Automated Development Concept Generation—Digital Transformation of Field Development Planning

Abstract

Abstract Effective field development planning is critical to maximize the value of opportunities. It can be a complex process due to factors like time, resource constraints, and siloed domain applications. To overcome these challenges an effective dataflow orchestration is required between subsurface, well, facility & economics to ensure coherency and auditability. This paper presents the possible digital transformation of field development planning using smart algorithms and automated dataflow orchestration to generate & evaluate numerous optimized development concepts rapidly. Extensive research has resulted in smart algorithms that work back-to-back and can automatically generate field layouts for different development concepts early stage of field development. These algorithms include the blackhole operator for specifying optimal reservoir targets using quality maps, an industry-standard trajectory engine for designing drillable wells, an evolutionary algorithm for placing facilities and the a-star algorithm for laying out the shortest pipeline route while avoiding surface no-go zones. These algorithms now function on a cloud-native digital technology that can automate the evaluation of field development plans by orchestrating data flow between subsurface, well, facility & economics. In the traditional waterfall approach for field development planning, it takes several months for each discipline to prepare data and takes many iterations between disciplines to ensure feasibility for different development concepts. In the early phase of development, teams often do not have enough time to screen a wide range of development concepts, and the opportunities presented for sanction with limited options, and often not sanctioned or recycled. The results demonstrate its exceptional ability to identify multiple reservoir targets while seamlessly adhering to a predefined injection scheme. Moreover, this solution connects these targets to optimally placed facilities using drillable, optimized trajectories and then links the facilities with pipelines that are positioned in the most efficient manner possible. To showcase our solution, we utilized the synthetic field, Olympus, which was developed by TNO for EAGE Olympus Challenge. The transformational digital solution presented here would enable coherent data sharing across all discipline and empower multi-disciplinary team to achieve faster screening of a larger number of development scenarios, leading to more efficient decision-making in field development planning. The modular and flexible solution enables refinement of the field development plan throughout the project maturation journey with different trade-offs between accuracy and efficiency. The presented innovative solution breaks down organizational silos between the reservoir, wells, and facility domains by integrating discipline specific consideration upfront and allowing them to perform detailed analysis on coherent and consistent data. Having these smart algorithms on a cloud-native data flow orchestrator allows for fast production of multiple technically feasible development concepts. The solution has been successfully validated by multiple field development teams across the globe.