The Mooring Digital Twin: Fatigue and Integrity Monitoring to Support Life Extension

Abstract Operators of floating production facilities must demonstrate their mooring systems are fit for service throughout operational life. When seeking life extension, the mooring system must be reassessed considering its present condition, load history, and forecast degradation. Given the significant CAPEX of mooring replacements or repairs, accurate assessment of fatigue loading and resistance, including the influence of degradation mechanisms such as corrosion and wear, is often crucial for the viability of extending the operating life of the facility using the existing moorings. This paper presents the application of a mooring digital twin to leverage operational data for both justifying mooring system life extension and implementing continuous integrity monitoring, in the absence of direct mooring line monitoring. The resulting system addresses Classification Society requirements while providing assurance on long-term system integrity. Hosted on the online SMIC platform, the digital twin approach combines detailed numerical analysis with vessel position and motion data, environmental measurements, and operational records such as vessel loading data and inspection data to create a virtual representation of the mooring system’s fatigue utilization. This enables a more accurate prediction of fatigue load duty compared to numerical simulations and provides a framework for continuous fatigue monitoring. A parallel application of mooring integrity monitoring, using the vessel position data to detect possible mooring failures, was also deployed on the same digital twin platform. Applied to OMV’s FPSO in New Zealand, the mooring digital twin enabled life extension through the implementation of live monitoring of fatigue duty and potential mooring failures. As direct load monitoring data was not available for this facility, the implementation of continuous fatigue monitoring was based on a multi-dimensional lookup of predicted fatigue damage in the observed operational conditions. Notably, this approach satisfied Classification Society requirements for reduced fatigue factors of safety using reliable operational data. This approach provides operators a pathway to justify life extension while giving Classification Societies, regulatory agencies and insurers greater confidence in ongoing system integrity.