概率神经网络技术在煤田地震反演中的应用研究
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摘要
实现从构造勘探向岩性勘探阶段的转变,是煤田地震勘探亟待解决的重要问题。其中,地震反演技术是岩性勘探的一种重要手段。为了规避常规反演方法的固有限制,利用概率神经网络技术预测井数据和地震数据之间的非线性关系,得到密度数据体和速度数据体,并获得相应的波阻抗数据体。对某矿区的实际地震资料采用该技术进行岩性反演,得到了较为准确的波阻抗数据体,为岩性解释提供了不可或缺的资料。
It is transformation from the structure to lithologic exploration that needs to be urgently solved in coalfield seismic exploration.As we all know,seismic inversion technique is a significant tool in lithologic exploration.We chose to apply probabilistic neural network method for predicting the nonlinear relationship between well data and seismic data so as to avoid the inherent limitations of the common inversion method and then predicte density and velocity volume to derive the impendence volume.Based on the thought,we use the technique to lithological inversion and obtained a quite accurate impendence volume which provide indispensible data to lithologic interpretation in one coalfield.
It is transformation from the structure to lithologic exploration that needs to be urgently solved in coalfield seismic exploration.As we all know,seismic inversion technique is a significant tool in lithologic exploration.We chose to apply probabilistic neural network method for predicting the nonlinear relationship between well data and seismic data so as to avoid the inherent limitations of the common inversion method and then predicte density and velocity volume to derive the impendence volume.Based on the thought,we use the technique to lithological inversion and obtained a quite accurate impendence volume which provide indispensible data to lithologic interpretation in one coalfield.
引文
[1]朱书阶,陈青峰,何文欣.利用波阻抗反演技术确定岩浆岩侵入煤层范围.煤田地质与勘探,2003,31(1):49-50.ZHU Shu-jie,CHEN Qing-feng,HE Wen-xin.Determinationof magnetic rock intrusion range using acoustic impedanceinversion.COAL GEOLOGY&EXPLORATION,2003,31(1):49-50.
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[3]彭苏萍,邹冠贵,李巧灵.测井约束地震反演在煤厚预测中的应用研究.中国矿业大学学报,2008,37(6):729-732.PENG Su-peng,ZOU Guan-gui,LI Qiao-ling.SeamThickness Prediction Methods Based on the LoggingConstrained Seismic Inversion.JOURNAL OF CHINAUNIVERSITY OF MINING&TECHNOLOGY,2008,37(6):729-732.
[4]许永忠.煤田地震反演方法与应用研究[D].徐州:中国矿业大学,2008.XU Yong-zhong.Study and application on the seismicinversion in coalfield[D].XUZHOU:JOURNAL OF CHINAUNIVERSITY OF MINING&TECHNOLOGY,2008.
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[8]杨立强.测井约束地震反演综述.地球物理学进展,2003,18(3):530-534.YANG Li-qiang.A review of well log constrained seismicinversion.PROGRESS I N GEOPHYSICS,2003,18(3):530-534.
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[10]刘爱群,盖永浩.测井约束反演过程中测井资料统计分析研究.地球物理学进展,2007,22(5):1487-1491.LIU Ai-qun,GAI Yong-hao.Analysis and research of loginformation in the process of oil well logging restraintinversion.PROGRESS I N GEOPHYSICS,2007,22(5):1487-1491.
[11]马劲风.地震勘探中的广义弹性阻抗正反演.地球物理学报,2003,46(1):118-124.MA Jin-feng.Forward modeling and inversion method ofgeneralized elastic impedance in seismic exploration.ChineseJ.Geophys,2003,46(1):118-124.
[12]姚逢昌,甘利灯.地震反演的应用与限制.石油勘探与开发,2000.27(2):53-58.YAO Feng-chang,GAN Li-deng.Application and restrictionof seismic inversion.Petroleum Exploration andDevelopment,2000.27(2):53-58.
[13]P.An,W.M.Moon.Reservoir Characterization Using Feedforward Neural Networks[C].SEG,2005,258-260.
[14]M.M.Saggaf,M.Nafi Toksozz,H.M.Mustafa.Estimationof reservoir properties from seismic data by smooth neuralnetworks.Geophysics,2003,68(6):220-236.
[15]Amit K Ray and Samir Biswal.An efficient method of effectiveporosity prediction using an unconventional attribute throughmulti-attribute regression and probabilistic neural network:Acase study in a deep-water gas field,East Coast of India[C].SEG,2010,1413-1417.
[16]Specht,Donald.Probabilistic neural networks.Neuralnetworks,1990,2:109-118.
[17]Malleswar Yenugu,Jeremy C.Fisk,Kurt J.Marfurt..Probabilistic Neural Network inversion for characterization ofcoalbed methane[C].SEG,2010,2906-2910.
[18]Hampson,D.,J.Schuelke,J.Quirein.Use of multiattributetransforms to predict log properties from seismic data.Geophysics,2001,66(1),220-236.
[19]Pramanik,A.G.,V.Singh,R.Vig,A.K.Srivastava,etal.Estimation of effective porosity using geostatistics andmultiattribute transforms:A case study.Geophysics,2004,69,352-372.
[20]Russell,B.,D.Hampson,J.Schuelke,et al.Multiattributeseismic analysis.The Leading Edge,1997,16(10):1439-1443.
