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《Computer Applications of Petroleum》 2009-01
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OIL AND GAS RESERVOIR IDENTIFICATION BASED ON LEAST SQUARE SUPPORT VECTOR MACHINE

Zhong Yihua,Li Rong,Southwest Petroleum University  
Oil and gas reservoir identification is virtually a problem of pattern recognition in well logging interpretation.The new generation small sample learning algorithm——support vector machine,developed on statistical learning theory,is one of the powerful methods for pattern recognition up to now.The paper presents the least square support vector machine(LSSVM)for oil and gas reservoir identification according to the shortcomings of current methods.It has been used in Daqing oilfield.The results show that this method is faster and more accurate than artificial neural network and standard support vector machine.It is worth generalizing and to be studied.
【Fund】: 四川省教育厅重点项目:基于数据挖掘的支持向量机理论及应用研究(07ZA143)资助
【CateGory Index】: P631.8
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