基于匹配追踪算法子波分解技术在薄互层储层预测中的应用
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摘要
薄互层储层砂体预测技术的研究已成为国内、外各油田的重要研究课题,并已取得较多研究成果。但多数利用地震资料进行薄互层预测技术,均基于单一地震子波与地震反射系数函数的褶积假设,实际上地震子波在穿过不同物理特性地层时,其形状会发生不同变化,导致该假设与实际情况尚有一定距离,致使薄互层储层预测的精度降低。这里主要论述的是基于匹配追踪算法子波分解技术识别薄互层储层。通过研究表明,该技术能较好地分辨出储层在空间的展布规律,识别薄互层储层,为油藏的地质及地球物理解释提供有力的支持。
The studies of prediction techniques for thin interbedded sand reservoir have become an important research topic and obtained many achievements.However,most of them using seismic data are based on convolution model,which is defined as the convolution of a single wavelet and a seismic reflection coefficient function.Actually,the shape of wavelet will change when seismic wavelets go through formation with different physical properties,therefore,this single wavelet convolution model is far away from the real situation,and it will decrease the accuracy of prediction.In this paper,we will discuss wavelet decomposition technique based on matching pursuit algorithm.The results show that this technique can identify the distribution of thin-interbedded sandstone reservoirs,and support for the reservoir geological and geophysical interpretation.
The studies of prediction techniques for thin interbedded sand reservoir have become an important research topic and obtained many achievements.However,most of them using seismic data are based on convolution model,which is defined as the convolution of a single wavelet and a seismic reflection coefficient function.Actually,the shape of wavelet will change when seismic wavelets go through formation with different physical properties,therefore,this single wavelet convolution model is far away from the real situation,and it will decrease the accuracy of prediction.In this paper,we will discuss wavelet decomposition technique based on matching pursuit algorithm.The results show that this technique can identify the distribution of thin-interbedded sandstone reservoirs,and support for the reservoir geological and geophysical interpretation.
引文
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[14]袁子龙,杨斌,王建国.薄层、薄互层地震反射时间域与频率域正演模拟研究及应用[J].石油物探,1996,35(3):1420
[15]PING AN.Sand Mapping Using Multiwavelet SeismicTrace Decomposition and Reconstruction[C].SPE,2006,1.
[16]邢成智,党玉芳.地震油气检测技术在准噶尔盆地拐19井区侏罗系油藏评价中的应用[J].天然气工业,2007,27(增刊):477.
[17]赵爽,李仲东,许红梅,等.多子波分解技术检测含煤砂岩储层[J].石油地球物理勘探,2007,27(9):44.
[18]李曙光,徐天吉,唐建明,等.基于频率域小波的地震信号多子波分解及重构[J].石油地球物理勘探,2009,44(6):675.
[19]MALLATS,ZHANG Z.Matching pursuits with time-frequency dictionaries[J].IEEE Transactions on SignalProcessing,1993,41:2297.
[20]MARFURTK J,KIRLIN R L.Narrow-band spectral a-nalysis and thin-bed tuning[J].Geophysics,2001,66(4):1274.
[2]苏盛甫.薄储集层的反射特征和定量解释方法[J].石油地球物理勘探,1988,23(4):387.
[3]梁光河,何樵登,韩立国,等.薄层厚度反演[J].石油物探快讯,1991,8(1):34.
[4]龙建东.薄层厚度与振幅、频率关系的神经网络BP法模拟[J].石油地球物理勘探,1995,30(6):817.
[5]贺振华,黄德济,王成祥.多波层位识别与薄层解释新方法[J].成都理工学院学报,1996,23(3):1.
[6]庄东海,肖春燕.用人工神经网络计算薄层厚度[J].石油地球物理勘探,1996,31(3):394.
[7]黄真萍,王晓华,王云专.薄层地震属性参数分析和厚度预测[J].石油物探,1997,36(3):28.
[8]邵治龙,贺振华,黄德济.小波变换与最大熵法联合计算薄层厚度[J].石油地球物理勘探,1998,33(2).
[9]李琼,贺振华.地震高分辨率非线性反演在薄互储层识别中的应用[J].成都理工大学学报自然科学版,2004,31(6):708.
[10]张巧凤,王余庆,王天琦,等.薄互层河道砂岩地震预测技术[J].天然气工业,2007,27(增刊):406.
[11]柏冠军,吴汉宁,赵希刚,等.地震资料预测薄层厚度方法研究与应用[J].地球物理学进展,2006,21(2):554.
[12]成仲良,张万选.利用地震反射波振幅计算薄储层厚度[J].石油地震地质,1991,3(2):25.
[13]黄真萍,王晓华,王云专.薄层地震属性参数分析和厚度预测[J].石油物探,1997,36(3):28.
[14]袁子龙,杨斌,王建国.薄层、薄互层地震反射时间域与频率域正演模拟研究及应用[J].石油物探,1996,35(3):1420
[15]PING AN.Sand Mapping Using Multiwavelet SeismicTrace Decomposition and Reconstruction[C].SPE,2006,1.
[16]邢成智,党玉芳.地震油气检测技术在准噶尔盆地拐19井区侏罗系油藏评价中的应用[J].天然气工业,2007,27(增刊):477.
[17]赵爽,李仲东,许红梅,等.多子波分解技术检测含煤砂岩储层[J].石油地球物理勘探,2007,27(9):44.
[18]李曙光,徐天吉,唐建明,等.基于频率域小波的地震信号多子波分解及重构[J].石油地球物理勘探,2009,44(6):675.
[19]MALLATS,ZHANG Z.Matching pursuits with time-frequency dictionaries[J].IEEE Transactions on SignalProcessing,1993,41:2297.
[20]MARFURTK J,KIRLIN R L.Narrow-band spectral a-nalysis and thin-bed tuning[J].Geophysics,2001,66(4):1274.
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