Autonomous inflow control devices (AICDs) have recently been introduced in the petroleum industry to restrict the production of unwanted fluids, namely water and gas, much more effectively than conventional inflow control devices (ICDs). As with ICDs, AICDs are installed downhole along the completion string to first delay water and gas coning and then restrict water and gas influx, without well intervention, if or when coning occurs. Unlike ICDs, AICDs selectively choke back water and gas significantly more than oil.

A novel cyclonic AICD was recently developed using computational fluid dynamics (CFD)–driven design optimization. The cyclonic AICD's unique internal geometry increases the flow resistance to unwanted fluids—based on how their viscosities and densities differ from those of oil—as initially predicted using CFD and subsequently validated by extensive, carefully controlled single- and two-phase flow tests. The resulting excellent match obtained between CFD and such laboratory tests yielded accurate mathematical models for predicting flow performance over a broad range of flow rates and oil, water, and gas properties.

The flow performance models were then incorporated into a state-of-the-art dynamic reservoir simulator with multisegmented wellbore capability to compare the production performance over time for the same well when completed with no ICDs, conventional ICDs, and cyclonic AICDs. A synthetic but realistic three- dimensional (3D) reservoir model was used that allowed oil, gas, and water production. Multiple sensitivity runs were initially performed to optimize the number of compartments using packers for annular isolation and the number of ICDs per compartment. Once these parameters were optimized, only the ICD type was varied for performance comparison.

The results of this systematic, multistep process, as presented herein, demonstrate that the cyclonic AICD adds significant value to the improvement of oil production by controlling unwanted fluids, such as water and gas, and by preserving the reservoir energy.