Abstract：The kernel-based machine learning algorithms proposed in last few years are a novel class of non-linear techniques,one of which is kernel Fisher discriminanting analysis.The kernel Fisher discriminant analyses is the non-linear generalization of classic Fisher linear diseriminant based on the kernel functions and obtains the better results in the classificarion problem of real data.The paper introduced a lateral prediction approach of hydrocarbon reservoir based on kernel Fisher discriminanting analysis.The computational results of field data show that the performance of kernel Fisher discriminant is superior to those of Fisher linear discriminant,fuzzy pattern recognition and backward propagation neural networks in lateral prediction of hydrocarbon reservoir.
