Daily production optimization of gas-lifted oil field with MPC framework

Abstract

The continuous increase in energy demand requires alternative solutions and sustainable energy production from the existing sources. Thus, the existing mature oil fields require optimization and gas injection is one option for enhancing the reservoir's productivity.

A steady-state model within a Model Predictive Control structure for daily production optimization in gas-lifted oil fields has been developed to optimize the production from mature oil fields. The model is integrated with a dynamic reservoir. The reservoir model is based on the multiphase flow and dynamic pressure within the reservoir. Simulations were performed to study the uncertainty parameters such as reservoir pressure, productivity index (PI), and water cut (WC).

Two different reservoir models were considered for the DPO from the gas-lifted oil reservoir. A modified "Egg Model" and the SPE9 benchmark model were used to study the performance of well in terms of well. These two models were simulated with and without optimization. A constant gas lift rate is supplied for the non-optimized case. The simulation showed a dynamic gas injection rate is required to optimize the production process for both reservoir models.

The study further reveals that the effectiveness of the optimization strategy is influenced by the reservoir's geological characteristics and heterogeneity. The Egg model showed a more pronounced response to optimization compared to the SPE9 model due to its relatively homogeneous channelized structure. The developed model was able to optimize the production outcomes in the gas-lifted reservoirs.