  Slender marine structures such as deep-water marine risers are subjected to
currents and will normally experience Vortex Induced Vibrations (VIV), which
can cause fast accumulation of fatigue damage. The ocean current is often
three-dimensional (3D), i.e., the direction and magnitude of the current vary
throughout the water column. Today, semi-empirical tools are used by the
industry to predict VIV induced fatigue on risers. The load model and
hydrodynamic parameters in present VIV prediction tools are developed based on
two-dimensional (2D) flow conditions, as it is challenging to consider the
effect of 3D flow along the risers. Accordingly, the current profiles must be
purposely made 2D during the design process, which leads to significant
uncertainty in the prediction results. Further, due to the limitations in the
laboratory, VIV model tests are mostly carried out under 2D flow conditions and
thus little experimental data exist to document VIV response of riser subjected
to varying directions of the current. However, a few experiments have been
conducted with 3D current. We have used results from one of these experiments
to investigate how well 1) traditional and 2) an alternative method based on a
data driven prediction can describe VIV in 3D currents. Data driven modelling
is particularly suited for complicated problems with many parameters and
non-linear relationships. We have applied a data clustering algorithm to the
experimental 3D flow data in order to identify measurable parameters that can
influence responses. The riser responses are grouped based on their statistical
characteristics, which relate to the direction of the flow. Furthermore we fit
a random forest regression model to the measured VIV response and compare its
performance with the predictions of existing VIV prediction tools (VIVANA-FD).
