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An Improved Approach For Ensemble Based Production Optimization: Application To A Field Case

机译:基于集合的生产优化的改进方法:应用于现场案例

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One of the primary goals of the reservoir management is to enable decisions that maximize recovery from the reservoir. With recent developments in monitoring and control, the opportunity to optimize reservoir production through frequent adjustment of well controls has substantially increased. We recently proposed and demonstrated an improved ensemble-based production optimization method using Conjugate Gradient technique (CGEnOpt) on a synthetic reservoir model. The proposed method results in faster convergence as a result of using the conjugate gradient directions instead of steepest ascent search directions. The net present value (NPV) of a single reservoir is optimized by obtaining the gradient of the NPV from an ensemble of control variables. In this paper, the benefits and effectiveness of the proposed method is demonstrated on a real field example located off-shore west Africa with 15 producers and 11 water injectors. The production and injection rates are used as control variables to maximize NPV of the reservoir. The results indicate that the control settings from the proposed method result in a significantly higher NPV of the reservoir as compared to the reference case. The number of iterations needed for the proposed method is significantly reduced compared to the standard ensemble-based optimization. The proposed method is able to allocate the production and injection rates effectively which results in a substantial decrease in the amount of water produced. In the literature, a wide variety of approaches were developed and implemented for optimizing the reservoir performance by adjusting operational controls. The proposed method is completely adjoint-free and is independent of the reservoir simulator used for the prediction simulation run which makes it easy to implement. It can be used with any existing simulator with minimal code development.
机译:水库管理的主要目标之一是启用最大化水库恢复的决定。随着最近的监测和控制的发展,通过频繁调整井控制来优化水库生产的机会大幅增加。我们最近提出并展示了一种使用共轭梯度技术(CGenopt)在合成储层模型上改进了基于基于的基于组合的生产优化方法。所提出的方法由于使用共轭梯度方向而不是最陡峭的上升搜索方向而导致更快的会聚。通过从控制变量的集合获得NPV的梯度来优化单个储存器的净现值(NPV)。在本文中,拟议方法的益处和有效性在距离岸边西非有15个生产商和11个水注射器的真实领域示例上进行了证明。生产和注射率用作控制变量,以最大化储层的NPV。结果表明,与参考案例相比,所提出的方法的控制设置导致储层的显着高于NPV。与基于标准的合并的优化相比,所提出的方法所需的迭代次数显着减少。所提出的方法能够有效地分配生产和注射率,从而导致产生的水量的显着降低。在文献中,通过调整操作控制来开发和实施各种方法,用于优化储层性能。所提出的方法完全伴随着,独立于用于预测仿真运行的储层模拟器,这使得易于实现。它可以与任何具有最小代码开发的现有模拟器一起使用。

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