Investigating Proxy Models for a Production System in Integrated Simulations with Oil Reservoir

Document Type : Research Paper


Center for Energy and Petroleum Studies, University of Campinas, Campinas, Brazil


The work evaluates Proxy model application representing the production system for integrated simulation with reservoir aimed at reducing computational time, while preserving the representativeness of financial return and hidrocarbon production behavior in relation to a reference model.
The production system’s Proxy models are developed through response surface methodology (RSM) and artificial neural network (ANN) that are generated and validated from a medium fidelity model (MFM). The validation is performed by cross-check simulations.
The RSM-Based Proxy model obtained highest representativeness combining discrete variables (pipe segment diameters and the gas flow rate for artificial lift) with splitted continuous variables (lengths of the production column and flowline, liquid rate and water cut) using several response surfaces. The ANN-Based Proxy model enhanced representativeness, combining all variables, by increasing the number of MFM samples for ANN training. In our case, RSM-Based Proxy model was selected due lower residual than ANN-Based Proxy model.
The results from the production strategy of the simulated Proxy model in the MFM showed a difference of 4% in net present value compared to the simulation of the reference model, inside a production strategy optimization process. The reduction of computational time was close to 30% with the selected Proxy model, which presents an advantage of using the proposed approach in optimization applications.
The developed methodology provides an alternative to replace more robust production system models in integrated simulations with several advantages, such as: reduction of computational times, applications in more complex problems, and better exploring uncertainties to provide faster decision making.