油页岩的地球物理识别和评价方法
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摘要
利用地球物理方法识别和评价油页岩主要是依靠测井技术,地震方面研究非常薄弱。在现有的油页岩测井响应特征和测井评价方法(ΔlogR重叠法)的基础上对ΔlogR重叠法进行了拓展,引入波阻抗与常规测井响应特征进行重叠来评价油页岩;同时根据油页岩的岩石结构特征,建立油页岩岩石物理模型,提出了一种基于岩石物理模型的由速度反演油页岩有机质含量的方法;最后利用地震多属性预测技术将已知钻井的含油率信息反演外推到地震数据,得到预测的含油率数据。结果表明,波阻抗ΔlogR重叠法、岩石物理反演法和地震多属性预测法都可以有效地评价油页岩的有机碳含量和含油率。
Currently,the identification and evaluation of oil shale in the way of geophysics is mainly depending on logging technology with few seismic means.We developed the logging evaluation method of oil shale(ΔlogR overlapping) by overlapping seismic acoustic impedance and conventional logging response characteristics to evaluate oil shale.Meanwhile,a petrophysical model for oil shale was established according to its structural characteristics and a new method to calculate the organic matter content of oil shale by inverting velocity was also presented based on this petrophysical model.Finally,the oil-cut information of a known well was inversely extrapolated to seismic data by using seismic multi-attribute prediction so as to get predicted oil-cut data.The results showed that the ΔlogR overlapping with seismic acoustic impedance,petrophysical velocity-inversion and seismic multi-attribute prediction methods are all able to effectively evaluate the total organic carbon and oil-cut of oil shale.
Currently,the identification and evaluation of oil shale in the way of geophysics is mainly depending on logging technology with few seismic means.We developed the logging evaluation method of oil shale(ΔlogR overlapping) by overlapping seismic acoustic impedance and conventional logging response characteristics to evaluate oil shale.Meanwhile,a petrophysical model for oil shale was established according to its structural characteristics and a new method to calculate the organic matter content of oil shale by inverting velocity was also presented based on this petrophysical model.Finally,the oil-cut information of a known well was inversely extrapolated to seismic data by using seismic multi-attribute prediction so as to get predicted oil-cut data.The results showed that the ΔlogR overlapping with seismic acoustic impedance,petrophysical velocity-inversion and seismic multi-attribute prediction methods are all able to effectively evaluate the total organic carbon and oil-cut of oil shale.
引文
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[11]Reuss A.Berechnung der fliessgrenze von mischkristallen auf gr-und der Plastizittsbedingungen für einkristalle[J].Zeitschriftfür Angewandte Mathematic undMechanik,1929,9:49-58.
[12]Krief M,Garat J,Stellingwerff J,et al.A petrophysical interpre-tation using the velocities of P and S waves(full-waveform son-ic)[J].The Log Analyst,1990,31:355-369.
[13]Gassmann F.Verteljahrsschrift der Naturforschenden Gesellschaft inZurich[J].Uber Die Elastizitat Poroser Medien,1951,96:1-23.
[14]Mavko G,Mukerji T,Dvoskin J.The rock physics handbook[M].Cambridge:Cambridge University Press,1998:133-156.
[15]马中高,解吉高.岩石的纵、横波速度与密度的规律研究[J].地球物理学进展,2005,20(4):905-910.Ma Zhonggao,Xie Jigao.Relationship among compressionalwave,shear wave velocities and density of rocks[J].Progress inGeophysics,2005,20(4):905-910.
[16]Yin H.Acoustic velocity and attenuations of rocks:isotropy,in-trinsic anisotropy,and stress induced anisotropy[D].Stanford:Stanford University,1992.
[17]姚逢昌,甘利灯.地震反演的应用与限制[J].石油勘探与开发,2000,27(2):53-56.Yao Fengchang,Gan Lideng.Application and restrictions of seis-mic inversion[J].Petroleum Exploration and Development,2000,27(2):53-56.
