The Support Vector Machines for predicting the reservoir thickness

Reservoir thickness is an important parameter in the description and simulation of reservoir. The principle and method of the Support Vector Machines are introduced in this paper. Based on the previous study of seismic interpretation, 100 sets of data of the five seismic attributes and the reservoir thickness in a work area are used as the example for predicting the reservoir thickness. The results prove that this method may throw important light on the predicting and computing the reservoir thickness.