Performance and Modelling of a Density-Based Autonomous Inflow Control Device

Abstract

Autonomous inflow control devices (AICDs) are used to improve reservoir influx and restrict unwanted fluids for higher oil recovery. A new AICD has been developed to restrict water based on the density of downhole fluids. This is particularly useful in reservoirs where the oil and water have similar viscosities. This paper presents full scale flow performance results at reservoir conditions and modelling to predict the impact of this Density-AICD in well completions under various scenarios. The Density-AICD is equipped with a novel Centrifugal Fluid Selector that magnifies subtle differences in buoyant forces and makes it orientation independent. The switching mechanism will autonomously adjust the choke to reduce the flow rate when changing from oil to water. A full-scale flow loop test was completed using a Norwegian oil crude sample and water at downhole conditions. The experiments evaluated the performance of the tool over different pressure differentials with single phase and multiphase fluid mixtures. To explore the impact of this device, a simple conceptual reservoir model was constructed. The flow performance test results demonstrated that the tool produces oil at high flow rates and chokes water effectively. Two different nozzles sizes were tested proving the expected ratios of oil to water. It also confirmed the switching capability of the device to independently open and close based on the density contrast of the fluids. The multiphase testing showed the reversibility of the device and the water cut level necessary to close and open the device across a range of differential pressures. The approximate behavior of this Density-AICD was implemented in an industry standard reservoir simulator. The model used realistic reservoir conditions from a Norwegian sub-sea development. The study shows that the Density-AICD can significantly decrease tail-end water production and further increase oil recovery across most reservoir scenarios. The Density-AICD's self-adjusting feature simplifies and addresses uncertainties in the reservoir to restrict water, enhance oil recovery, optimize reservoir management, reduce water treatment costs at surface and contribute to reduced carbon intensity. This paper publishes new flow performance test data for the Density-AICD using a Norwegian crude oil sample at representative downhole conditions. The conceptual reservoir modelling indicates a possible step-change autonomous inflow control technology that enables more carbon-efficient reservoir management.