[21]Somanath Misra,Satinder Chopra,John Zhang.Neural networkregression analysis and post-stack inversion-A comparison[C].SEG,2010,1473-1477.
[2]张爱印,李学文,董守华.测井约束反演技术在煤田三维地震岩性勘探中的应用.地球物理学进展,2004,19(3):533-536.ZHANG Ai-yin,LI Xue-wen,DONG Shou-hua.Applicationof logging constrained inversion to the 3-D seismic lithologicalexploration in coalfield.PROGRESS IN GEOPHYSICS,2004,19(3):533-536.
[3]彭苏萍,邹冠贵,李巧灵.测井约束地震反演在煤厚预测中的应用研究.中国矿业大学学报,2008,37(6):729-732.PENG Su-peng,ZOU Guan-gui,LI Qiao-ling.SeamThickness Prediction Methods Based on the LoggingConstrained Seismic Inversion.JOURNAL OF CHINAUNIVERSITY OF MINING&TECHNOLOGY,2008,37(6):729-732.
[4]许永忠.煤田地震反演方法与应用研究[D].徐州:中国矿业大学,2008.XU Yong-zhong.Study and application on the seismicinversion in coalfield[D].XUZHOU:JOURNAL OF CHINAUNIVERSITY OF MINING&TECHNOLOGY,2008.
[5]林建东,霍全明,吴奕峰.多井约束三维地震反演技术在煤厚预测中的应用.中国煤田地质,2003,15(3),43-45.LIN Jian-dong,HUO Quan-ming,WU Yi-feng.Applicationon 3 dimensional seismic inverse technology of multipleconstraint in prediction of coal thickness.COAL GEOLOGYOF CHINA,2003,15(3),43-45.
[6]许升辉,马劲风.波阻抗反演中多井条件下的子波提取方法.地球物理学进展,2003,18(4):623-627XU Sheng-hui,MA Jin-feng.Wavelet extraction method ofwave impedance inverse with multi-well restrictions.PROGRESS I N GEOPHYSICS,2003,18(4):623-627.
[7]马中高,解吉高.岩石的纵横波速度与密度的规律研究.地球物理学进展,2005,20(4):905-910.MA Zhong-gao,XIE Ji-gao.Relationship among compressionalwave,shear wave velocities and density of rocks.PROGRESSI N GEOPHYSICS,2005,20(4):905-910.
[8]杨立强.测井约束地震反演综述.地球物理学进展,2003,18(3):530-534.YANG Li-qiang.A review of well log constrained seismicinversion.PROGRESS I N GEOPHYSICS,2003,18(3):530-534.
[9]张宏兵,杨长春.正则参数控制下的波阻抗约束反演.地球物理学报,2003,46(6):827-834.ZHANG Hong-bing,YANG Chang-chun.A constrainedimpendence inversion method controlled by regularizedcontrolled.Chinese J.Geophysics,2003,46(6),827-834.
[10]刘爱群,盖永浩.测井约束反演过程中测井资料统计分析研究.地球物理学进展,2007,22(5):1487-1491.LIU Ai-qun,GAI Yong-hao.Analysis and research of loginformation in the process of oil well logging restraintinversion.PROGRESS I N GEOPHYSICS,2007,22(5):1487-1491.
[11]马劲风.地震勘探中的广义弹性阻抗正反演.地球物理学报,2003,46(1):118-124.MA Jin-feng.Forward modeling and inversion method ofgeneralized elastic impedance in seismic exploration.ChineseJ.Geophys,2003,46(1):118-124.
[12]姚逢昌,甘利灯.地震反演的应用与限制.石油勘探与开发,2000.27(2):53-58.YAO Feng-chang,GAN Li-deng.Application and restrictionof seismic inversion.Petroleum Exploration andDevelopment,2000.27(2):53-58.
[13]P.An,W.M.Moon.Reservoir Characterization Using Feedforward Neural Networks[C].SEG,2005,258-260.
[14]M.M.Saggaf,M.Nafi Toksozz,H.M.Mustafa.Estimationof reservoir properties from seismic data by smooth neuralnetworks.Geophysics,2003,68(6):220-236.
[15]Amit K Ray and Samir Biswal.An efficient method of effectiveporosity prediction using an unconventional attribute throughmulti-attribute regression and probabilistic neural network:Acase study in a deep-water gas field,East Coast of India[C].SEG,2010,1413-1417.
[16]Specht,Donald.Probabilistic neural networks.Neuralnetworks,1990,2:109-118.
[17]Malleswar Yenugu,Jeremy C.Fisk,Kurt J.Marfurt..Probabilistic Neural Network inversion for characterization ofcoalbed methane[C].SEG,2010,2906-2910.
[18]Hampson,D.,J.Schuelke,J.Quirein.Use of multiattributetransforms to predict log properties from seismic data.Geophysics,2001,66(1),220-236.
[19]Pramanik,A.G.,V.Singh,R.Vig,A.K.Srivastava,etal.Estimation of effective porosity using geostatistics andmultiattribute transforms:A case study.Geophysics,2004,69,352-372.
[20]Russell,B.,D.Hampson,J.Schuelke,et al.Multiattributeseismic analysis.The Leading Edge,1997,16(10):1439-1443.
[21]Somanath Misra,Satinder Chopra,John Zhang.Neural networkregression analysis and post-stack inversion-A comparison[C].SEG,2010,1473-1477.
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