Model-Based Scheduling of Smart Injection and Production Wells for Waterflooding in Multi-Layer Reservoirs

Document Type : Research Article


Faculty of Chemical, Petroleum and Gas Engineering, Iran University of Science and Technology, Tehran, I.R. IRAN


Smart wells are unique tools for the management of oil reservoirs under waterflooding to increase the oil flow rate and reduce the associated wastewater production costs. The costs associated with smart completion are considerable. Consequently, the decision for designing and controlling such completion elements can have considerable impacts on project profitability. This work presents an efficient production scheduling for a multi-layer reservoir during water flooding by regulating water movement in the layers to control associated wastewater using intelligent elements. The central focus of this research is to give a production schedule using smart well completions. To achieve this, several segments of the production and injection wells are controlled independently with the schedules provided by a model-based optimization technique. To perform optimization, three methods are used to regulate waterfront and velocity in different layers; the first approach is used to regulate production well according to the saturation distribution in the reservoir without considering NPV. The second approach is the sequential optimization of well controls including flow rates and bottom-hole pressures, to find an optimized NPV. The third approach is to optimize flow rates and bottom-hole pressures for different segments in the production and injection wells, simultaneously, to achieve a maximized NPV using a genetic optimization algorithm. To evaluate these approaches, 2D and 3D reservoir models are used as case studies. The study shows a considerable increase in NPV concerning conventional wells in a fair comparison ground. In the 2D model, 9.89%, 11.75%, and 11.78% additional recoveries are achieved compared to a conventional production well using the first, second, and third optimization approaches, respectively. For the 3D model, 5.87%, 5.99%, and 6.20% were additional recoveries concerning the equivalent conventional production wells, for the first, second, and third approaches, respectively. This additional recovery is due to lower produced associated water and bypassed oil.


Main Subjects

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