THE APPLICATION OF THE SUPPORT VECTOR MACHINE TO THE RECOGNITION OF FLOODING FORMATION
ZHAO Jun1, CHENG Peng-fei1, LIU Di-yuan2, XU Wei-dong2
1. Institute of Resource and Environment, Southwest Petroleum University, Chengdu 610500, China;
2. Production Mill of Zhongyuan Oilfield, Sinopec, Puyang 457000, China
The support vector machine proposed by Vapnik is a newly-developed technique for data processing. It is suitable for the data processing based on a finite number of training samples,with special technique for restricting overfitting. In this paper,the support vector classification technique was used to make modeling on the relationships between the acoustic time, SP, deep induction resistivity, medium induction resistivity, density and water flood grade,with these parameters serving as input of the training samples and the character of the oil and gas as the output. This technique was used in the P oilfield, which shows that SVM can yield efficient modeling results.
赵军, 程鹏飞, 刘地渊, 徐卫东. 支持向量机在水淹层测井识别中的应用[J]. 物探与化探, 2008, 32(6): 652-655.
ZHAO Jun, CHENG Peng-fei, LIU Di-yuan, XU Wei-dong. THE APPLICATION OF THE SUPPORT VECTOR MACHINE TO THE RECOGNITION OF FLOODING FORMATION. Geophysical and Geochemical Exploration, 2008, 32(6): 652-655.
