关键词: 邻域, 粗糙集, 属性约简, 支持向量机

Abstract: This paper uses neighborhood rough set theory to the attributes reduction of oil-bearing reservoir and puts the residuary attributes reduction as the input variables of support vector machine to carry on an empirical study in the three wells oilfield reservoir type，the results of which are compared with the artificial neural network method，which show that the method is effective and feasible.Specific steps：firstly，neighborhood rough set is used to predigest the input attributes as a front pretreatment system and eliminate the redundant information，then put the remaining attributes as a Support Vector Machine（SVM） input variables，while the SVM as a rear system，it not only eliminates duplication of information between indicators，but also reduces the dimension.They make cooperation mutually，thus obtains the better measure results.

Key words: neighborhood, rough set, attributes reduction, support vector machine