Validation of tool for safer and more efficient offshore oil & gas vessel operations

The MetOcean Solutions' tool can predict conditions that are unsafe for FPSOs.

The MetOcean Solutions' tool can predict conditions that are unsafe for FPSOs.

A paper detailing research carried out at MetOcean Solutions has just been published in the Ocean Engineering journal.

The research, done by Ian Milne, Sebastien Delaux and Peter McComb, presents the validation of a tool used to predict the behaviour of the large vessels used for the processing and storage of oil and gas in remote and deepwater offshore locations under different metocean conditions. 

Floating Production, Storage and Offloading (FPSO) and Floating Liquid Natural Gas (FLNG) vessels are used around the world. These huge vessels (lengths of up to 300-400 m) are moored using a turret system, which lets the vessel rotate around the mooring fixed to the seabed. Once tethered, the vessels are typically left for up to 25 years in one location from which they are only moved if the safety of operations is threatened. 

The combined forces of wind, waves and currents determine the alignment of the vessels. Therefore, the ability to forecast headings is important to operators as certain directions could result in roll motion which may compromise safety and hence require operations to be shut down. 

Supported by a research and development grant from Callaghan Innovation, MetOcean Solutions has developed a tool for the prediction of vessel heading. The paper details the validation of the tool using measurements from an operating FPSO.

"The model predicted the vessel heading within an accuracy of 5% for a range of environmental conditions," states Dr Sebastien Delaux. "It is great to have a good validation, and we are looking forward to finalising the tool and making it operational, so that we can help operators identify dangerous conditions. The tool will also be useful in planning stages to assess the operability of an FPSO for a particular site." 

Ian Milne is now with the University of Western Australia.
Data for the validation of the tool was provided by OMV New Zealand.
Click here for details of the Callaghan Innovation Research and Development Grant.  
The full journal article can be found here