Flexible Riser Life Extension Associating Machine Learning and Innovative Monitoring

摘要

The paper introduces advanced flexible riser design fatigue analysis anddescribes an innovative method that allows the conversion of measureddynamic riser and vessel response into real time fatigue damageaccumulation. This is achieved through a combination of field-provenriser monitoring system, machine learning, and global and local flexibleriser stress analysis at both the tensile and pressure armour layers of aflexible riser. The innovative monitoring system outputs and benefits aredescribed, being the input for the machine learning method used forfatigue tracking. Key aspects and benefits of the methodology, resultsand the efficiency increase in comparison to traditional methods arediscussed and recommendations made on the multiple applications thatare enabled through these.