Inflow Control Devices Placement: A Computational Fluid Dynamics Approach

Nowadays, it is common to use horizontal wells to improve the oil production rate. The production rate varies along the horizontal well because of either frictional pressure losses (the heel-toe effect) or reservoir heterogeneity. Such a flux variability in zones close to the bottomwater and gas cap leads to water and gas breakthroughs. To mitigate water (or gas) coning, inflow control devices (ICDs) have become a standard practice to control instability and improve uniformity in the inflow profile. These devices help delay the water (or gas) breakthroughs by exerting a greater restriction on high water/oil ratio (or gas/oil ratio) zones. In the design and analysis of ICDs, the only sensible method is to model these tools using the numerical simulation that couples the well and the reservoir. Reservoir and production engineers formulate the ICD characteristics using expensive and time-consuming flow loop testing. In some scenarios, fluid flow simulations using computational fluid dynamics (CFD) are used to compare the results with the flow loop. However, owing to convergency issues in CFD and the unavailability of an established framework, the CFD results are not used to formulate the ICDs in the reservoir models. Instead, different types of empirical correlations are used to describe the ICDs, which require many empirical factors, causing inconsistencies in calculations. In this study, we first use CFD to characterize an orifice-based ICD in terms of the Reynolds number. Then, the results are formulated in a correlation that provides a consistent approach from CFD to well/reservoir modeling. Using such a framework, operators can ensure their prototypes are suitable for any specific problem by altering the geometry and simulating several scenarios from CFD to well/reservoir model.

Automated summary

The use of horizontal wells to improve oil production rates has become common practice. Inflow control devices (ICDs) are now widely used to mitigate water (or gas) coning. By using numerical simulations and formulating results into correlations, operators can ensure prototypes are suitable for specific problems.