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What is Liquid Rate Modeling via Neural Networks about?

This study presents two artificial neural network models, the Cascaded Forward Neural Network (CFNN) and the Generalized Regression Neural Network (GRNN), for accurately estimating liquid flow rates through wellhead chokes, which is essential for optimizing oil production. The GRNN outperformed the CFNN with a low average absolute relative error of 2.329% and a high determination coefficient of 0.9922, while also providing interpretability through the SHAP method. The findings highlight the potential of the

Author

Saurabh Tewari

Language

EN