密井网区井震结合进行沉积微相研究及储层预测方法探讨——以大庆杏树岗油田杏56区为例
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摘要
随着中国油气田开发程度的逐步加深,有效预测井间砂体的分布已成为高效开采与提高采收率的核心问题。文中以大庆杏树岗油田杏56区块为例,尝试利用井、震有机结合的方法进行精细沉积微相展布的研究,对进入特高含水阶段的油田进行井间砂体的预测。在密测网地震层位追踪的前提下提取多种地震属性,以反距离加权平均法提取井点属性,并采用聚类方法对提取的井点地震属性和井点储层参数进行多元统计相关性分析,以确定聚类分析中使用的地震信息,进而建立多元一次方程,描述敏感地震信息与储层参数的桥梁,以便用井、震信息综合预测井间储层参数的变化,由此编制出目的层段的沉积微相平面展布图,并结合生产动态资料进行验证。其成果在实际生产中得到较好的验证。
As the exploitation of oil and gas fields in China is rapidly developing,the effective prediction of the distribution of interwell sand has become an urgent issue in achieving efficient exploitation and improving oil recovery.Based on the integrated information of well and seismic data,a study of the fine microfacies and the prediction of interwell sand in super high water cut oil field at Daqing Xingshugang oil field Xing 56 block was carried out.Seismic attributes were extracted on the premise of seismic horizon tracing in a dense framework and the seismic attributes on wells were determined by inverse distance weighted mean method.The clustering procedure correlation analysis method in the multivariate statistical correlation analysis between seismic attributes and well data was employed to build up the relationship between the seismic information and the reservoir information and to predict the changes of interwell reservoir data.The planar map of depositional microfacies distribution in target segments was compiled using the result of relationship among rock,logging and seismic data,and it was verified by production performance data.
As the exploitation of oil and gas fields in China is rapidly developing,the effective prediction of the distribution of interwell sand has become an urgent issue in achieving efficient exploitation and improving oil recovery.Based on the integrated information of well and seismic data,a study of the fine microfacies and the prediction of interwell sand in super high water cut oil field at Daqing Xingshugang oil field Xing 56 block was carried out.Seismic attributes were extracted on the premise of seismic horizon tracing in a dense framework and the seismic attributes on wells were determined by inverse distance weighted mean method.The clustering procedure correlation analysis method in the multivariate statistical correlation analysis between seismic attributes and well data was employed to build up the relationship between the seismic information and the reservoir information and to predict the changes of interwell reservoir data.The planar map of depositional microfacies distribution in target segments was compiled using the result of relationship among rock,logging and seismic data,and it was verified by production performance data.
引文
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[9]Shi J,Xiong Y.Multivariate statistical and cluster analysis method appliedin exploit of natural resources[J].Journal of Shandong University of Technology:Science and Technology Edition,2003,17(1):81-83(in Chinese).
[10]Yu X L.Multivariate statistical analysis[M].Beijing:China Statistics Press,1999:61-97(in Chinese).
[11]Su J M,Ruan S Y,Wang Y L.Matlab engineering mathe-matics[M].Beijing:Publishing House of Electronics Indus-try,2005:110-114(in Chinese).
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[14]Deng H W,Wang H L,Zhu YJ,et al.High resolution se-quence stratigraphy—fundamentals and applications[M].Beijing:Petroleum Industry Press,2002:161-181(in Chi-nese).
[15]Deng H W,Wang H L.Application of high-resolution se-quence stratigraphic correlation to fluvial facies[J].Oil&Gas Geology,1997,18(2):90-114(in Chinese).
[16]Yu X H.Reservoir sedimentology in clastic rock[M].Bei-jing:PetroleumIndustry Press,2002:232-237(in Chinese).
[1]曹卿荣,李佩,孙凯,等.应用地震属性分析技术刻画河道砂体[J].岩性油气藏,2007,19(2):93-96.
[2]赵军.地震属性技术在沉积相研究中的应用[J].石油物探,2004,43:67-69.
[8]赵政璋,赵贤正,王英民,等.储层地震预测理论与实践[M].北京:科学出版社,2005:209-221.
[9]石军,熊苡.多元统计、聚类分析法在自然资源开发中的应用[J].山东理工大学学报:自然科学版,2003,17(1):81-83.
[10]于秀林.多元统计分析[M].北京:中国统计出版社,1999:61-97.
[11]苏金明,阮沈勇,王永利.Matlab工程数学[M].北京:电子工业出版社,2005:110-114.
[12]刘波,赵翰卿,李广月,等.储层砂质辫状河的识别——以大庆喇嘛甸-萨尔图油田西部PI-(2～3)为例[J].石油学报,2002,23(2):43-47.
[13]吕晓光,李长山,蔡希源,等.松辽大型浅水湖盆三角洲沉积特征及前缘相储层结构模型[J].沉积学报,1999,17(4):572-577.
