Capacitance Resistance Clustered Model for Mature Peripheral Waterflood Performance Prediction & Optimization
نویسندگان
چکیده
Optimizing water injection rate distribution in waterflooding operations is a vital reservoir management aspect since capacities may be constrained due to geographic location and facility limitations. Traditionally, numerical grid-based simulation used for waterflood performance evaluation prediction. However, the approach can time-consuming expensive with vast amount of wells data mature fields.
 Capacitance Resistance Model (CRM) has been widely recently as data-driven physics-based model rapid projects. Even though CRM smaller computation load than simulation, large fields containing hundreds still pose challenge calibration optimization. In this study, we propose an alternative solution improve application large-scale waterfloods that particularly suitable peripheral configuration. Our attempts reduce problem size by employing clustering algorithm automatically group producer irregular pattern. The selection well groups considers position high throughput (key well). We validate our through field case South Sumatra. Based on obtained up 18.2 times increase speed parameter reduction, excellent history match accuracy.
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ژورنال
عنوان ژورنال: Journal of Earth Energy Engineering
سال: 2022
ISSN: ['2301-8097', '2540-9352']
DOI: https://doi.org/10.25299/jeee.2022.10633