Water-Control Optimization Design for Bottom-Water Reservoirs Based on a Hybrid Model

Horizontal wells in bottom-water reservoirs are highly susceptible to water coning during production. Consequently, accurately evaluating the water-control performance of inflow control valves (ICVs) is critical for optimizing completion strategies. Conventional semi-analytical models often struggle to capture the transient dynamics of multiphase flow, while standard numerical reservoir simulators fail to explicitly resolve the complex geometries of completion hardware. To address these limitations, this study proposes a multiscale composite modeling framework tailored for bottom-water reservoirs. At the near-well scale, a semi-analytical model is developed to characterize wellbore hydraulics and the pressure drops induced by ICV completions. At the reservoir scale, a numerical model is employed to simulate multiphase fluid transport, with the two scales coupled via cross-scale pressure field mapping. Validation against NETool software under steady-state conditions confirms the physical consistency of the near-well model in determining zonal flow allocation. Comparisons with conventional equivalent well numerical models demonstrate that the proposed composite model offers superior resolution of ICV-induced flow redistribution, yielding distinct production performance profiles. Furthermore, the integration of a Particle Swarm Optimization (PSO) algorithm enables the dynamic optimization of ICV settings. Results indicate that this composite framework provides a robust theoretical and computational basis for designing and evaluating intelligent water-control completions in bottom-water reservoirs.