Passive inflow control devices (ICDs) can redistribute the fluid influx (rate per unit length) into the well completion by causing additional pressure drops between the sand face and tubing. The aim of ICDs is to provide an increase in oil recovery and/or net present value (NPV) by reducing unwanted fluids. Software tools exist to model all aspects of ICD, reservoir, well and surface facilities. The challenge addressed by this paper is to provide an understanding of the implications for optimal ICD design over the life of the field, by integrating these models in a consistent manner.

This paper investigates different aspects of detailed ICD design on horizontal producers, using a wellcentric reservoir model. The ICD designs from the well-centric models were then applied to a full field reservoir model and integrated studies were then completed. This was achieved by linking several existing software to study the interaction between the ICD design, full field reservoir, well and surface network. Various aspects of the integration of these models were simulated including: artificial lift, water injection strategy and surface network.

Predictably, well-centric simulations showed that ICD designs are dependent on the objective function that is being maximized. If NPV is to be optimized, designing ICD strength to have higher production from the heel and toe regions of the well may produce better results than attempting to equalize the inflow for the entire well.

Integrated studies showed that artificial lift can be beneficial in combination with ICDs, as the ICDs redistributed the fluid influx into the well, yet the liquid rate reduction due to the additional pressure drop from the ICDs was mitigated. Even when ICDs were shown to be beneficial on standalone reservoir/well models, the design and predicted benefit when a surface network is coupled depends on: how the surface network is operated, surface network constraints and the relative water cut of the well which ICDs are applied to in comparison to the other wells in the field. These results show that ICD design and optimization requires an integrated approach to ensure outcomes that are consistent with the reality of the field.

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