拟空隙替代比拟VRR概念在5点聚合物驱优化中的应用——以Mangala油田为例

Kavish Grover, Jayabrata Kolay, Ritesh Kumar, P. Ghosh, S. Shekhar, Nitesh Agrawal, Joyjit Das
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引用次数: 0

摘要

对于任何典型的水驱或聚合物驱管理,保持最佳的空隙替代比(VRR)是优化油藏性能的最关键。在典型的注水模式中,单个注入器支持附近的许多生产商,因此确定其对特定生产商的贡献是主观的,并且具有固有的不确定性。为了避免分配因素中的这些不确定性,本文提出了一种基于逐模仿真模型的电压补偿方法。历史匹配模拟模型,已划分为5点生产者为中心的模式,形成了本研究的基础。在这些以生产者为中心的5点模式上分析了空隙置换。通过油气孔隙体积(HCPV)、水孔隙体积(WPV)和该区域的产量变化来确定该区域产生的空隙。由此计算出的部门空隙补偿比(或伪VRR)代表了由于注入和生产造成的净变化。优点是它不需要任何数值分配因子,而是基于模拟模型预测的模式内的流体运动。该方法为分析模式性能提供了一种新的方法。除了VRR之外,模式智能采收率和井间通道/循环是任何水驱性能分析的关键参数。提出了一个工作流,根据这些参数对模式进行排序,并将它们分类到问题桶中。每个桶对应的操作已经被提出。这就形成了对每口井和每个模式的性能进行改进的战略基础,从而优化油田性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Application of Pseudo Voidage Replacement Ratio Pseudo VRR Concept to Optimize 5 Spot Polymer Flood: A Mangala Field Case Study
For any typical water flood or polymer flood management, maintaining optimum Voidage Replacement Ratio (VRR) is most crucial for optimizing reservoir performance. In a typical patternflood, a single injector supports many nearby producers, determining its contribution to particular producer is subjective and has inherent uncertainties. To avoid these uncertainties in allocation factor, a novel approach using simulation model based voidage compensation on pattern by pattern basis has been proposed in this paper. History matched simulation model, which has been sectored into 5-spot producer centric patterns, forms the basis of this study. Voidage replacements are analyzed on these producer centric 5-spot patterns. Sectoral voidage created is determined using change in hydrocarbon pore volume (HCPV), water pore volume (WPV) and production from the sector. Sectoral Voidage Compensation Ratio (or Pseudo VRR) thus calculated is representative of the net change due to injection and production. The advantage is that it does not require any numerical allocation factor, rather is based on fluid movements within a pattern as predicted by the simulation model. This method thus provides a new approach to analyze pattern performance. Along with VRR, pattern wise recovery and interwell channeling/cycling are the key parameters for any water flood performance analysis. A workflow has been proposed to rank the patterns based on these parameters and categorizing them into problem buckets. Actions corresponding to each bucket have been proposed. This forms the basis of strategizing improvements in well-by-well and pattern-by-pattern performance for optimizing field performance.
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