利用反褶积广义S变换提取流体流度属性
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摘要
在流体流度属性计算过程中,不同时频分析方法获得的流体流度属性剖面的分辨率存在差异,进而影响储层预测精度,而在流体流度属性计算过程中岩石物理关键参数又难以求取(如岩石的基质体积模量)。为此,引入反褶积广义S变换及LRM线性拟合法提取流体流度属性。具体方法为:利用LRM线性拟合法计算基质体积模量,由Silin等的快纵波反射共振峰值频率公式计算峰值频率,再根据流体流度与振幅对频率的一阶导数的关系,获得储层流体流度属性;通过反褶积广义S变换,提高流体流度属性剖面的分辨率。仿真试验及实例分析结果表明:反褶积广义S变换的时频分布具有较高的时频分辨率和聚集性,对非平稳信号中不同信号分量有较强的区分能力,更适应非平稳地震信号流体流度属性的计算; LRM线性拟合法为确定岩石基质体积模量提供了一种方法。
In the calculation of fluid attributes,the resolution of fluid mobility attribute profiles obtained by time-frequency analysis methods are different,which affects the accuracy of reservoir prediction,and in this calculation,it is difficult to obtain key parameters of rock physics(such as the bulk modulus of rock matrix).Therefore,the deconvolution generalized S-transform and linear regression method(LRM)are introduced to extract the fluid mobility attribute.The realization of the method is as follows:the bulk modulus of matrix is calculated by LRM,the peak frequency is calculated by Silin's formula of peak frequency of fast P-wave reflection resonance,and the reservoir fluid mobility is obtained by the relationship between fluid mobility attribute and derivative of amplitude to frequency;then the deconvolution generalized S-transform is used to improve the resolution of fluid mobility attributes profile.Results of the simulation test and case analysis show that the proposed approach has high time-frequency resolution and a strong ability to distinguish different signal components in non-stationary signals,which is more suitable for fluid mobility attribute calculation of non-stationary seismic signals.LRM provides a method for determining the bulk modulus of rock matrix.
In the calculation of fluid attributes,the resolution of fluid mobility attribute profiles obtained by time-frequency analysis methods are different,which affects the accuracy of reservoir prediction,and in this calculation,it is difficult to obtain key parameters of rock physics(such as the bulk modulus of rock matrix).Therefore,the deconvolution generalized S-transform and linear regression method(LRM)are introduced to extract the fluid mobility attribute.The realization of the method is as follows:the bulk modulus of matrix is calculated by LRM,the peak frequency is calculated by Silin's formula of peak frequency of fast P-wave reflection resonance,and the reservoir fluid mobility is obtained by the relationship between fluid mobility attribute and derivative of amplitude to frequency;then the deconvolution generalized S-transform is used to improve the resolution of fluid mobility attributes profile.Results of the simulation test and case analysis show that the proposed approach has high time-frequency resolution and a strong ability to distinguish different signal components in non-stationary signals,which is more suitable for fluid mobility attribute calculation of non-stationary seismic signals.LRM provides a method for determining the bulk modulus of rock matrix.
引文
[1] Rubino J G,Velis D R,Holliger K.Permeability effects on the seismic response of gas reservoirs[J].Geophysical Journal International,2012,189(1):448-468.
[2] 陈程,文晓涛,郝亚矩,等.基于White模型的砂岩储层渗透率特性分析[J].石油地球物理勘探,2015,50(4):723-729.CHEN Cheng,WEN Xiaotao,HAO Yaju,et al.Sandstone reservoir permeability characteristics analysis based on White model[J].Oil Geophysical Prospecting,2015,50(4):723-729.
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[10] 张生强,韩立国,李才等.基于高分辨率反演谱分解的储层流体流度计算方法研究[J].石油物探,2015,54(2):142-149.ZHANG Shengqiang,HAN Liguo,LI Cai,et al.Computation method for reservoir fluid mobility based on high-resolution inversion spectral decomposition[J].Geophysical Prospecting for Petroleum,2015,54(2):142-149.
[11] Stockwell R G,Mansinha L,Lowe R P.Localization of the complex spectrum:the S transform[J].IEEE Transactions on Signal Processing,1996,44(4):998-1001.
[12] 陈学华,贺振华,黄德济.基于广义S变换的地震资料高效时频谱分解[J].石油地球物理勘探,2008,43(5):530-534.CHEN Xuehua,HE Zhenhua,HUANG Deji.High-efficient time-frequency spectrum decomposition of seismic data based on generalized S transform[J].Oil Geophysical Prospecting,2008,43(5):530-534.
