A new method to predict the reservoir porosity based on fuzzy-PCA and neural network

Porosity and permeability are the two fundamental and crucial reservoir parameters which are often used in reservoir description. However, the two properties are difficult to be measured and predicted, due to some influences such as rock type and cement and so on. In this paper, we proposed a new method combined of fuzzy theory, principal component analysis and the neural network to predict the porosity by well log in Yangerzhuang oil field. The experiment results demonstrate that the method in this paper can retain the information more effectively in the process of dimension reduction, and thus greatly the prediction accuracy can be improved.