Dynamic positioning evaluation study
Traditionally Floating Production Storage and Offloading (FPSO) systems use anchor leg mooring systems for the permanent mooring at a fixed position. The application of Dynamic Positioning (DP) systems is hardly used for mooring of FPSO’s. DP mooring seems to become more promising as it is a favorable option for operations of FPSO’s in deep waters and/or for relatively short field exploitations.
When operating on DP, an operator continuously has to supervise the process and correct the system if something goes wrong. As long as the process runs flawless, which it should do most of the time, the operator only has to look at his screens and see that the system is indeed functioning as it should. DP operations for FPSO’s will mostly run over a long period, so when an operator has looked to those screens where nothing special happens for a long time, his alertness is expected to become less and his response time might be high when a problem suddenly arises.
If the DP system can be made more ‘intelligent’ it might be able to supply the operator with valuable advice on how to react to an undesired event and thus decrease the response time, like for example a drive-off or drift-off event. If enough intelligence can be provided, it might be possible to work as an unmanned system, where an operator is only needed in case of a failure. In a normal engine room this kind of operation is normal: the engines run unmanned, but when an alarm is given the engine room becomes manned and operators have to solve a problem (for DP operations the engine room is always manned, but this might change if the system gets enough intelligence).
Unmanned operation for DP requires a much more sophisticated system than in an engine room, because a failure can have much more impact. An engine can be shut down by the software to prevent damage if a major problem arises, but shutting down a DP system will generally worsen the problem and cause a drift-off. Other solutions thus have to be found to deal with problems during operations.
Intelligence can be added to the system in different ways. Three promising fields of improvement are the application of feed-forward control, making the system self-learning and advising the operator on possible scenarios.
This project’s goal is to determine the extend of adding ‘intelligence’ to a DP system, so that safety, availability and reliability of DP operations will be increased. This goal can be translated into three research-questions:
1. How can an ‘intelligent’ system provide advice to the DP operator on how to deal with new and possibly dangerous situations?
2. How can an ‘intelligent’ system be made ‘self-learning’ so that it can update its own knowledge about the DP system during operations, to improve accurateness and reliability?
3. How can an ‘intelligent’ system use real time measured signals in feed-forward control?