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[14] 陈学华,贺振华,文晓涛,等.低频阴影的数值模拟与检测[J].石油地球物理勘探,2009,44(3):298-303.CHEN Xuehua,HE Zhenhua,Wen Xiaotao,et al.Numeric simulation and detection of low frequency sha-dow[J].Oil Geophysical Prospecting,2009,44(3):298-303.
[15] Martin W,Flandrin P.Wigner-Ville spectral analysis of nonstationary processes[J].IEEE Transactions on Acoustics Speech & Signal Processing,2003,33(6):1461-1470.
[16] Lu W K,Zhang Q.Deconvolutive short-time Fourier transform spectrogram[J].IEEE Signal Processing Letters,2009,16(7):576-579.
[17] Lu W K,Li F Y.Seismic spectral decomposition using deconvolutive short-time Fourier transform spectrogram[J].Geophysics,2013,78(2):V43-V51.
[18] 朱恒,文晓涛,金炜龙,等.基于反褶积短时傅立叶变换的油气检测[J].地球物理学进展,2015,30(5):2354-2359.ZHU Heng,WEN Xiaotao,JIN Weilong,et al.Oiland gas detection based on deconvolutive short-time Fourier transform[J].Progress in Geophysics,2015,30(5):2354-2359.
[19] 张懿疆,文晓涛,刘婷,等.基于反褶积广义S变换的地震频谱成像方法研究[J].科学技术与工程,2017,17(15):12-18.ZHANG Yijiang,WEN Xiaotao,LIU Ting,et al.Seismic spectral imaging method based on deconvolutive generalized S-transform[J].Science Technology and Engineering,2017,17(15):12-18.
[20] 贺锡雷.烃类预测的岩石物理基础和地震孔隙度反演[D].四川成都:成都理工大学,2012.
[21] 胡军辉,文晓涛,杨小江,等.基于叠前黏滞—弥散波动方程的数值模拟[J].石油地球物理勘探,2014,49(4):708-714.HU Junhui,WEN Xiaotao,YANG Xiaojiang,et al.Numerical simulation based on prestack diffusive-viscous wave equation[J].Oil Geophysical Prospecting,2014,49(4):708-714.
[22] 胡军辉,文晓涛,许艳秋,等.利用黏滞—弥散波动方程理论进行油水识别[J].石油地球物理勘探,2016,51(3):556-564.HU Junhui,WEN Xiaotao,XU Yanqiu,et al.Oil-water recognition based on diffusive-viscous wave equation[J].Oil Geophysical Prospecting,2016,51(3):556-564.
[23] 李世凯,文晓涛,阮韵淇,等.基于黏滞—弥散理论的含气砂岩数值模拟与分析[J].石油地球物理勘探,2017,52(4):752-759.LI Shikai,WEN Xiaotao,RUAN Yunqi,et al.Sandstone gas reservoir simulation and analysis based on diffusive-viscous theory[J].Oil Geophysical Prospecting,2017,52(4):752-759.
[2] 陈程,文晓涛,郝亚矩,等.基于White模型的砂岩储层渗透率特性分析[J].石油地球物理勘探,2015,50(4):723-729.CHEN Cheng,WEN Xiaotao,HAO Yaju,et al.Sandstone reservoir permeability characteristics analysis based on White model[J].Oil Geophysical Prospecting,2015,50(4):723-729.
[3] Korneev V A,Silin D B,Goloshubin G M,et al.Seismic imaging of oil production rate[C].SEG Technical Program Expanded Abstracts,2004,23:1476-1479.
[4] Silin D and Goloshubin G M.A Low-frequency As-ymptotic Model of Seismic Reflection from a High Permeability Layer[R].Lawrence Berkeley National Laboratory Report,Berkeley,California,USA,2009.
[5] Silin D and Goloshubin G M.An asymptotic model of seismic reflection from a permeable layer[J].Transport in Porous Media,2010,83(1):233-256.
[6] Gassmann F.Uber die elastizitat poroser medien[J].Veirteljahrsschrift der Naturforschenden Gesellschaft in Zzirich,1951,96:1-23.
[7] Goloshubin G,Vanschuyver C,Korneev V,et al.Reservoir imaging using low frequencies of seismic reflections[J].The Leading Edge,2006,25(5):527-531.
[8] Goloshubin G,Silin D,Vingalov V,et al.Reservoir permeability from seismic attribute analysis[J].The Leading Edge,2008,27(3):376-381.
