Author/Authors :
Buhamad ، Ahmad Faculty of Chemical, Petroleum and Gas Engineering - Iran University of Science and Technology , Assareh ، Mehdi Faculty of Chemical, Petroleum and Gas Engineering - Iran University of Science and Technology
Abstract :
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 smart elements. The central focus in 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 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. 2D and 3D reservoir models are used as case studies to evaluate these approaches. The study shows a considerable increase in NPV with respect to 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 with reference to 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.
Keywords :
Smart Well , Production Scheduling , Water , flooding , Multi , layer Reservoirs , Optimization