Wellhead fatigue monitoring was performed during Plug and Abandonment (P&A) activities of a well in the Gulf of Mexico (GOM). Fatigue monitoring was deemed necessary for several reasons: an older vintage of wellhead system with uncertain fatigue life consumption from previous drilling activities, excessive wellhead stick-up, potentially large rig motions from a moored drilling rig for P&A. Fatigue monitoring was performed to ensure the integrity of the wellhead during P&A operations.
The wellhead fatigue monitoring methods previously developed by several of the coauthors was applied in the wave-dominated GOM environment. Motions of the Blow Out Preventer(BOP) stack were measured and combined with a model of the riser/BOP/wellhead/casing system to reconstruct fatigue damage in the wellhead, conductor and surface casing. To measure wellhead motions, Subsea Vibration Data Loggers (SVDLs) were run with the riser and retrieved via Remotely Operated Vehicle (ROV). Fatigue damage reconstruction in the wellhead, conductor and surface casing was performed directly using the measured motion data and an analytical transfer functions obtained from the calibrated Finite Element (FE) model. Results were provided with fast turnaround time to support operations.
Results demonstrated that fatigue damage rates compared well with pre-deployment predictions, though measured fatigue demand was slightly higher. It was also demonstrated that the primary cause of fatigue damage was due to wave activity at the site. Analysis of low frequency response at the riser natural frequencies indicated that the first few riser modes may have been excited by currents. It was also demonstrated that the low frequency response did not contribute significantly to fatigue life.
The wellhead monitoring methods discussed result in rapid turn-around of valuable fatigue life consumption information, enabling informed decisions to be made in challenging conditions. The monitoring instrumentation and fatigue analysis methods increase the safety and efficiency of drilling, workover and P&A activities. In a larger sense, measured data also serves as a benchmark for analytical model calibration activities, reducing the known conservatism in stress and fatigue in future deployments.