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Model predictive automatic control of sucker rod pump system with simulation case study

机译:抽油杆泵系统的模型预测自动控制与仿真案例研究

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摘要

This work enables accelerated fluid recovery in oil and gas reservoirs by automatically controlling fluid height and bottomhole pressure in wells. Several literature studies show significant increase in recovered oil by determining a target bottomhole pressure but rarely consider how to control to that value. This work enables those benefits by maintaining bottomhole pressure or fluid height. Moving Horizon Estimation (MHE) determines uncertain well parameters using only common surface measurements. A Model Predictive Controller (MPC) adjusts the stroking speed of a sucker rod pump to maintain fluid height. Pump boundary conditions are simulated with Mathematical Programs with Complementarity Constraints (MPCCs) and a nonlinear programming solver finds a solution in near real-time. A combined rod string, well, and reservoir model simulate dynamic well conditions, and are formulated for simultaneous optimization by large-scale solvers. MPC increases cumulative oil production vs. conventional pump off control by maintaining an optimal fluid level height. (C) 2018 ElsevierLtd. Allrightsreserved.
机译:通过自动控制井中的流体高度和井底压力,这项工作可以加快油气储层的采收率。多项文献研究表明,通过确定目标井底压力可以显着提高采出油量,但很少考虑如何控制该值。这项工作通过保持井底压力或流体高度来实现这些好处。 “移动层估算”(MHE)仅使用常见的地面测量来确定不确定的井参数。模型预测控制器(MPC)调节抽油杆泵的冲程速度,以保持流体高度。使用具有互补约束(MPCC)的数学程序对泵边界条件进行仿真,并且非线性编程求解器可以近乎实时地找到解决方案。组合的杆柱,井和储层模型可模拟动态井况,并为大型求解器的同时优化制定了公式。与传统的泵送控制相比,MPC通过保持最佳的液位高度来提高累计产油量。 (C)2018爱思唯尔有限公司。版权所有。

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