The Prediction of Permeability From Well Logging Data Based on Reservoir Zoning, Using Artificial Neural Networks in One of an Iranian Heterogeneous Oil Reservoir

Abstract The distinct characteristics of Iranian oil reservoirs, such as high pressure, heterogeneity and anisotropy, high thickness, carbonation, huge size, and presence of cracks and various rock types, lead to deficiency of present applications of neural network methods. The authors attempt to improve the proficiency of present methods in one of Iranian heterogeneous oil reservoirs for permeability prediction using the well logging data, by zoning the reservoir on the basis of geology characteristics and sorting the data in correspondence. The obtained results from the well logging data using artificial neural networks are compared with the measured permeability in core analysis experiments. The appropriate compatibility of the results confirms the proposed method.