Hybrid Neural Network Performance Prediction Model for Gas Assisted Gravity Drainage Recovery Method Based on the Scaling Analysis

Abstract

Hybrid system is a potential tool to deal with nonlinear regression problems. The authors present an efficient prediction model for gas assisted gravity drainage injection recovery process based on artificial neural network (ANN) and dimensionless groups. Ant colony optimization (ACO) is applied to determine the network parameters. Results show that ACO optimization algorithm can obtain the optimal parameters of the ANN model with very high predictive accuracy. The predicted recovery from the ACO-ANN model, in comparison with other proposed models in literature, were in good agreement with those measured from simulations, and were comparable to those estimated from the other proposed models.

Keywords:

• neural network
• oil recovery
• ant colony
• scaling
• GAGD