Water Control Solutions Combining Intelligent Algorithm and Reservoir Simulation Methods for Horizontal Wells in Bottom Water Reservoirs

Abstract Currently, a substantial majority of bottom water reservoirs are in a developmental phase characterized by both high extraction rates and extensive water encroachment, commonly referred to as the "dual high" stage. This stage presents significant challenges for residual oil recovery, primarily due to severe water flooding issues encountered in horizontal wells. To address these challenges, this study investigates the fundamental mechanical water production dynamics within horizontal wells. Through the implementation of multi-segment well models, the study simulates the application of ICDs, AICDs, and C-AICDs in reservoirs. It evaluates the influence of permeability ratio, oil viscosity, well length, and liquid production rate on cumulative oil production and oil recovery enhancement achieved by deploying water control tools. The research identifies the primary factors controlling the incremental oil recovery effect of these tools. Furthermore, the Elite Opposition-based Learning-Simulated Annealing-Particle Swarm Optimization (EO-SAPSO) algorithm is introduced to optimize the placement of annular packers. Additionally, the Elite Opposition-based Learning-Multi-Objective Particle Swarm Optimization (EO-MOPSO) algorithm is applied to optimize the placement and operational parameters of mechanical water control devices. A reservoir numerical simulation-based optimization approach is employed to achieve parameter optimization for mechanical water control in bottom water reservoirs. Moreover, the trajectory irregularities in horizontal wells can be corrected using a rotation adjustment method, which improves the accuracy of water control simulations. An automatic history matching method is developed to iteratively calibrate production dynamics and liquid production profiles, achieving precise matching results and enhancing the reliability of subsequent optimization strategies. Field application results demonstrate that cumulative oil production increased 5.25× 103 m3 for the initial timing and 3.44 × 103 m3 for the high water cut timing by the C-AICD water control tool compared to scenarios without water control interventions. These results indicate that the proposed water control technology effectively improves oil recovery in bottom-water reservoirs.