AS Mosley will attend OMAE 2017 in Trondheim, 25-30 June, for the publication of a paper which we co-authored in collaboration with BP and Fugro. The paper will be presented under the Rigid Risers symposia and is titled ‘Wellhead Monitoring – Measured Fatigue Damage Validation (OMAE2017-61081)’.
Our analysis supported BP in the North Sea with a real time monitoring campaign to measure wellhead fatigue damage. This technical paper describes the method validation, utilising measured data for calibration and refinement of the analysis models. Valuable lessons were learned which continues to build on our expertise in the area of wellhead integrity.
The OMAE2017-61081 paper abstract is presented below, please contact us if you have any questions, we would love to hear from you!
'A monitoring system is deployed on a BOP-stack and riser during drilling of production wells West of Shetland to record fatigue accumulation in the wellhead and conductor. Data is relayed to the vessel in real-time so that well operations can be planned to manage fatigue life. The monitoring assures the asset integrity maintained during construction and work-over operations throughout its lifecycle.
Motion measurements of the BOP-stack and riser are analysed in conjunction with a finite-element model of the wellhead-BOP-riser-vessel system to determine stresses at various welds. The main drawback of such approach is that “measured” fatigue still relies on the model accuracy, which cannot be guaranteed due to inevitable uncertainty associated with many parameters used in modelling.
This paper describes validation of the modelled subsea stack and its foundation characteristics against measurements so that “measured” fatigue is as accurate as possible. This involves (1) determining the depth of BOP-stack centre of rotation; (2) identifying the BOP-stack characteristic frequency, and (3) matching stress responses derived from measurements taken at different heights on the stack. Model parameters (e.g. soil stiffness and added mass) are tailored to optimise agreement with measurements thereby improving the accuracy of “measured” fatigue estimations.' Copyright OMAE 2017.