[14]邓宏文,王红亮,祝永军,等.高分辨率层序地层学——原理及应用[M].北京:石油工业出版社,2002:161-181.
[15]邓宏文,王洪亮.高分辨率层序地层对比在河流相中的应用[J].石油与天然气地质,1997,18(2):90-114.
[16]于兴河.碎屑岩系油气储层沉积学[M].北京:石油工业出版社,2002:232-237.
[2]Zhao J.Application of the seismic attribution technique in the study of sedimentary facies[J].Geophysical Prospecting for Petroleum,2004,43:67-69(in Chinese).
[3]Todorov I T.Integration of3C-3Dseismic data and well logs for rock property estimation[D].Alberta:University of Cal-gary,2000:53-80.
[4]Ai-marhoun MI.Application of multi-seismic attributes in estimating reservoir properties[D].Saudi Arabia:King Fahd University of Petroleumand Mineral,1997:11-20.
[5]Hart B S.Validating seismic attribute studies:beyond statis-tics[J].The Leading Edge,2002,21(10):1016-1021.
[6]Tebo J M.Use of volume-based3-Dseismic attribute analysis to characterize physical property distribution:a case study to delineate reservoir heterogeneity at the Appltion Field,SW Alabama[D].Montréal:McGill University,2003:22-30.
[7]Costa F,Rodriguez C,Sarzenski D,et al.Using seismic at-tributes in petrophysical reservoir characterization[J].Amer-ica:2007,SPE107935:1-5.
[8]Zhao Z Z,Zhao XZ,Wang Y M,et al.Theories and applica-tions in reservoir seismic prediction[M].Beijing:Science Press,2005:209-221(in Chinese).
[9]Shi J,Xiong Y.Multivariate statistical and cluster analysis method appliedin exploit of natural resources[J].Journal of Shandong University of Technology:Science and Technology Edition,2003,17(1):81-83(in Chinese).
[10]Yu X L.Multivariate statistical analysis[M].Beijing:China Statistics Press,1999:61-97(in Chinese).
[11]Su J M,Ruan S Y,Wang Y L.Matlab engineering mathe-matics[M].Beijing:Publishing House of Electronics Indus-try,2005:110-114(in Chinese).
[12]Liu B,Zhao H Q,Li G Y,et al.Sand bodyidentification of braided river reservoir—an example fromthe PI-(2～3)West of Lamadian-Saertu oilfield,Daqing,China[J].Acta PetroleiSinica,2002,23(2):43-47(in Chinese).
[13]Lu X G,Li C S,Cai X Y,et al.Depositional characteristics and front facies reservoir framework model in Songliao shal-lowlacustrine delta[J].Acta Sedimentologica Sinica,1999,17(4):572-577(in Chinese).
[14]Deng H W,Wang H L,Zhu YJ,et al.High resolution se-quence stratigraphy—fundamentals and applications[M].Beijing:Petroleum Industry Press,2002:161-181(in Chi-nese).
[15]Deng H W,Wang H L.Application of high-resolution se-quence stratigraphic correlation to fluvial facies[J].Oil&Gas Geology,1997,18(2):90-114(in Chinese).
[16]Yu X H.Reservoir sedimentology in clastic rock[M].Bei-jing:PetroleumIndustry Press,2002:232-237(in Chinese).
[1]曹卿荣,李佩,孙凯,等.应用地震属性分析技术刻画河道砂体[J].岩性油气藏,2007,19(2):93-96.
[2]赵军.地震属性技术在沉积相研究中的应用[J].石油物探,2004,43:67-69.
[8]赵政璋,赵贤正,王英民,等.储层地震预测理论与实践[M].北京:科学出版社,2005:209-221.
[9]石军,熊苡.多元统计、聚类分析法在自然资源开发中的应用[J].山东理工大学学报:自然科学版,2003,17(1):81-83.
[10]于秀林.多元统计分析[M].北京:中国统计出版社,1999:61-97.
[11]苏金明,阮沈勇,王永利.Matlab工程数学[M].北京:电子工业出版社,2005:110-114.
[12]刘波,赵翰卿,李广月,等.储层砂质辫状河的识别——以大庆喇嘛甸-萨尔图油田西部PI-(2～3)为例[J].石油学报,2002,23(2):43-47.
[13]吕晓光,李长山,蔡希源,等.松辽大型浅水湖盆三角洲沉积特征及前缘相储层结构模型[J].沉积学报,1999,17(4):572-577.
[14]邓宏文,王红亮,祝永军,等.高分辨率层序地层学——原理及应用[M].北京:石油工业出版社,2002:161-181.
[15]邓宏文,王洪亮.高分辨率层序地层对比在河流相中的应用[J].石油与天然气地质,1997,18(2):90-114.
[16]于兴河.碎屑岩系油气储层沉积学[M].北京:石油工业出版社,2002:232-237.
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