A Smart, Adaptive Workflow for Lower Completion Optimisation Integrating Proxy Reservoir Models and Lower Completion

This study presents a smart, adaptive workflow for optimising lower completion designs by integrating proxy reservoir modelling with wellbore flow performance analysis. The workflow is developed to address challenges in heterogeneous reservoirs with complex inflow behaviour and high water cut risks. Stage 1 focuses on a well-centric model to assess baseline inflow performance and identify problem zones, while Stage 2 extends the analysis to a sector model with Local Grid Refinement (LGR) for enhanced resolution and explicit well-reservoir coupling. Different inflow control completion strategies, including passive inflow control valves (ICDs), autonomous inflow control devices (AICDs), autonomous inflow control valves (AICVs), and surface-controlled intelligent completions (ICVs), are evaluated. The results obtained from two case studies highlight that while highly restrictive AICVs are effective at reducing water production, they may limit oil recovery compared to less restrictive completions. ICVs demonstrate superior long-term performance and flexibility, yielding additional cumulative oil recovery and enabling dynamic water cut management.