An efficient methodology for estimating the extreme response of risers, e.g. Steel Catenary Risers (SCR) or Steel Lazy Wave Risers (SLWR), connected to deep water floaters with large hang-off motions is presented. The conventional approach is to estimate the appropriate level of long-term response based on variable short-term sea states and multiple floater loading conditions. This approach is computationally intensive and not considered practical for a typical project time frame. The methodology presented in this paper reduces the computational efforts while still maintaining a high level of accuracy by using directional sea state contour plots and combinations of floater loading conditions and offsets


Risers are an important component of any deep water field development. Estimating the right level of long-term response for a given return period, e.g., 100-years or 10,000-years, combining varying sea states from every direction and floater motion variations due to draft and floater offsets is computationally demanding.

Sea states for a given wave direction are often represented by a wave contour diagram, which describes Hs/Tp combinations for a given return period or probability of exceedance, Haver et al.(2013). Further, the long term response of risers and ancillary riser components connected to large motion floaters need to have higher fractile response from every short term sea state, Haver and Winterstein (2008) and Haver et al.(2013). Typically for floaters with large motions and varying sea states, a 90% fractile level of response from short term sea states gives an appropriate long term response, Haver at al.(2013).

In order to estimate higher fractile extreme response, many short-term extremes are estimated and fitted to an extreme value distribution like Gumbel distribution. This often requires at least 30 to 40 independent 3-hour long realizations to estimate extremes with an acceptable statistical certainty. Combining multiple sea states in each direction along the wave contour diagram, all wave directions and variations in floater draft and offset requires considerable computational resources. Such high computational demand is difficult to sustain on fast paced project when changes in design parameters are common.

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