摘要: |
针对曲流河点坝厚砂体内储M非均质性表征,提出一种点坝内部构型的嵌人式建模方法。该方法以点坝级次 三维模型及点坝内部构铟分折结果为基础,依次通过荜于三维向量场的侧积面模式拟合、侧枳而趋势控制的侧积层 厚度插值以及网格局部加密的侧积层模型嵌入等3个主要技术环节,形成一套完整的嵌入式构型建模技术流程及算 法实现,并应用孤岛油田某区块曲流河点坝储层内部构型的4维建模实例.对建模方法的有效性进行验证。结果表 明:嵌人式构型建模方法4建立与井点条件化的点坝内部蜊积夹层精细二维模型,并可对井间侧积层分布进行有效 预测;采用的网格局部加密侧积层模型嵌人方义优化了不同构型级次及尺寸规模构型单元的三维网格表示。 |
关键词: 曲流河 点坝 内部构铟 侧枳层 嵌人式地质建模 孤岛油田 |
DOI:10.3969/j.issn.1673-5005.2012.03.001 |
分类号:TE 319 |
基金项目:国家科技重大专项课题(201IZX05009 - 003 );国家自然科学基金项目(40902035);教育部博士点新教师基金项目 (20090007120003) |
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Embedding modeling method for internal architecture of point bar sand body in meandering river reservoir |
FAN Zheng1,2,WU Sheng-he1,YUE Da-li1,BI Dong-liang2,WEN Li-feng3
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(1. College of Geosciences in China University of Petroleum.,Beijing 102249, China ;2. Tebn Hi-Tech Company Limited Beijing 100085, China ;3. Research Institute of Exploration and Production, SI ISO PEC, Beijing 100083, China)
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Abstract: |
A new internal architecture embedding modeling method was proposed for the reservoir heterogeneity of latera] accretion shale beddings ( LA) of point bar sand body in meandering river reservoir. Based on the point bar 3D grid model and the internal architecture analysis results, three-order modeling technology links were applied to form a full set of embedding modeling technology process and the algorithm implementationt which includes 3D vector field lateral accretion pattern filling modeling, the LA thickness distribution interpolation in the control of lateral accretion surface trend and partial grid subdividing model embedding process. And then, the validity of the modeling method was validated. The results show that the embedding modeling melhod can be used to establish fine 3D model of LA which conditions to wells, and the LA distribution between wells can be drawn from this fine model. An optimized grid description of different levek and scale architecture units was provided through partiai grid subdividing model embedding technology. |
Key words: meandering river point bar internal architecture lateral accretion shale beddings embedding modeling Gud-ao Oilfield |