关键词: 测井岩性识别,SVM,最优数据

Abstract: Rock-soil is a kind of extremely complex material,and it will encounter a lot of influence,these factors include the slip,fracture,rain erosion,corrosion and other natural factors and artificial factors.So many impacts result in the identification of lithology will produce a large number of error data.In the large amounts of data information optimization processing algorithm,support vector machine (Support Vector Machine,SVM) is a widely concerned optimization method.But the traditional SVM method is time-consuming,so we optimized the traditional SVM,made the leave one out cross method change to K fold cross method,and used optimized SVM optimize large data searching.Comparative test results show that the method has the advantages of high recognition accuracy, quick convergence speed,compared with the traditional optimization algorithm of support vector machine.

Key words: Logging lithology identification,SVM,Optimal data