[18]王延光.储层地震反演方法以及应用中的关键问题与对策[J].石油物探,2002,41(3):299-303.Wang Yanguang.Seismic reservoir inversion algorithm and thekey problems and policies in its application[J].Geophysical Pros-pecting for Petroleum,2002,41(3):299-303.
[19]Hampson D P.Use of multi-attribute transform to predict log proper-ties from seismic data[J].Geophysics,2001,66(1):220-236.
[20]Schultz P S,Ronen S,Hattori M,et al.Seismic guided estimationof log properties,Parts 1,a data-driven interpretation methodolo-gy[J].The Leading Edge,1994,13(5):305-310.
[21]Ronen S,Schultz P S,Hattori M,et al.Seismic guided estimationof log properties,Parts 2,using artificial neural networks fornonlinear attribute calibration[J].The Leading Edge,1994,13(6):674-678.
[22]Schultz P S,Ronen S,Hattori M,et al.Seismic guided estimationof log properties,Parts 3,a controlled study[J].The LeadingEdge,1994,13(7):770-776.
[23]石双虎,何樵登,滕吉文,等.利用多元地震属性预测测井特性[J].西北地震学报,2006,28(4):309-313.Shi Shuanghu,He Qiaodeng,Teng Jiwen,et al.Using multi-at-tribute to predict log properties from seismic data[J].North-western Seismological Journal,2006,28(4):309-313.
[24]何碧竹,周杰,汪功怀.利用多元地震属性预测储层信息[J].石油地球物理勘探,2003,38(3):258-262.He Bizhu,Zhou Jie,Wang Gonghuai.Using multivariate to pre-dict reservoir information[J].Oil Geophysical Prospecting,2003,38(3):258-262.
[25]张绍红.概率神经网络技术在非均质地层岩性反演中的应用[J].石油学报,2008,29(4):549-552.Zhang Shaohong.Application of probabilistic neural networktechnique to lithology inversion of heterogeneous stratum[J].Acta Petrolei Sinica,2008,29(4):549-552.
[26]周金应,桂碧雯,李茂,等.基于岩控的人工神经网络在渗透率预测中的应用[J].石油学报,2010,31(6):985-988.Zhou Jinying,Gui Biwen,Li Mao,et al.An application of the ar-tificial neural net dominated by lithology to permeability predic-tion[J].Acta Petrolei Sinica,2010,31(6):985-988.
[27]Chen Q,Sidney S.Seismic attribute technology for reservoir forecas-ting and monitoring[J].The Leading Edge,1997,16(5):445-456.
[28]谢雄举,季玉新.优选地震属性预测储层参数的方法及其应用[J].石油物探,2004,43(S1):127-131.Xie Xiongju,Ji Yuxin.Optimization of seismic attributes for res-ervoir parameter prediction and its application[J].GeophysicalProspecting for Petroleum,2004,43(S1):127-131.
[29]孔炜,彭苏萍,霍全明.地震属性预测测井响应的研究与应用[J].煤炭学报,2004,29(1):45-48.Kong Wei,Peng Suping,Huo Quanming.Research and applica-tion of coal seam log response predicted from seismic attribute[J].Journal of China Coal Society,2004,29(1):45-48.
[30]曹强,叶加仁,石万忠,等.低勘探程度盆地烃源岩早期评价——以南黄海北部盆地东北凹为例[J].石油学报,2009,30(4):522-529.Cao Qiang,Ye Jiaren,Shi Wanzhong,et al.Preliminary predictionand evaluation of source rocks in low-exploration basins:a casestudy on the northeast sag of the Northern South Yellow Sea Ba-sin in China[J].Acta Petrolei Sinica,2009,30(4):522-529.
[2]刘招君,董清水,叶松青,等.中国油页岩资源现状[J].吉林大学学报:地球科学版,2006,36(6):869-876.Liu Zhaojun,Dong Qingshui,Ye Songqing,et al.The situation ofoil shale resources in China[J].Journal of Jilin University:EarthScience Edition,2006,36(6):869-876.
