This paper presents a case study of the use of an enhanced analytical approach, combined with the use of structural monitoring, as an enabling technique in the planning of sidetrack operations on a well in 110m water depth in the Northern North Sea.
Subsea wellheads are fatigue sensitive structures due to their exposure to dynamic loading transferred from connected riser systems. Intervention and workover operations over the life span of the well each contribute to the total fatigue damage accumulated in components that cannot be readily inspected. Accurate assessment of fatigue damage accumulation in ageing wells using advanced analytical techniques is often necessary to quantify the residual life of these components. The ability to reliably estimate this life can greatly affect the planning and viability of operations to enhance the productivity of ageing wells, particularly in the North Sea.
A simplified screening approach to wave and current fatigue assessment, typically applied to new-drill wells, with comparatively fatigue resistant hardware is unlikely to be sufficient to provide the level of confidence required when planning intervention operations on a brownfield development featuring less fatigue resistant hardware. Further sophistication, more involved than the typical approach, is necessary to avoid over-conservatism and to provide confidence to proceed with the planned operations. To thoroughly assess the fatigue accumulation in an ageing well, a detailed operational history including hindcast or measured weather data is usually sourced. The assessment is conducted to ensure that the actual operational conditions during periods when risers were connected are as accurately represented as possible. However, this may not be sufficient to bring the resulting fatigue damage within the allowable limits set using the traditional code-defined factor of safety approach. In this scenario further analytical methods are required.
The use of pre and post-failure analysis and the development of a monitoring strategy to maximise both the likelihood of identifying a fatigue failure during the operations and the ability to subsequently calibrate the analytical models are discussed. The applicability of these techniques to other operations and geographical locations is also described
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