Effective artificial lift is essential for maximizing hydrocarbon recovery from complex offshore fields, with Electrical Submersible Pumps (ESPs) playing a critical role in transporting produced fluids. Deploying ESPs in seabed boosting systems offers clear advantages in subsea environments, especially in operations involving Floating Production, Storage, and Offloading (FPSO) units Ref 4.2. Housing ESPs on the seabed enables intervention-free replacement—a key factor in improving maintenance efficiency and uptime on remote deepwater platforms 1. However, ensuring the reliable and efficient performance of high-flow ESPs presents major challenges, particularly in demanding fields like Jubarte, offshore Brazil. The harsh production conditions—such as heavy crude oil, high viscosity, variable Gas-Oil Ratios (GOR), and complex deepwater dynamics 2,5—can significantly reduce hydraulic efficiency, trigger issues like gas locking, increase power consumption, and drastically shorten ESP lifespan. Overcoming these challenges required not only advanced technology but also a strong collaboration between Petrobras and SLB, focused on developing remote operations tailored to Jubarte's unique requirements. The offshore industry's push for Digital Transformation—aimed at enhancing safety, increasing efficiency, and reducing costs—relies heavily on advanced automation and real-time data to support operational models with reduced offshore staffing. As part of this transformation, complex surveillance and optimization tasks are being shifted to specialized onshore support centers. The advanced system described in this paper, implemented on FPSO P-57, clearly reflects this digital shift. It is enabled by continuous ESP monitoring and the combined expertise of remote surveillance teams from both the ESP supplier and the operator. Expert oversight from onshore centers supports this modern, data-driven approach. Such collaboration enables proactive optimization, supports long-term ESP integrity, and serves as the foundation for a successful reduced-POB (Personnel on Board) operational model.
Bacellar et al. (Mon,) studied this question.