Insurance Value of Intelligent Well Technology against Reservoir Uncertainty

摘要

Significant challenges remain in the development of optimized control techniques for intelligent wells, particularly with respect to properly incorporating the impact of reservoir uncertainty. Most optimization methods are model-based and are effective only if the model can be used to predict future reservoir behavior with no uncertainty. Recently developed schemes, which update models with data acquired during the optimization process, are computationally very expensive. We suggest that simple reactive control techniques, triggered by permanently installed downhole sensors, can enhance production and mitigate reservoir uncertainty across a range of production scenarios. We assess the implementation of an intelligent horizontal well in a thin oil rim reservoir in the presence of reservoir uncertainty, and evaluate the benefit of using two completions in conjunction with surface and downhole monitoring. Three control strategies are tested. The first is a simple, passive approach using a fixed control device to balance inflow along the well, sized prior to installation. The second and third control strategies are reactive, employing intelligent completions that can be controlled from the surface. The second strategy opens or closes the completions according to well water cut and flow rate and individual downhole rate and phase measurements obtained from a surface multiphase flowmeter and alternating zonal well tests. The third strategy proportionally chokes the completions as increased completion water cut is measured using downhole multiphase flowmeters. A cost-benefit analysis demonstrates that reactive control strategies always yield a neutral or positive return, whereas a passive, model-based strategy can yield negative returns if the reservoir behavior is poorly understood. While reactive control strategies enhance production and mitigate reservoir uncertainty, they may not deliver the optimum possible solution. Proactive control techniques, which additionally incorporate data from downhole reservoir-imaging sensors, may yield near- optimal gains.