| Summary: | Capacitance–resistance models (CRMs) are semi-analytical methods to estimate the production rate of either an individual producer or a group of producers based on historical observed production and injection rates using material balance and signal correlations between injectors and producers. Waterflood performance methods are applied to evaluate the waterflooding performance effect and to forecast the development index on the basis of Buckley–Leverett displacement theory and oil–water permeability curve. In this case study, we propose an approach that combines a capacitance–resistance model (CRM) modified by increasing the influence radius on the constraints and a waterflood performance equation between oil cut and oil accumulative production to improve liquid and oil production prediction ability. By applying the method, we can understand the waterflood performance, inter-well connectivities between injectors and producer, and production rate fluctuation better, in order to re-just the water injection and optimize the producers’ working parameters to maximize gain from the reservoir. The new approach provides an effective way to estimate the conductivities between wells and production rates of a single well or well groups in CRMs. The application results in Kalamkas oilfield show that the estimated data can be in good agreement with the actual observation data with small fitting errors, indicating a good development index forecasting capability.
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