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河流储层建筑结构要素的定量识别——以胜坨油田二区沙二段3砂层组为例
引用本文:冯建伟,戴俊生,冀国盛,黄文科. 河流储层建筑结构要素的定量识别——以胜坨油田二区沙二段3砂层组为例[J]. 沉积学报, 2007, 25(2): 207-213
作者姓名:冯建伟  戴俊生  冀国盛  黄文科
作者单位:中国石油大学地球资源与信息学院,山东东营,257061;中国石油大学地球资源与信息学院,山东东营,257061;中国石油大学地球资源与信息学院,山东东营,257061;中国石油大学地球资源与信息学院,山东东营,257061
基金项目:国家“十五”攻关项目(编号:2003BA613A-02)资助
摘    要:针对地下河流相储层内部建筑结构分析难度大、非均质性突出的问题,在岩芯、露头、钻井、测井资料分析的基础上,以胜坨油田二区沙二段3砂层组(胜二区S32)辫状河沉积体为例,运用Miall的结构要素分析法,进行层次界面解剖、岩相类型和建筑结构要素的划分,提取相应测井曲线特征参数,建立有效的结构要素定量模糊识别模型,并编成软件,对研究区进行了实际资料处理,结果与地质专家解释结果相当吻合,最后建立了储层建筑结构展布模型,精细表征了砂体间的接触方式和连通程度,为进行精确的储层预测和剩余油挖潜提供了地质依据。

关 键 词:河流储层  测井资料  建筑结构  模糊识别模型
文章编号:1000-0550(2007)02-0207-07
收稿时间:2006-05-02
修稿时间:2006-05-022006-07-17

The Quantitative Discrimination of Architectural Elements of Fluvial Reservoir
FENG Jian-wei,DAI Jun-sheng,JI Guo-sheng,HUANG Wen-ke. The Quantitative Discrimination of Architectural Elements of Fluvial Reservoir[J]. Acta Sedimentologica Sinica, 2007, 25(2): 207-213
Authors:FENG Jian-wei  DAI Jun-sheng  JI Guo-sheng  HUANG Wen-ke
Affiliation:Department of Geo Resource and Information, University of Petroleum ,Dongying Shandong 257061
Abstract:To discuss the problem that the analysis of interior architectural structures of underground fluvial reservoirs is difficult, and the heterogeneity is serious. Based on cores, outcrop, drilling and well log data, this paper analyzes the fluvial characteristics of the 3 Sand Sets in the 2 member of Shahejie Formation(S32) in 2 District, Shengtuo Oilfield(TDSO), and recognizes all kinds of hierarchical bounding surfaces, lithofacies and architectural elements in the sandbody according to Miall's suggestion. Then the paper analyzes well logs of the architectural elements, and extracts characteristic parameters, to establish quantitative fuzzy digital model and develop a set of effective software to discriminate the types of architectural elements, and the results coincide very well with the interpretation of the geological specialist. Finally, geological models are established by using this software in Shengtuo Oilfield, and this method provides scientific foundation for enhancing oil recovery in mature oilfield.
Keywords:fluvial reservoir   well log data   architectural elements   fuzzy discriminating models
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