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dc.contributor.authorSingarimbun, Hanifa Ramadani
dc.date.accessioned2025-10-10T09:45:56Z
dc.date.available2025-10-10T09:45:56Z
dc.date.issued2024-11-21
dc.identifier.citationAPAen_US
dc.identifier.urihttps://library.universitaspertamina.ac.id//xmlui/handle/123456789/15090
dc.description.abstractThe project "Well Performance Modelling for Optimum Tubing Size and Completion Design at X Field" aims to enhance well productivity and operational efficiency through advanced performance modeling techniques. By integrating detailed field data and using state-of-the-art modeling tools, the study focuses on optimizing tubing and completion designs to maximize production and ensure the well's long-term viability. The primary objective is to develop accurate well performance models that simulate flow dynamics, pressure profiles, and other subsurface factors, enabling the design of customized tubing and completion systems. Using PROSPER software, the project combines geological, reservoir, and operational data to create comprehensive models that predict well behavior under various scenarios. Sensitivity analyses assess the impact of different tubing sizes, completion techniques, and operational conditions, identifying the most efficient and cost-effective configurations. The horizontal well design with 3-½" tubing emerged as the optimal solution, offering improved reservoir contact, higher production rates, and reliable artificial lift performance. Key factors such as pressure drops, friction losses, water cut, and gas-to-oil ratios are analyzed to understand their impact on well performance. The study emphasizes the importance of continuous monitoring and adaptive management throughout the well's lifecycle, providing insights into minimizing risks like wellbore instability and gas lift inefficiencies. By optimizing well design and operational strategies, the project enhances production efficiency, reduces operational risks, and supports better economic returns at X Field. This approach highlights the value of advanced modeling and data-driven decision-making in optimizing well performance and reservoir management.en_US
dc.description.sponsorshipPetronas Sponsoren_US
dc.language.isoen_USen_US
dc.publisherHanifa Ramadani Singarimbunen_US
dc.subjectWell performance modelling, tubing size optimization, completion design, PROSPER software, horizontal wells, production efficiency, artificial lift performance, reservoir management, sensitivity analysis, flow dynamicsen_US
dc.titleCase Study: Well Performance Modelling for Optimum Tubing Size and Completion Design at X Fielden_US
dc.typeTechnical Reporten_US


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