Improved Simulation Efficiency for Optimising Inflow Control Device Completions Using Suitably Upscaled Models and Parallel Global Search Optimisation Techniques

Abstract

Inflow Control Device (ICD) completions can improve well performance by adjusting the inflow profile along the well and reducing the influx of unwanted fluids. The ultimate aim of using ICD completions is to provide maximum oil recovery and/or Net Present Value (NPV) over the life of the field. Proactive ICD optimisation studies use complex reservoir models and high-dimensional nonlinear objective functions to find the optimum ICD configurations over the life of the field. These complex models are generated from fine scale detailed geological models to accurately capture fluid flow behaviour in the reservoir. Although these high-resolution geological models can provide better performance predictions, their simulation runtimes can be computationally expensive and time consuming for performing proactive ICD optimisation studies that often require thousands of simulation runs. We propose a new workflow where we use upscaled and locally refined models coupled with parallelised global search optimisation techniques to improve the simulation efficiency when performing ICD optimisation and decision-making studies. Our approach preserves the flow behaviour in the reservoir and maintains the interaction between the reservoir and the well in the near wellbore region. Moreover, when coupled with parallel optimisation techniques, the simulation time is significantly reduced. We present an in-house code that couples global search optimisation algorithms (Genetic Algorithm and Surrogate Algorithm) with a commercial reservoir simulator to drive the ICD configurations. We evaluate the NPV as the objective function to determine the optimum ICD configurations. We apply and benchmark our approach to two different reservoir models to compare and analyse its efficiency and the optimisation results. Our analysis shows that our proposed approach reduces the run time by more than 80% when using the upscaled models and the parallel optimisation techniques. These results were based on a standard dual-core parallel desktop configuration. Additional results also showed further reduction in run time is possible when employing more processors. Additionally, when testing different ICD completion strategies (ICDs in producers only, ICDs in injectors only, and ICDs in both producers and injectors), the NPV can be increased by 9.6% for the optimised ICD completions. The novelty of our work is rooted in the much-improved simulation efficiency and better performance predictions that supports ICD optimisation and decision-making studies during field development planning to maximize profit and minimize risk over the life of the field.