Intelligent assessment method of reliability for deepwater riser deployment
Riser deployment is an important step in deepwater drilling,during which the spider is the prima-ry support of the riser system.At the same time,the harsh deepwater environment leads to a high risk of riser deployment.To ensure the safety of riser deployment,firstly,a joint distribution model of environmental pa-rameters was constructed.Then,an intelligent prediction model of structural response based on IAGA-BRNN was determined.Finally,the method of structure reliability assessment for riser deployment was estab-lished combining Monte Carlo,and a case study was carried out.Results show that most parameters in the joint distribution model of environment obey Weibull distribution and Beta distribution.The prediction model proposed in this paper performs well in all the prediction indicators,and has a stronger prediction ability com-pared with the conventional prediction model.The equivalent stress and maximum axial force are the first and secondary limitation factors of the riser deployment.In addition,as the number of hang-off riser increas-es,the reliability is on the decline,and wave height is the main limiting factor of operational reliability.
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维普
