Proceedings Title : Proc. Indon. Petrol. Assoc., 48th Ann. Conv., 2024
Achieving national production targets presents challenges, especially in mature fields like PTN Field, with over 50 years of production and annual declines. A key solution involves an increase in drilling activities, requiring an efficient process for maturing new well candidates. This paper responds to these challenges by introducing a transformative innovation: Integrated Precision Automated Drilling Infill (i-PADI). i-PADI aims to redefine mature field development through digitalization and automation for infill well placement strategies, representing a groundbreaking leap toward overcoming production challenges.
i-PADI stands out as a comprehensive solution designed for the efficient generation of numerous infill well candidates and streamlining the maturation process. The workflow integrates digitalization techniques, including subsurface data integration, Voronoi gridding mapping for automated well placement, and production forecast automation using closeology methods, and prioritization scoring driven by artificial intelligence fuzzy logic.
The approach to identifying potential infill well locations employ Voronoi gridding mapping, integrating minimum distance rules to ensure optimal infill spacing. Automated procedures assess remaining opportunities using digitalized hydrocarbon pore thickness (HPT) data and forecast potential production through closeology methods. These essential parameters, covering benchmarking existing well production, historical workover well service gains, and recent well drilling, form the foundation for prioritization through the adept application of fuzzy logic.
The successful integration and application of i-PADI establish a highly effective workflow for precisely identifying infill well opportunities, reduce ~80% of the maturation process cycle time, and supporting doubling field production with an additional ~6,600 BOPD (barrels of oil per day). Adopting i-PADI, which utilizes advanced data analytics and artificial intelligence, automated and systematic production enhancement opportunities have been made possible, giving a positive impact on work processes that give engineers more time to focus on strategic and value-added activities, increasing workforce satisfaction and productivity.
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