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The Classification of Low Permeable and Low Yield Reservoir Based on Grey Relational Clustering Analysis

机译:基于灰色关系聚类分析的低渗和低产量储层分类

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In accordance with the non-dimensional data feature of low permeable and low yield reservoir, this paper defines the distance between non-dimensional vectors and establishes a grey correlation degree quantification model of non-dimensional data series, which exploits relevance weighting method and objective weighting method to determine the comprehensive weight of classification indexes respectively and establishes a grey clustering analysis model to sort the oil wells and obtain the maximum spanning tree to classify the low permeable and low yield reservoir in a certain confidence level. The actual classification results of the two laminated production wells of Baoziwan reservoir of Changqing oilfield shows the grey relational clustering analysis of low permeable and low yield reservoir classification has extensive adaptability for non-dimensional data, and the weight is determined rationally, the method could classify oil wells under different confidence level according to different requirement, which has preferable guidance to practical problems.
机译:根据低渗透率和低产量储存器的非尺寸数据特征,本文定义了非维度矢量之间的距离,并建立了非维数据序列的灰色相关度量化模型,其利用相关性加权方法和客观加权分别确定分类指标综合重量的方法,建立灰色聚类分析模型,以对油井进行排序,获得最大的跨度树,在一定置信水平中对低渗透率和低产量储存器进行分类。长庆油田宝子储库的两个层压生产井的实际分类结果显示了低渗透性和低产量水库分类的灰色关系聚类分析对非尺寸数据的广泛适应性,并且重量是合理的,该方法可以分类根据不同的要求,油井在不同的置信水平下,这对实际问题具有更优选的指导。

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