[3]赵政璋,吴国干,胡素云,等.全球油气勘探新进展[J].石油学报,2005,26(6):119-126.Zhao Zhengzhang,Wu Guogan,Hu Suyun,et al.Recent develop-ment of global oil and gas exploration[J].Acta Petrolei Sinica,2005,26(6):119-126.
[4]王红岩,李景明,赵群,等.中国新能源资源基础及发展前景展望[J].石油学报,2009,30(3):469-474.Wang Hongyan,Li Jingming,Zhao Qun,et al.Resources and de-velopment of new energy in China[J].Acta Petrolei Sinica,2009,30(3):469-474.
[5]车长波,杨虎林,刘招君,等.我国油页岩资源勘探开发前景[J].中国矿业,2008,17(9):1-4.Che Changbo,Yang Hulin,Liu Zhaojun,et al.Exploration andexploitation prospects of oil shale resources in China[J].ChinaMining Magazine,2008,17(9):1-4.
[6]贺君玲,邓守伟,陈文龙,等.利用测井技术评价松辽盆地南部油页岩[J].吉林大学学报:地球科学版,2006,36(6):909-914.He Junling,Deng Shouwei,Chen Wenlong,et al.Evaluation of oilshale in the Southern Songliao Basin using logging techniques[J].Journal of Jilin University:Earth Science Edition,2006,36(6):909-914.
[7]王永明,郭建军,刘宏.陕北三叠纪煤田勘探中油页岩的地球物理测井效果[J].陕西地质,2007,25(1):59-63.Wang Yongming,Guo Jianjun,Liu Hong.Geophysical logging ofoil shale in exploration of the Triassic Coal-Fields in NorthernShaanxi[J].Geology of Shaanxi,2007,25(1):59-63.
[8]Passey Q R,Creaney S,Kulla J B,et al.A practical model for or-ganic richness from porosity and resistivity logs[J].AAPG Bul-letin,1990,74(12):1777-1794.
[9]朱振宇,刘洪,李幼铭.ΔlogR技术在烃源岩识别中的应用与分析[J].地球物理学进展,2003,18(4):647-649.Zhu Zhenyu,Liu Hong,Li Youming.The analysis and applicationofΔlogR method in the source rock's identification[J].Progressin Geophysics,2003,18(4):647-649.
[10]Eseme E,Urai J L,Krooss B M,et al.Review of mechanical prop-erties of oil shales:implications for exploitation and basin modelling[J].Oil Shale,2007,24(2):159-174.
[11]Reuss A.Berechnung der fliessgrenze von mischkristallen auf gr-und der Plastizittsbedingungen für einkristalle[J].Zeitschriftfür Angewandte Mathematic undMechanik,1929,9:49-58.
[12]Krief M,Garat J,Stellingwerff J,et al.A petrophysical interpre-tation using the velocities of P and S waves(full-waveform son-ic)[J].The Log Analyst,1990,31:355-369.
[13]Gassmann F.Verteljahrsschrift der Naturforschenden Gesellschaft inZurich[J].Uber Die Elastizitat Poroser Medien,1951,96:1-23.
[14]Mavko G,Mukerji T,Dvoskin J.The rock physics handbook[M].Cambridge:Cambridge University Press,1998:133-156.
[15]马中高,解吉高.岩石的纵、横波速度与密度的规律研究[J].地球物理学进展,2005,20(4):905-910.Ma Zhonggao,Xie Jigao.Relationship among compressionalwave,shear wave velocities and density of rocks[J].Progress inGeophysics,2005,20(4):905-910.
[16]Yin H.Acoustic velocity and attenuations of rocks:isotropy,in-trinsic anisotropy,and stress induced anisotropy[D].Stanford:Stanford University,1992.