[9] Chen X H,He Z H,Zhu S X,et al.Seismic low-frequency-based calculation of reservoir fluid mobility and its applications[J].Applied Geophysics,2012,9(3):326-332.
[10] 张生强,韩立国,李才等.基于高分辨率反演谱分解的储层流体流度计算方法研究[J].石油物探,2015,54(2):142-149.ZHANG Shengqiang,HAN Liguo,LI Cai,et al.Computation method for reservoir fluid mobility based on high-resolution inversion spectral decomposition[J].Geophysical Prospecting for Petroleum,2015,54(2):142-149.
[11] Stockwell R G,Mansinha L,Lowe R P.Localization of the complex spectrum:the S transform[J].IEEE Transactions on Signal Processing,1996,44(4):998-1001.
[12] 陈学华,贺振华,黄德济.基于广义S变换的地震资料高效时频谱分解[J].石油地球物理勘探,2008,43(5):530-534.CHEN Xuehua,HE Zhenhua,HUANG Deji.High-efficient time-frequency spectrum decomposition of seismic data based on generalized S transform[J].Oil Geophysical Prospecting,2008,43(5):530-534.
[13] 陈学华,贺振华,黄德济,等.时频域油气储层低频阴影检测[J].地球物理学报,2009,52(1):215-221.CHEN Xuehua,HE Zhenhua,Huang Deji,et al.Low frequency shadow detection of gas reservoirs in time-frequency domain[J].Chinese Journal of Geophysics,2009,52(1):215-221.
[14] 陈学华,贺振华,文晓涛,等.低频阴影的数值模拟与检测[J].石油地球物理勘探,2009,44(3):298-303.CHEN Xuehua,HE Zhenhua,Wen Xiaotao,et al.Numeric simulation and detection of low frequency sha-dow[J].Oil Geophysical Prospecting,2009,44(3):298-303.
[15] Martin W,Flandrin P.Wigner-Ville spectral analysis of nonstationary processes[J].IEEE Transactions on Acoustics Speech & Signal Processing,2003,33(6):1461-1470.
[16] Lu W K,Zhang Q.Deconvolutive short-time Fourier transform spectrogram[J].IEEE Signal Processing Letters,2009,16(7):576-579.
[17] Lu W K,Li F Y.Seismic spectral decomposition using deconvolutive short-time Fourier transform spectrogram[J].Geophysics,2013,78(2):V43-V51.
[18] 朱恒,文晓涛,金炜龙,等.基于反褶积短时傅立叶变换的油气检测[J].地球物理学进展,2015,30(5):2354-2359.ZHU Heng,WEN Xiaotao,JIN Weilong,et al.Oiland gas detection based on deconvolutive short-time Fourier transform[J].Progress in Geophysics,2015,30(5):2354-2359.
[19] 张懿疆,文晓涛,刘婷,等.基于反褶积广义S变换的地震频谱成像方法研究[J].科学技术与工程,2017,17(15):12-18.ZHANG Yijiang,WEN Xiaotao,LIU Ting,et al.Seismic spectral imaging method based on deconvolutive generalized S-transform[J].Science Technology and Engineering,2017,17(15):12-18.
[20] 贺锡雷.烃类预测的岩石物理基础和地震孔隙度反演[D].四川成都:成都理工大学,2012.
[21] 胡军辉,文晓涛,杨小江,等.基于叠前黏滞—弥散波动方程的数值模拟[J].石油地球物理勘探,2014,49(4):708-714.HU Junhui,WEN Xiaotao,YANG Xiaojiang,et al.Numerical simulation based on prestack diffusive-viscous wave equation[J].Oil Geophysical Prospecting,2014,49(4):708-714.
[22] 胡军辉,文晓涛,许艳秋,等.利用黏滞—弥散波动方程理论进行油水识别[J].石油地球物理勘探,2016,51(3):556-564.HU Junhui,WEN Xiaotao,XU Yanqiu,et al.Oil-water recognition based on diffusive-viscous wave equation[J].Oil Geophysical Prospecting,2016,51(3):556-564.
[23] 李世凯,文晓涛,阮韵淇,等.基于黏滞—弥散理论的含气砂岩数值模拟与分析[J].石油地球物理勘探,2017,52(4):752-759.LI Shikai,WEN Xiaotao,RUAN Yunqi,et al.Sandstone gas reservoir simulation and analysis based on diffusive-viscous theory[J].Oil Geophysical Prospecting,2017,52(4):752-759.