Intelligent (I-) wells equipped with Interval Control Valves (ICVs) add downhole (zonal) control and multiple flow monitoring sensors to the capabilities of Conventional (C-) Wells. They reduce the well count and accelerate the field's production ramp-up by managed, commingled production from multiple reservoir layers (or zones). This early NPV gain during the plateau period is easily lost if optimum flow control management is not practiced. Optimal C- and I- field management and control during this period is a complicated optimization problem using multiple reservoir simulation models generated to address limited knowledge of the reservoir.
This study discusses the application of a state-of-the-art robust optimization framework that addresses the challenging problem of I-field control under reservoir uncertainty to develop an optimum well and zone management strategy. A stochastic gradient estimation method optimizes a utility function to account for the reservoir description uncertainty. This framework enabled identification of the optimum control scenario for a recent, real North Sea field development using a single, high-end workstation.
The field development plan requires drilling 21 C-wells - 14 producers and 7 injectors. Six of these C-producers penetrate two separate reservoirs; presenting the opportunity to replace them with three I-production wells with controlled, commingled production. Reducing the number of wells via a partial I-well field development scenario resulted in an increased, early-time, NPV and accelerated plateau production. Robust, proactive optimization of these wells ensured that the early NPV gain was maintained. It extended the oil production plateau in all reservoir model realizations. The field NPV increased by up to 4.5% when compared to a "no-proactive-production-control" scenario. The larger gains in the field NPV, as a result of robust proactive optimization, were achieved by the less favorable, reservoir simulation realizations - reducing the uncertainty associated with the profitability of the field development.