Intelligent well systems are gradually gaining ground in the development of hydrocarbon assets. One of the reasons is the value added by the technology in maximizing production relative to conventional systems because of its flexibility in reacting to detrimental production conditions.

The maximization benefit is closely tied to a simple, consistent, robust and standardized optimization process. This paper describes a network optimization and control methodology that can be implemented in either a zonal compensation or distribution mode. In a compensation mode, the technique maximizes total well throughput of a specified fluid stream (oil or gas) in a multi-zone commingled intelligent well system by rewarding favorable zones and penalizing unfavorable ones. In zonal distribution mode, it is used to allocate rates to contributing zones based on predefined distribution factors.

The approach is similar to those used in resource allocation and dynamic programming. Unlike the gradient-based method, this approach does not require calculations of differentials. Instead, it uses historical zonal production, pressure/temperature data, and installed down-hole component properties to recommend new operating conditions for each zonal down-hole interval control valve (ICV). The analysis involves characterization of the zonal ICVs within the boundaries of the contributing reservoirs and specifying dynamic or static constraints for the well of interest. This analysis is then combined with existing zonal and total well data to predict an optimized operating condition for the zonal ICVs. The method can be used both in a reactive or proactive mode. It can also be used in a discrete or continuous flow process. The paper discusses the optimization and control process and provides two field cases.

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