Strategic Modelling Approach for Optimizing and Troubleshooting Gas Lifted Wells: Monitoring, Modelling, Problems Identification and Solutions Recommendations

Offshore gas-lifted wells are challenging due to the numerous factors affecting performance, starting from the surface gas compression facility to reservoir performance. Mature oil fields add more challenges due to many flow assurance and mechanical problems. Real-time well monitoring is a must for early problem identification. Also, performance modeling is powerful and helpful for identifying and rectifying problems early. The work here emphasizes an optimization strategy for offshore gas-lifted wells. This paper introduces cases of offshore problematic gas-lifted wells and their full optimization and problems solving strategy to be utilized as an integrated approach for solving the problems of similar problematic gas-lifted wells in any field. The recommended strategy depends on studying problematic gas-lifting wells covering some commonly encountered problems. The recommended remedial actions for the selected problematic cases in this intensive study resulted in precious oil gains, cost savings, and gas lift usage optimization. The solution combines surveillance, multiphase simulation, data analytics, and operations. This paper discusses three major problems and the strategy to solve them: the first is wells with erroneous surface gas measurement and excessive gas injection; the second is unstable gas-lifted wells, and the third is optimizing low reservoir deliverability gas-lifted wells. In addition, other individual optimization cases, including integrated full-field cases, are introduced for the recommended strategy's completeness. This comprehensive study finds that the optimum approach for rectifying most gas-lifted wells problems must start with real-time monitoring, then modeling the case, and end by recommending possible solution scenarios and their impact on optimizing well performance. This study brings the significance of surveillance and dynamic simulations in the overall production cycle: planning to operations. Further, dynamic simulations also help arrive at operators’ guidelines on avoiding failed start-ups and ensuring stable operation. Finally, the power of integration between different disciplines is shown by incorporating several subsurface and surface information in the uncertainty study.