There is a growing interest in downhole flow control devices (FCD) as they can be used to counter the effects of reservoir heterogeneity and improve hydrocarbon recovery. The variety of FCD types, sizes, and specifications makes it challenging to select the right device, providing an optimal investment return. Reservoir engineers play an essential role in identifying and evaluating the possible options based on numerical simulation models. This paper utilizes a transient numerical optimizer, designed for FCD with active controls, as a generic tool for lower completion optimization, including passive and autonomous FCD.
The workflow consists of five steps. The first step is to determine a practical number of completion zones in a well, given the reservoir heterogeneity and completion string considerations. The second step is to explore the potential gains of downhole control without accounting for device-specific limitations. Here, we integrate a local optimization method to run several simulations with reactive and proactive strategies. In the third step, we contrast the local optimization simulations results to determine the suitable family of FCD: passive, autonomous, or active. In step four, we ensure the selected FCD family is correctly modelled in reservoir simulation, particularly for autonomous devices, based on a recently published method to calculate equipment-specific flow coefficients. Finally, optimization runs are performed using the selected FCD family and specific coefficients.
The workflow is demonstrated on a synthetic carbonate sector model with a ~2,000-m horizontal well. It can be shown that analyses of the local optimization results provide quick guidelines to screen and select suitable lower completion equipment for the well and reservoir. Furthermore, the local optimization results can be used to design the selected lower completion string. The suggested workflow is the first of its kind in that it caters to all FCD families. The workflow uses an efficient local optimization method in a next-generation reservoir simulator. The efficiency gains from using the optimizer allows the decision-making time required for FCD evaluation to be an order of magnitude less than the logging and completion operation timeframe. Hence, the workflow enables efficient real-time design, planning, and optimization of FCD.