多属性模糊聚类在辽河滩海沉积相研究中的应用
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摘要
由于辽河滩海地质条件复杂以及勘探资料的局限性,使得该地区存在沉积相变快,物源分布不清等问题,严重影响了辽河油田对勘探目标的认识和评价.本文针对研究区钻井少且分布不均等难题,提出采用多属性模糊聚类地震相自动划分技术进行沉积相的划分.该技术通过交会图、相关系数等优化方法选择出对沉积砂体最敏感的地震属性,再结合模糊聚类方法将优选出的多个地震属性进行聚类,使反映相同沉积体的地震属性聚为一类,形成地震相图.通过综合岩心宏观和微观特征描述,结合测井、录井和分析化验等资料,对辽河滩海西部地区古近系沙河街组的沉积相进行了细致地分析.
As the complexity of geological condition and limitation of exploration data in the beach area of Liaohe Basin,it make sedimentary facies change fast and provenance distribution unclearly in this region.It seriously affected Liaohe oil field on the understanding and evaluation of exploration targets.According to the problem of few and uneven distribution drilling wells in the study area,this paper propose automatic recognizing technique of seismic facies using multi-attribute fuzzy clustering to research sedimentary facies.The technique use optimization methods of cross plot and correlation coefficient to select the most sensitive seismic attributes of depositional sand body,combine with fuzzy clustering method to process the multiple optimization seismic attributes.Thus the same seismic attribute response of depositional body were clustered into one group.Through integrating macro and micro characterization of core and combining logging,analysis assay and other data,this paper thoroughly analyse sedimentary facies of the Eogene Shahejie formation in the western beach area of Liaohe basin.
As the complexity of geological condition and limitation of exploration data in the beach area of Liaohe Basin,it make sedimentary facies change fast and provenance distribution unclearly in this region.It seriously affected Liaohe oil field on the understanding and evaluation of exploration targets.According to the problem of few and uneven distribution drilling wells in the study area,this paper propose automatic recognizing technique of seismic facies using multi-attribute fuzzy clustering to research sedimentary facies.The technique use optimization methods of cross plot and correlation coefficient to select the most sensitive seismic attributes of depositional sand body,combine with fuzzy clustering method to process the multiple optimization seismic attributes.Thus the same seismic attribute response of depositional body were clustered into one group.Through integrating macro and micro characterization of core and combining logging,analysis assay and other data,this paper thoroughly analyse sedimentary facies of the Eogene Shahejie formation in the western beach area of Liaohe basin.
引文
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[18]朱剑兵,赵培坤.国外地震相划分技术研究新进展[J].勘探地球物理进展,2009,32(3):167-171.Zhu J B,Zhao P K.Advances in seismic facies classificationtechnology abroad[J].Progress in Exploration Geophysics(in Chinese),2009,32(3):167-171.
[19]Coleo U T,Poupon M,Azbel K.Unsupervised seismic faciesclassification:A review and comparison of techniques andimplementation[J].The Leading Edge,2003,22(10):942-953.
[20]石洪波,于剑,黄厚宽.一种有效的FCM算法的实现方式[J].铁道学报,2003,25(1):63-67.Shi H B,Yu J,Huang H K.An effective implementationmethod of Fuzzy C-Means algorithm[J].Journal of the ChinaRailway Society(in Chinese),2003,25(1):63-67.
[21]杨培杰,印兴耀,张广智.模糊C均值地震属性聚类分析[J].石油地球物理勘探,2007,42(3):322-324.Yang P J,Yin X Y,Zhang G Z.Cluster analysis of seismicattributes by fuzzy C-mean algorithm[J].Oil GeophysicalProspecting(in Chinese),2007,42(3):322-324.
[22]Kanungo T,Mount D M,Netanyahu N S,et al.An efficientK-means clustering algorithm[J].IEEE Trans.PatternAnal.Mach.Intell.,2002,24(7):881-892.
[23]李树军,纪宏金.对应聚类分析与变量选择[J].地球物理学进展,2005,20(3):694-697.Li S J,Ji H J.Correspondence cluster analysis and variableselection[J].Progress in Geophysics(in Chinese),2005,20(3):694-697.
[24]Lefeuvre F E,Wrolstad K H,Zou K S,et al.Sand-shaleratio and sandy reservoir properties estimation from seismicattributes:An integrated study[C].//65th Annual Internat.Mtg.,Soc.Expl.Geophys.,Expanded Abstracts,1995:108-110.
[25]Lawrence P,Aramco S,Arabia D S.Seismic attributes in theCharacterization of small-scal reservoir in Abqaiq Field[J].The Leading Edge,1998,17(4):521-525.
[2]孙素青.辽河盆地西部凹陷沙河街组西八千扇体沉积特征及其控制因素[J].古地理学报,2001,3(2):92-98.Sun S Q.Sedimentary characteristics and controlling factors ofXibaqian Fan of Shahejie formation,West Depression,LiaoheBasin[J].Journal of Palaeogeography(in Chinese),2001,3(2):92-98.
[3]吴兴录,邹丙方.辽河滩海地区下第三系沉积体系及分布特征[J].特种油气藏,2002,9(3):13-17.Wu X L,Zou B F.Sedimentary system and distributionfeatures of early Tertiary in Liaohe tidal zone[J].Special Oiland Gas Reservoirs(in Chinese),2002,9(3):13-17.
[4]Chen Q,Sidney S.Seismic attribute technology for reservoirforecasting and monitoring[J].The Leading Edge,1997,16(5):220-231.
