首页> 外文会议>Abu Dhabi International Petroleum Exhibition Conference >A Subsurface Sectorization Workflow for Assessing Reservoir Properties, Screening for Remaining Hydrocarbon Volumes and Ranking of EOR Methods to Improve the Reservoir Ultimate Recovery Factor
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A Subsurface Sectorization Workflow for Assessing Reservoir Properties, Screening for Remaining Hydrocarbon Volumes and Ranking of EOR Methods to Improve the Reservoir Ultimate Recovery Factor

机译:用于评估储层性质的地下扇形工作流程,筛选剩余烃类和EOR方法的排序,以改善储层终极回收因子

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Enhanced Oil Recovery (EOR) strategies are becoming increasingly common in the Middle East, used primarily for optimizing mature fields. The final location, selected for any EOR scheme, is often critical to its ultimate success and developing new methods to investigate the most optimal EOR locations can add significant value in optimizing recovery from mature fields. One approach for a given field, is to subdivide 3D Geo-cellular model into different sectors and perform a statistical analysis of the 3D model's properties (porosity, permeability, saturations, etc.) in each individual sector. This task is usually performed manually and can be resource intensive and time-consuming. In particular, in the case of large mature fields in the Middle East, the scale and data volume involved often makes the workflow impractical to implement. Advanced ‘automation methods’, developed to rapidly generate EOR sectors and perform the statistical analysis of 3D model properties are therefore necessary. This work presents a new workflow implemented for extracting and analyzing model properties at a scale relevant for EOR planning in large scale Middle East Fields.
机译:增强的储油(EOR)策略在中东越来越普遍,主要用于优化成熟领域。为任何EOR方案选择的最终位置通常对其最终成功和开发研究来调查最佳EOR位置的新方法是至关重要的,这可以在优化成熟字段中的恢复方面增加显着的值。给定领域的一种方法是将3D地理蜂窝模型细分为不同的扇区,并且在每个单独的扇区中对3D模型的性质(孔隙度,渗透率,饱和等)进行统计分析。此任务通常是手动执行的,可以是资源密集和耗时的。特别地,在中东的大型成熟场的情况下,涉及的规模和数据量通常使工作流程不切实际地实现。因此,为快速生成EOR扇区开发的高级“自动化方法”因此需要对3D模型属性进行统计分析。这项工作提出了一种用于在大型中东领域的EOR规划中提取和分析模型属性的新工作流程。

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