مدل سازي و بهينه سازي عملكرد فراز اوري گاز پيوسته با استفاده از تحليل نودال يكپارچه با نرم افزار PIPESIM شركت شلمبرژه

Abstract Declining reservoir pressure in mature oil fields necessitates reliable artificial lift methods, with Continuous Gas Lift CGL widely adopted globally due to its exceptional operational flexibility, mechanical simplicity, an‎d ability to han‎dle abrasive fluids, high water cuts, an‎d highly deviated wellbores. This research proposes an integrated methodology utilizing Nodal Analysis System Analysis within Schlumberger PIPESIM to meticulously model an‎d optimize CGL well performance. The process centers on constructing a robust, high-fidelity wellbore model through rigorous history matching of historical production data. This involves critical steps like calibrating Pressure- Volume-Temperature PVT fluid properties an‎d selec‎ting the most appropriate Vertical Lift Performance VLP correlations against measured downhole an‎d surface pressures. The critical objective is minimizing the discrepancy between the simulated an‎d actual flowing conditions, thereby creating a reliable digital twin of the well. The resulting validated model enables comprehensive sensitivity analyses to determine the optimal gas injection rate GLIR that maximizes liquid production (QL) under practical constraints such as available lift gas volume an‎d maximum casing pressure limits. Analysis of the Gas Lift Performance Curve GLPC reveals the technical optimum GLIR an‎d corresponding maximum liquid rate, with sensitivity studies quantifying the impacts of varying parameters such as Water Cut WC an‎d Wellhead Pressure (Pwh) on well performance. Ultimately, the expected outcomes include a verified, predictive tool capable of forecasting future well performance an‎d providing data-driven operating 103 guidelines to significantly enhance well productivity, maximize ultimate reserves recovery, an‎d improve the overall economic efficiency of the gas lift system by reducing wasted compression power.

محسن محمدي

حميدرضا شاه وردي , روح اله هاشمي