[5]程耀清,蔡冬梅.地震相技术应用实例[J].石油地球物理勘探,2007,42(S1):79-82.Cheng Y Q,Cai D M.Application case of seismic phasetechnique[J].Oil Geophysical Prospecting(in Chinese),2007,42(S1):79-82.
[6]王利田,苏小军,官仁顺,等.地震属性分析在彩16井区储层预测中的应用[J].地球物理学进展,2006,21(3):922-925.Wang L T,Su X J,Guang R H,et al.The appliation ofseismic attribute analyscs in predicating reservoir of cai 16area[J].Progress in Geophysics(in Chinese),2006,21(3):922-925.
[7]季敏,王尚旭.灰色理论在地球物理勘探开发中的应用综述[J].地球物理学进展,2005,20(4):1164-1170.Ji M,Wang S X.The application of grey theory in geophysicalexploration[J].Progress in Geophysics(in Chinese),2005,20(4):1164-1170.
[8]Gao D L.Application of seismic tex ture model regression toseismic facies characterization and interpretation[J].TheLeading Edge,2008,27(3):394-397.
[9]张治国,杨毅恒,夏立显.自组织特征映射神经网络在测井岩性识别中的应用[J].地球物理学进展,2005,20(2):332-336.Zhang Z G,Yang Y H,Xia L X.The application of self-organizing feature map neural network to logging lithologicalidentification[J].Progress in Geophysics(in Chinese),2005,20(2):332-336.
[10]朱剑兵.地震相划分方法研究新进展[J].油气地球物理,2008,6(3):6-9.Zhu J B.New progress at the analysis on seismic faciesdivision[J].Petroleum Geophysics(in Chinese),2008,6(3):6-9.
[11]张明振,谭明友,王兴谋.济阳坳陷第三系隐蔽藏储层预测配套技术[J].地球物理学进展,2005,20(1):42-48.Zhang M Z,Tan M Y,Wang X M.Combined describingtechniques of tertiary hidden hydrocarbon reservoir in Jiyangdepression[J].Progress in Geophysics(in Chinese),2005,20(1):42-48.
[12]Michelena R J.Similarity analysis:a new tool to summarizeattrbute information[J].The Leading Edge,1998,17(4):62-67.
[13]张延玲,肖高杰.地层岩性油气藏地震属性的研究和应用———以准噶尔盆地永1井区为例[J].地球物理学进展,2010,25(4):1332-1338.Zhang Y L,Xiao G J.Research and application of seismicattributions of fromation lithology hydrocarbon reservoirs inthe Yong 1area as an example[J].Progress in Geohpys.(inChinese),2010,25(4):1332-1338.
[14]刘保国,刘力辉.实用地震沉积学在沉积相分析中的应用[J].石油物探,2008,47(3):266-271.Liu B G,Liu L H.Application of applied seismicsedimentology in sedimentary facies analysis[J].GeophysicalProspecting for Petroleum(in Chinese),2008,47(3):266-271.
[15]Neves F A,Triebwasser H.Multi-attribute seismic volumefacies classification for predicting fractures in carbonatereservoirs[J].The Leading Edge,2006,25(6):698-700.
[16]Brown A R.Seismic attributes and their classification[J].The Leading Edge,1996,15(10):36-41.
[17]吕公河,于常青,董宁.叠后地震属性分析在油气田勘探开发中的应用[J].勘探地球物理进展,2006,21(1):161-166.LüG H,Yu C Q,Dong N.The application of post-stackseismic attribute analysis in the oil-gas exploration anddevelopment[J].Progress in Exploration Geophysics(inChinese),2006,21(1):161-166.
[18]朱剑兵,赵培坤.国外地震相划分技术研究新进展[J].勘探地球物理进展,2009,32(3):167-171.Zhu J B,Zhao P K.Advances in seismic facies classificationtechnology abroad[J].Progress in Exploration Geophysics(in Chinese),2009,32(3):167-171.
[19]Coleo U T,Poupon M,Azbel K.Unsupervised seismic faciesclassification:A review and comparison of techniques andimplementation[J].The Leading Edge,2003,22(10):942-953.
[20]石洪波,于剑,黄厚宽.一种有效的FCM算法的实现方式[J].铁道学报,2003,25(1):63-67.Shi H B,Yu J,Huang H K.An effective implementationmethod of Fuzzy C-Means algorithm[J].Journal of the ChinaRailway Society(in Chinese),2003,25(1):63-67.
[21]杨培杰,印兴耀,张广智.模糊C均值地震属性聚类分析[J].石油地球物理勘探,2007,42(3):322-324.Yang P J,Yin X Y,Zhang G Z.Cluster analysis of seismicattributes by fuzzy C-mean algorithm[J].Oil GeophysicalProspecting(in Chinese),2007,42(3):322-324.
[22]Kanungo T,Mount D M,Netanyahu N S,et al.An efficientK-means clustering algorithm[J].IEEE Trans.PatternAnal.Mach.Intell.,2002,24(7):881-892.
[23]李树军,纪宏金.对应聚类分析与变量选择[J].地球物理学进展,2005,20(3):694-697.Li S J,Ji H J.Correspondence cluster analysis and variableselection[J].Progress in Geophysics(in Chinese),2005,20(3):694-697.
[24]Lefeuvre F E,Wrolstad K H,Zou K S,et al.Sand-shaleratio and sandy reservoir properties estimation from seismicattributes:An integrated study[C].//65th Annual Internat.Mtg.,Soc.Expl.Geophys.,Expanded Abstracts,1995:108-110.
[25]Lawrence P,Aramco S,Arabia D S.Seismic attributes in theCharacterization of small-scal reservoir in Abqaiq Field[J].The Leading Edge,1998,17(4):521-525.
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