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Polymer Flooding Simulation Modeling Feasibility Study: Understanding Key Aspects and Design Optimization

机译:聚合物洪水仿真建模可行性研究:了解关键方面和设计优化

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The paper discusses the feasibility study approach of polymer flooding enhanced oil recovery. This work is focused on understanding and quantifying key aspects of polymer flooding and design parameter optimization case. A synthetic reservoir simulation model was employed for the study. The first stage is to identify and understand key factors that have most significant impact to polymer flooding response. There are eight parameters that are considered in the analysis, such as polymer concentration, polymer thermal degradation, polymer injection duration, and polymer-rock properties (adsorption, residual resistance factor, etc.). The impact of each parameter to oil recovery response was sensitized with its low, mid, and high values. The difference of high to low oil recovery output for all parameters was ranked to determine their significance levels. The top three parameters obtained from the sensitivity analysis are polymer injection duration, thermal degradation, and polymer concentration. Sensitivity cases of polymer injectivity and thermal degradation effects were covered in this work. The second stage is to determine optimum design parameters of polymer flooding. The most significant parameters from the sensitivity analysis results were considered for further optimization. Three parameters that were selected for design optimization include polymer injection duration, polymer concentration, and well spacing. An optimization workflow with simplex algorithm is linked with a reservoir simulator to generate optimization cases by varying values of optimized parameters. The optimization iteration stops when the maximum value of the objective function, which is the net revenue, is reached. The optimization cycle was done for rock permeability of 500 md and 1000 md. For a low rock permeability reservoir, the well spacing should be short and a lower polymer concentration is sufficient to provide a good response, in addition to avoiding potential injectivity problem. There should be minimum injectivity problem for reservoir with permeability above 1000 md. It is very important to apply polymer thermal degradation in the simulation model to avoid an optimistic performance prediction. The sensitivity analysis results provide a good understanding on the significance impact of parameters controlling polymer injection response and potential challenges. The optimization approach used in the study aids in investigating many optimization scenario within a short period of time.
机译:本文讨论了聚合物泛滥增强的采油的可行性研究方法。这项工作侧重于理解和量化聚合物洪水和设计参数优化案的关键方面。用于研究的合成储层模拟模型。第一阶段是识别和理解对聚合物泛滥反应产生最大影响的关键因素。在分析中存在八个参数,例如聚合物浓度,聚合物热降解,聚合物注射持续时间和聚合物 - 岩石性质(吸附,残留抗性因子等)。每个参数对恢复响应的影响敏感,低,中,高值。所有参数的高到低油回收输出的差异被评为确定其意义水平。从敏感性分析获得的前三个参数是聚合物注射持续时间,热降解和聚合物浓度。在这项工作中涵盖了聚合物注射率和热降解效应的敏感性案例。第二阶段是确定聚合物洪水的最佳设计参数。来自敏感性分析结果的最重要参数被认为进一步优化。选择优化选择的三个参数包括聚合物注射持续时间,聚合物浓度和间隔孔。具有Simplex算法的优化工作流程与储库模拟器相关联,以通过不同的优化参数值生成优化案例。当达到净收入的目标函数的最大值时,优化迭代停止。优化周期是为500 md和1000 md的岩石渗透性进行的。对于低岩石渗透性贮存器,除避免潜在的再射性问题之外,井间距应短而较低的聚合物浓度足以提供良好的反应。储层应有最小的注射性问题,渗透率高于1000 md。在仿真模型中应用聚合物热劣化是非常重要的,以避免乐观的性能预测。灵敏度分析结果对控制聚合物注射响应的参数的意义影响提供了良好的理解和潜在的挑战。研究中使用的优化方法辅助在短时间内调查许多优化方案。

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