Artificial neural network based production forecasting for a hydrocarbon reservoir under water injection

NEGASH Berihun Mamo,YAW Atta Dennis

Table 6 Information related the optimum architecture of ANN model for oil production prediction.

Items Value/content Input 13 Number of hidden neuron 30 Output Oil flow rate Training algorithm Bayesian regularization R2 (Training) 0.983 R2 (Testing) 0.947 Number of epochs 946 Training time 103 s.