Parametric Differentiable Flow Modeling for Fluid Production Optimization Under Flow Assurance Constraints
This work presents a Physics-Informed Neural Network (PINN) framework for multiphase steady-state production systems and its application to constrained production optimization. The PINN is constructed to approximate the coupled momentum and energy equations of a flowline–riser configuration with state-dependent thermop...