As offshore units near the end of their design life, Operators are often faced with the requirement of extending the operating life of the facility, either to continue producing from an existing and still productive field, or to pursue new opportunities and/or defer new CAPEX as is often the case with MODUs, construction and support vessels and leased production units.

Life extension presents a unique engineering challenge from the perspective of risk management; requiring a complete structural re-assessment of the facility, from its current, as-is condition in order to determine the remaining life of the unit, along with any repairs required in order to achieve the desired additional service life.

This paper describes a methodology, developed by Bureau Veritas, for the engineering reassessment of aging offshore units that will help operators with decision making relating to life extension. It will focus on the two main degradation mechanisms affecting the structure: corrosion and fatigue.

Resulting directly from Bureau Veritas's digital transformation strategy, the methodology is built around the concept of a 3-D "digital twin" model of the asset, which is updated periodically and automatically with critical inspection data collected by connected surveyors. This facilitates continuous updating of the model to ensure a "real-time" equivalence to the "as-is" physical asset.

Furthermore, interfaces between the "digital twin" and conventional structural and hydrodynamics analysis software enable accurate condition assessment analyses to be performed, at any time, on the current state of the asset; providing critical information to be used in the assessment of feasibility of life extension and in determining actual expected remaining life.

In the event of extended life operations, the output of these condition assessment calculations can also be used to develop a Risk-Based Inspection (RBI) programme, based on the criticality and condition of each structural element, to monitor the critical degradation mechanisms, and measure and predict on-going degradation and calculate any consequences to the actual remaining life, using the continuously updated "digital twin". This approach maximizes the useful life of any facility while minimizing the overall cost of inspection, without compromising safety.

While the focus of this paper is life extension of existing assets, this methodology is equally applicable and valid for application on new-build assets, allowing risk-based and just-in-time management of maintenance and repair operations as well as real-time determination of existing asset life from the earliest stages of an assets deployment.

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