Closed-Loop Feedback Control for Production Optimization

Abstract

This article, written by Senior Technology Editor Dennis Denney, contains highlights of paper SPE 150096, ’Closed-Loop Feedback Control for Production Optimization of Intelligent Wells Under Uncertainty,’ by F.A. Dilib, SPE, and M.D. Jackson, SPE, Imperial College, London, prepared for the 2012 SPE Intelligent Energy International, Utrecht, the Netherlands, 27-29 March. The paper has not been peer reviewed. Most optimization methods are model based and are effective only if the model or ensemble of models used in the optimization captures all possible reservoir behaviors at the individual well and at the completion level. Closed-loop control based on direct feedback between reservoir monitoring and inflow-valve settings can yield close-to-optimal gains in net present value (NPV) compared with uncontrolled production, even if the reservoir does not behave as predicted. Closed-loop feedback control can mitigate uncertain reservoir behavior. Introduction Intelligent wells are equipped with downhole sensors to monitor the well and reservoir conditions and with valves to control the flow of fluid from the reservoir into the well. This combination of monitoring and control technologies has potential to improve hydrocarbon recovery. However, considerable challenges remain in formulating control strategies to operate the valves during production, particularly when there is uncertainty associated with the reservoir description. Inflow control can be open or closed loop. Open-loop control may be effective if the reservoir geology and drive mechanism are well understood, enabling prediction of inflow with confidence by use of reservoir and well models, and if the predicted inflow does not change significantly with time during production. The well can then be configured such that hydrocarbon production (or some other objective function) is maximized by optimizing the inflow profile along the well by use of fixed control devices (FCDs) sized before installation. Closed-loop control is facilitated by adjustable inflow-control valves (ICVs) installed in intelligent wells. The settings of these valves can be varied to optimize the inflow profile along the well in response to monitored data obtained from downhole sensors or to predictions of reservoir and well models. Reactive strategies change the settings of ICVs in response to adverse changes in flow, such as the arrival of unwanted fluid measured in the well or in the adjacent reservoir. Proactive strategies change the settings of ICVs in response to changes in flow measured or predicted in the reservoir at some distance from the well. The advantage of proactive control is that potential problems, such as the approach of unwanted fluid, can be mitigated before they affect production from the well. The challenge for both open- and closed-loop-control strategies is to determine the optimal response of the flow control at the well. This is a difficult problem because the optimal response typically is well and reservoir specific and it may vary through time. The aim was to investigate whether simple closed-loop-control strategies (based on direct feedback between ICV settings and surface or downhole measurements) can enhance production and mitigate reservoir uncertainty.