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Optimization of petroleum reservoir waterflooding using receding horizon approach

机译:利用后退地平线方法对石油储层的优化

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In this paper, static and dynamic optimization of a reservoir waterflooding process for enhanced oil recovery was studied. The dynamic optimization was achieved using receding horizon (RH) algorithms. Two forms of RH which are moving-end and fixed-end RH were formulated and compared. MATLAB Reservoir Simulator (MRST) from SINTEF was used for reservoir simulation. The objective function to be maximized is net present value (NPV) of the venture while the control variable is water injection rate. Sequential quadratic programming (SQP) was applied for the optimization. It was found out that fixed-end RH gave the highest NPV with improvements of 0.81% and 1.49% over static and moving-end RH strategies respectively.
机译:本文研究了储层加油过程加油回收的静态和动态优化。 使用后退地平线(RH)算法实现了动态优化。 制定并比较了两种形式的RH,其是移动端和固定螺旋RH。 Sintef的Matlab储层模拟器(MRST)用于储层模拟。 最大化的目标函数是风险的净现值(NPV),而控制变量是注水速率。 汇率二次编程(SQP)被应用于优化。 发现固定末端RH分别在静态和移动终端RH策略中提高了最高NPV的最高NPV,改善了0.81%和1.49%。

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