[17]姚逢昌,甘利灯.地震反演的应用与限制[J].石油勘探与开发,2000,27(2):53-56.Yao Fengchang,Gan Lideng.Application and restrictions of seis-mic inversion[J].Petroleum Exploration and Development,2000,27(2):53-56.
[18]王延光.储层地震反演方法以及应用中的关键问题与对策[J].石油物探,2002,41(3):299-303.Wang Yanguang.Seismic reservoir inversion algorithm and thekey problems and policies in its application[J].Geophysical Pros-pecting for Petroleum,2002,41(3):299-303.
[19]Hampson D P.Use of multi-attribute transform to predict log proper-ties from seismic data[J].Geophysics,2001,66(1):220-236.
[20]Schultz P S,Ronen S,Hattori M,et al.Seismic guided estimationof log properties,Parts 1,a data-driven interpretation methodolo-gy[J].The Leading Edge,1994,13(5):305-310.
[21]Ronen S,Schultz P S,Hattori M,et al.Seismic guided estimationof log properties,Parts 2,using artificial neural networks fornonlinear attribute calibration[J].The Leading Edge,1994,13(6):674-678.
[22]Schultz P S,Ronen S,Hattori M,et al.Seismic guided estimationof log properties,Parts 3,a controlled study[J].The LeadingEdge,1994,13(7):770-776.
[23]石双虎,何樵登,滕吉文,等.利用多元地震属性预测测井特性[J].西北地震学报,2006,28(4):309-313.Shi Shuanghu,He Qiaodeng,Teng Jiwen,et al.Using multi-at-tribute to predict log properties from seismic data[J].North-western Seismological Journal,2006,28(4):309-313.
[24]何碧竹,周杰,汪功怀.利用多元地震属性预测储层信息[J].石油地球物理勘探,2003,38(3):258-262.He Bizhu,Zhou Jie,Wang Gonghuai.Using multivariate to pre-dict reservoir information[J].Oil Geophysical Prospecting,2003,38(3):258-262.
[25]张绍红.概率神经网络技术在非均质地层岩性反演中的应用[J].石油学报,2008,29(4):549-552.Zhang Shaohong.Application of probabilistic neural networktechnique to lithology inversion of heterogeneous stratum[J].Acta Petrolei Sinica,2008,29(4):549-552.
[26]周金应,桂碧雯,李茂,等.基于岩控的人工神经网络在渗透率预测中的应用[J].石油学报,2010,31(6):985-988.Zhou Jinying,Gui Biwen,Li Mao,et al.An application of the ar-tificial neural net dominated by lithology to permeability predic-tion[J].Acta Petrolei Sinica,2010,31(6):985-988.
[27]Chen Q,Sidney S.Seismic attribute technology for reservoir forecas-ting and monitoring[J].The Leading Edge,1997,16(5):445-456.
[28]谢雄举,季玉新.优选地震属性预测储层参数的方法及其应用[J].石油物探,2004,43(S1):127-131.Xie Xiongju,Ji Yuxin.Optimization of seismic attributes for res-ervoir parameter prediction and its application[J].GeophysicalProspecting for Petroleum,2004,43(S1):127-131.
[29]孔炜,彭苏萍,霍全明.地震属性预测测井响应的研究与应用[J].煤炭学报,2004,29(1):45-48.Kong Wei,Peng Suping,Huo Quanming.Research and applica-tion of coal seam log response predicted from seismic attribute[J].Journal of China Coal Society,2004,29(1):45-48.
[30]曹强,叶加仁,石万忠,等.低勘探程度盆地烃源岩早期评价——以南黄海北部盆地东北凹为例[J].石油学报,2009,30(4):522-529.Cao Qiang,Ye Jiaren,Shi Wanzhong,et al.Preliminary predictionand evaluation of source rocks in low-exploration basins:a casestudy on the northeast sag of the Northern South Yellow Sea Ba-sin in China[J].Acta Petrolei Sinica,2009,30(4):522-529.
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