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.