Autonomous flow control device modelling and completion optimisation

The functions of the various wellbore completion components and their impact on the given well performance should be fully understood to achieve the full potential of advanced wells completions (AWCs). Inflow control technology has been a success when installed in many fields. Field trials of the more recently developed Autonomous Flow Control Completions (AFCC) have shown their potential to further improve well performance. However, such (autonomous) discrimination and control of the different fluid phases, presents new modelling challenges that require extension of today's wellbore/reservoir models and workflows for optimizing the completion design. The modelling challenges associated with this new technology requires more research to correctly quantify their added-value and guide future design improvements in AFCC technology. This paper discusses how the currently available modelling tools can best designed when only singlephase flow performance data is available. Methods and workflows to improve the modelling accuracy, as well as, to understand the performance of an AFCC in a horizontal well in comparison with passive inflow control technology are presented. Novel methods to visualize and optimize the AFCC are presented and used to optimize the equipment design and identify the technology's added-value. Finally, this paper presents a modelling workflow for reservoir and well engineering studies by providing optimal AFCC selection guidelines together with a brief summary of an extension of the work reported here to multi-phase flow in typical AFCCs. Incorrect modelling of the devices Multi-Phase Flow Performance was found to effect the economic evaluation of this promising technology; forming an extra barrier to its early adoption.