Horizontal wells have been used to maximize recovery from thin pay reservoirs but this does not eliminate early water/gas breakthrough problem due to the presence of a non-uniform inflow along the completion. This uneven inflow is as a result of non-uniform pressure losses along the completion and instance reservoir heterogeneities. The non-uniform pressure losses causes higher flow rate and early break through from the heel sections than from the toe and the occasional presence of permeability variations creates zonal variations in water and/or gas encroachment. Recent research efforts have led to the successful application of smart completions (Inflow Control Devices [ICDs] / Inflow Control Valves [ICVs]) to suppress the non-uniform inflow. The selection of optimal ICD configurations for such smart wells is normally obtained from a trial and error simulation with different configurations. A more recent study proposed a model for calculating optimal ICD strengths without flow simulations. The earlier solution with trial and error simulation is time consuming and the later solution with no flow simulation will not capture the influence of reservoir heterogeneities. This paper presents the application of a new approach to ICD optimization in a horizontal well located offshore Niger Delta. The approach involves the development of a diagnostic algorithm which utilize results from a basecase simulation with an openhole horizontal well in order to determine the optimal ICD configuration for the well. The configuration parameters specified as optimization control variables in the algorithm include ICD strengths, the total number of ICDs in the wellbore and the valves density per ICD's compartment. A comparison of recoveries is made between an open-hole completion case, identical ICDs’ configurations case and the optimized ICDs case. The case study is carried out with autonomous inflow control devices (AICDs) but the optimization's control variables are independent of the choice of ICD.
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