Maximum Revenue for Oilwells With Optimized Downhole Water Drainage

Abstract

Abstract 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:the bottom completion is a water sink that suppresses water cone formation; and,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. Introduction Downhole water sink (DWS) wells have proven to be effective in controlling water inflow and improving oil productivity by draining water below water oil contact(1–3). DWS wells comprise two completions:the bottom completion is a water sink that suppresses water cone formation; and,the top completion produces oil with as little water as possible (see Figure 1). Arslan et al.(2) addressed the well productivity, improved the understanding of DWS well operation and identified the optimal conditions using a new nodal analysis approach addressing the optimal production and water drainage rates. However, these analyses use stabilized flow simulations where the average reservoir pressure is not allowed to change; fluid in place volumes and average reservoir pressure are maintained by re-injection. This enabled a comparison of reservoir conditions for potential production improvement, but it does not capture the dynamics of water production and coning. Arslan et al.(3) later provided a successive nodal analysis approach using a numerical reservoir simulation to model a DWS well's inflow performance, while preserving the water coning conditions from earlier production stages. This approach required the simulations of infeasible well production and water drainage rates to find the feasible operating conditions at a given stage of depletion that does not address global optimal strategy. An operator may select a candidate reservoir and evaluate a DWS installation. The operator of a DWS well should manipulate the production and water drainage rates to maximize oil productivity and produce oil-free water from the bottom completion.