Reservoir Characterization and Performance Prediction in Waterflooded Reservoir using Capacitance-Resistance Model - Ray Yuda Suyatna, Made
Characterizing and predicting reservoir performance need to be done in order to improve reservoir management decision. Time consuming and data uncertainty make the numerical simulators less preferable for a quick reservoir evaluation. Capacitance-resistance model (CRM) proved to be a quick and reliable tool to evaluate waterflood performance using just production and injection historical data to perform history matching. The CRM characterize reservoir by quantifying the interwell connectivity and response delay that constitute the CRM unknown parameters. In this study, the CRM was used to characterize and predict waterflooded reservoir performance. The CRM was applied to four synthetic reservoir models with different complexities to investigate the CRM responses toward the reservoir heterogeneity. The result showed that the CRM was able to infer the reservoir heterogeneity and match the synthetic historical data within more than 0.9 R-squared. The calibrated CRM model then coupled with fractional flow models to match the oil production performance. Once the oil production matched, the model then used to predict the production performance and maximize the amount of oil produced by reallocating water injection rates. To validate the CRM prediction, the results were tested against numerical simulation results. The result showed that the CRM was able to perform performance prediction and maximize the amount of oil produced by reallocating the injection rates.