Perpustakaan Digital ITB

Waterflooding is widely recognized as one of the most effective and commonly employed methods for enhancing oil recovery in diverse oil fields around the world. It is popularity stems from the efficiency and accessibility in obtaining injection fluids, making it a preferred choice among operators. Effective reservoir management in waterflooding fields requires quick actions to optimize fluid distribution and improve areal and vertical sweep efficiency during the secondary process. Reservoir characterization and simulation are the most important activities in order to evaluate reservoir performance. Currently, reservoir simulation is one of the methods that is commonly used by petroleum engineer. However, complexity in the geological system, limited understanding of interwell connectivity, vertical heterogenity, long time consuming, and lack of injection and production controls lead to lower-than-expected flood performance. This study shows waterflood optimization process using CRM-IP coupled with fractional flow model for onshore oil fields that have 18 active water injection well and 24 active productions well with Python programming language. The Liquid production rate history data and Injection rate history data will be used to find the connectivity and time constant parameters in CRM-IP equation by using SLSQP in Python sci-kit learn library. The fractional flow equation by (Gentil, 2005) is used for predicting the maximize oil production with optimized distribution of water injection rate. The result of this study shows that waterflood optimization model successfully constructed using CRM-IP with only injection rate and production rate history data. The time that is needed to run the optimization model is less than 3 minutes. The cumulative oil production is predicted will increase 20.45% in the next 120 months if the total field injection rate remains the same, but the distribution is optimized. However, if the total field injection rate is increase to 60,000 BWIPD, the cumulative oil production is predicted will increase to 27.3% with the optimized distribution of injection rate. By using CRM-IP technique, waterflood management within this study can be done faster than conventional approaches. Therefore, the decision taken for optimization in this field could be more effective.