Neural-network prediction of riser top tension for vortex induced vibration suppression

Abstract

Vortex induced vibration (VIV) of marine riser is a significant challenge for the offshore oil and gas industry. Traditional passive suppression devices which are commonly used in permanent production risers to reduce the risks of collision caused by VIV are less practical to be utilized in short-term drilling operation due to expensive overhead cost and installation time factors. This paper studied active control of riser VIV by tuning the tensioner output force (pretension) so that this method can be utilized in short-term operation, such as drilling, without adding additional high-cost systems. A novel active control method by using neural network in tuning top tension of marine riser was studied to examine the effectiveness of VIV suppression. A response surface was derived from VIV experimental data and used to predict the targeted riser top tension to be exerted by the tensioner under different conditions. Reduction of VIV amplitude has been identified for the range of applicability. The findings of this paper have identified the practical scope of active control for riser top tension tuning to suppress VIV.