Maximum Revenue for Oilwells With Optimized Downhole Water Drainage

Downhole Water Sink (DWS) technology is an alternative to conventional limited-entry completions to control water production in bottomwater drive reservoirs. DWS wells comprise two completions: 1) the bottom completion is a water sink that suppresses water cone formation; and, 2) the top completion produces oil with as little water as possible. Essentially, optimization manipulates the two rates to maximize oil productivity and produce oil-free water from the bottom completion. In this paper, stepwise and global optimization methods are interfaced with a commercial reservoir simulator to optimize top and bottom rate schedules for DWS wells. The stepwise optimization uses a polytope algorithm to maximize oil productivity and incremental recovery in discrete, forward-marching time steps. The global optimization employs a hybrid polytope-conjugate gradient algorithm to simultaneously adjust top and bottom production rates for all time steps, thereby maximizing net revenue over the well life. Global optimization uses a stochastic search to find the best solutions, but demands considerable computation. Stepwise optimization performs nearly as well as global optimization for rate scheduling, final recovery, well life and cumulative water production-and the stepwise method is much faster than the global method. The optimization results suggest that economic performance is improved by maximizing production rate via maintaining low water saturations around the oil completion using water sink completions. This proactive strategy preempts water production and attendant productivity decline, in contrast to strategies that attempt to mitigate problems after water has broken through to the oil completion. Plausible ranges of reservoir properties are modelled and optimal strategies are computed and compared.