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PERMEABILITY PREDICTION FROM WIRELINE LOGS USING ARTIFICIAL NEURAL NETWORKS

The study presented here, is an artificial neural networks (ANNs) modeling in one of the carbonate reservoirs in the south of Iran. The permeability ANN is a three layer back propagation network. We have used two separate ANNs to model permeability. Initially, density, neutron, sonic and gamma ray logs were applied for input. Then depths data related to these log data were added to input, and finally results of the two networks have been compared. This comparison has shown that the accuracy of the model in the second case has been significantly improved.