A significant effort is made by the industry through analyses and field monitoring to ensure delivery of safe and reliable wells. Fatigue analysis is an important aspect of well integrity assurance. Structural fatigue damage arises from stress changes caused by environmental cyclic loads acting on the riser system. In practice, the conductor-soil interaction under cyclic loading is modeled using the soil resistance-displacement (P-y) springs. Use of an appropriate soil model is essential for accurate determination of the fatigue damage. The American Petroleum Institute recommendations (API 2011) for P–y curves, which are often used for conductor–soil interaction analysis, have originally been developed for piled foundation and are inappropriate for well fatigue analysis. To that end, a new approach was developed by Zakeri et al. (2015) to derive P-y curves specifically for well fatigue analysis. Ultimate performance of each soil model can be determined and verified with field monitoring.
This paper presents results of a field monitoring campaign for a well drilled in 354 ft water depth within a complex seabed stratigraphy comprising sands (loose to dense) and clays (very soft to stiff). Design, calibration and verification of the riser/conductor structural model using field data are presented in a companion paper (Ge et al. 2017). Herein, the effect of soil modeling on wellhead fatigue is discussed and predictions made with the API (2011) and the Zakeri et al. (2015) soil P-y springs are compared to field monitoring data. For the case presented herein, the results indicate that the Blowout Preventer (BOP) stack motion response is significantly affected by the soil stiffness and modeling methods. The predictions made with the Zakeri et al. (2015) model provided BOP response similar to those observed in the field both above and below the mudline. Whereas, the analyses done with the API (2011) model significantly overestimated the ‘measured’ conductor fatigue life above the mudline and underestimated it below. The results of this monitoring program are a step forward in better understanding system behavior of offshore wells.
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