法实现匹配追踪算法.西安交通大学学报，2005；39：295-299
[23] 高飞，玉振明，解光．匹配追踪分解算法的简化实现.广西大学梧州分校学报，2002；12：35-37
[24] 李勤学，付雷，张向君等．薄层地震响应分析及识别技术．世界地质，1999；18：91－95
[25] 窦易升．薄层厚度定量解释的振幅谱平方比法．石油地球物理勘探，1995；30（增刊）：57－65
[26] Barnes A.E.Instantaneous spectral bandwidth and dominantfrequency with applications to seismic reflection data. Geophysics,1993;58:419-428
[27] Bo Zhao.Spectral decomposition of 4D seismic data,SEG/NewOrleans 2006 Annual Meeting,New Orleans:SEG,2006:3235－3238
[28] John P,Castagna,Shengjie Sun.Comparison of spectral decompositionmethods,EAGA,2006;24:75－79
[29] Arthur E,Barnes.Instantaneous spectral bandwidth and dominantfrequency with applications to seismic reflection data.Geophysics,1993;58:419-428
[30] Jianlei liu,Kurt J,Marfurt.Matching pursuit using decompositionMorlet wavelets,SEG/Houston 2005Annual Meeting,Houston:SEG,2005:786-789