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Optimal control of polymer flooding based on mixed-integer iterative dynamic programming

机译:基于混合整数迭代动态规划的聚合物驱最优控制

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Polymer flooding is one of the most important technologies for enhanced oil recovery. In this article, a mixed-integer optimal control model of distributed parameter systems (DPS) for the injection strategies is established, which involves the performance index as maximum of the profit, the governing equations as the fluid flow equations of polymer flooding and some inequalities constraints, such as polymer concentration and injection amount limitation. The control variables are the volume size, the injection concentration of each slug and the terminal flooding time. For the constant injection rate, the slug size is determined by the integer time stage length, and thus the integer variables are introduced in the DPS. To cope with the optimal control problem (OCP) of this DPS, a mixed-integer iterative dynamic programming incorporating a special truncation procedure to handle integer restrictions on stage lengths is proposed. First, the OCP with variable time stage lengths is transformed into a fixed time stage problem by introducing a normalised time variable. Then, the optimisation procedure is carried out at each stage and preceded backwards in a systematic way. Finally, the numerical results of an example illustrate the effectiveness of the proposed method.
机译:聚合物驱是提高采油率的最重要技术之一。本文建立了一种用于注射策略的混合整数分布参数系统(DPS)最优控制模型,该模型涉及性能指标(最大利润),控制方程(聚合物驱的流体流动方程)和一些不等式。约束条件,例如聚合物浓度和注入量限制。控制变量是体积大小,每个段塞的注入浓度和最终溢流时间。对于恒定的注入速率,段塞尺寸由整数时间段长度确定,因此将整数变量引入DPS。为了解决此DPS的最优控制问题(OCP),提出了一种混合整数迭代动态规划,该规划结合了特殊的截断过程来处理对舞台长度的整数限制。首先,通过引入归一化的时间变量,将具有可变时间段长度的OCP转换为固定时间段问题。然后,在每个阶段执行优化过程,然后以系统的方式向后进行优化。最后,通过算例验证了所提方法的有效性。

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