智能井非线性预测控制器设计

Design of Nonlinear Model Predictive Controller for Intelligent Well

随着石油开采中出现的新技术——智能井的应用,井控由地面转移到地下。为了解决地层物理属性难以准确获得以及流体流动的强非线性给井下控制带来的困难,研究了带有模型不确定性的非线性预测控制器。首先建立了带有不确定性的预测控制模型;然后基于反馈线性化和反步设计的思想设计非线性预测控制器。该控制器在模型带有不确定性时更易使闭环系统稳定,且动态特性良好。以北海油田某区块为例进行的仿真研究结果验证了控制器是有效的。

Applying of intelligent well, which is frontier technology used in oil production industry, transfers well controller from well surface to down hole. To resolve the difficulties of down hole control, which are arisen from the impossibility of acquiring the exact reservoir parameters and the strongly nonlinearity of fluid flow, a nonlinear model predictive controller for model with uncertainty was designed. Firstly, a control model with uncertainty was built. Then, a nonlinear model predictive controller was proposed by using feedback linearization method and backstepping design. By using the controller, not only the stability of closed loop system can be acquired more easily, but also the dynamic behavior is good even uncertainty exited in the model. The validity of the controller can be verified by simulation results of a reservoir located at North Sea Oilfield.