Towards Autonomous Operations

Abstract

Abstract There has been tremendous focus in recent years in applying automation technology to offshore operations in order to reap the promised benefits of increased productivity and economic returns while reducing emissions and ensuring workforce safety. While there are few concrete numbers available, a recent study (ABB 2022) demonstrates clearly the motivation to take further steps on the journey towards autonomous operations showing annual operating cost savings of between 30-50%, carbon savings of up to 27% per asset per year and improvements for the safety and work life balance of the workforce. The ambition -and long-term vision- is to have operations conducted entirely autonomously – not only capable of managing themselves during stable operation, but also being robust enough to deal with unexpected and unforeseen situations such as process upsets and of course this should be extended to cover start-up and shut down. We also anticipate a change in maintenance philosophy giving an overhaul of maintenance operations to stretch the interval between planned campaigns. Progress in the last few decades shows a clear move in the right direction with everything from technology breakthroughs, acceptance of remote work and the focus on decarbonization. There are several key technologies that are the building blocks behind these trends including advances in low cost and low power sensors that are widely connected, cyber security, big data and analytics that can aggregate this information in the cloud, and spot trends and patterns to provide an automatic response. The same cloud-based data also gives experts in a collaboration center a high-definition picture of the plant which in turn leads to stronger situational awareness. Transitioning operations from automated to completely autonomous is not a one-step process- it is a journey. ARC (ARC 2023) and others have developed a six-level maturity model which is useful both as a roadmap and a benchmark. Each level in this model is defined by the degree of autonomy from low level PID control through to the highest level defining fully autonomous operations where operators are, in principle, not required for any intervention and the system can deal with unexpected abnormalities. As we transition through this model, we shift the balance of tasks from human operator to the control system moving from hands-on, on-site operators through remote control where the operators are largely away from the plant to the adoption of integrated analytics where certain actions of the operator are automated and replaced by the system or machine. We can't easily generalize but most offshore energy production operations are currently at Level 2 or 3. Those that are moving towards level 4 are implementing a maintenance regime based on predictive analytics and deep insights that assist. This paper will outline the scope, the ambitions, and the benefits of working towards more autonomous operations. It will explain the maturity model and will illustrate the benefits and challenges of turning strategy into delivery through 3-4 cases and examples.