Application of Evolutionary Algorithms for Optimal & Flexible Field Architectures (OFFA)

The development of offshore fields, particularly in ultra-deepwater environments, presents significant technical and economic challenges that demand innovative, data driven approaches to maximize project value while managing uncertainties. Traditional concept selection processes often rely on manually generated alternatives and simplified assumptions, limiting the exploration of the full solution space and potentially overlooking more efficient field development strategies. Leveraging advanced tools and methodologies empowers engineers to improve project efficiency and optimize resource utilization in offshore field development. This paper introduces an enhanced methodology that integrates Evolutionary Algorithms (EA) with automated concept generation to support the design of Optimal and Flexible Field Architectures (OFFA). Building on the foundational work of (Diaz Arias et al. 2021), this study extends the framework by incorporating a probabilistic uncertainty analysis that accounts for variability in reservoir performance, capital expenditures (CAPEX), and oil prices. The proposed approach enables the automated generation, evaluation, and refinement of subsea field layouts, including decentralized processing modules such as Subsea Gate Boxes (SGBs), with the objective of maximizing Net Present Value (NPV) under uncertainty. Decentralized processing using modular SGBs may enable viability for challenging field developments, and their benefits increase with water depth, flowrates and step-out. Regarding subsea separation, these advantages are maximized when employing subsea compact separation technologies (Albuquerque et al. 2013). The Subsea Gate Box (SGB) is a multipurpose assembly that makes it possible to decouple well performance from the flow restrictions imposed by the common network. These process units perform the preliminary stages of processing, preparing the wells to be connected to the production system by integrating various process modules, such as separation, boost, chemical injection, metering, or any other process that may help the production stream perform better (Sales et al. 2024). An innovative application of Evolutionary Algorithms (EA) to support the optimization of subsea system design and flow assurance analysis in the context of field development optimization is presented. The proposed methodology Optimal and Flexible Field Architectures (OFFA) integrates engineering and economic evaluations to identify near-optimal project solutions during the conceptual phase. It incorporates probabilistic uncertainty analysis to account for variability in reservoir performance, capital expenditures (CAPEX), and oil prices, with the objective of maximizing Net Present Value (NPV) under uncertainty. The uncertainty modeling approach considered relevant uncertainties grounded in recent work by (Sales et al. 2024), which provide a framework for incorporating variability in key economic drivers into early-phase decision-making.