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Abstract Subsea tiebacks are a principal building block of deepwater developments. Operators seek to continuously enhance operational efficiencies and tieback distances while reducing capital, operating expenditures, and emissions. Rapid advances have been made in remote operations, subsea equipment capabilities and standardization. However, significant additional improvements in subsea tieback operational efficiencies are achievable by leveraging the steep decline in data storage and processing costs, the massive increase in processing power and high-speed internet along with the availability of proven Artificial Intelligence (AI) and Machine Learning (ML) tools. Subsea tieback operational efficiency improvements are bottlenecked by human operator ability to process and respond in a timely manner to the overwhelming quantity of data collected by modern subsea monitoring and sensor technologies. This paper will address specific areas where the proven ability of AI and ML tools to assimilate large quantities of data, together with bespoke algorithms, can provide real-time, targeted recommendations to unlock the following improvements in subsea tieback operational efficiencies: Enhanced Oil Recovery: With real-time detection and analyses of changes and anomalies in production flow, AI can use Model Predictive Control (MPC) or Hybrid AI-Physics Models to optimize production rates, riser base gas lift, and gas or water injection systems. Predictive Maintenance: By ingesting and analyzing real-time sensor and Autonomous Underwater Vehicle (AUV)/Remote Operated Vehicle (ROV) data, AI algorithms can:Improve performance and reliability of subsea boosting systems (multiphase pumps, power generation and conditioning).Increase operational uptime and service life by anticipating potential failures in subsea infrastructure. Operational Efficiencies: AI can process vast amounts of data from disparate sources to support decision-making related to:Monitoring and predicting flow assurance challenges while suggesting targeted mitigations.Maintaining optimum production rates and flow conditions from wellhead to production manifold.Providing a holistic view of complex multi-tieback systems to facilitate decision-making targeting total asset performance. By combining data gathered from multiple sources (SCADA, PLC, Camera DVR, etc.) with bespoke algorithms, AI can provide diagnostic, prescriptive, intelligent insights; accelerate positive interventions; increase ultimate recovery while reducing downtime, power requirements, and emissions. The offshore oil and gas industry is embracing AI to make operations safer and more efficient. This paper will show how an integrated, holistic and targeted approach of incorporating AI into subsea tiebacks will enable the industry to immediately and inexpensively attain new levels of operational excellence, cost-effectiveness, and environmental sustainability.
Jarrell et al. (Mon,) studied this question.