There is growing concern in the oil and gas industry about the high frequency of mooring line failure and its potentially catastrophic consequences
Physical tension sensors can be difficult and costly to maintain, and can be prone to failure within the first few years of installation
Machine learning is a more accurate and less costly method for anomaly detection, structural integrity assessment, and virtual sensors
In more than 99% of simulated test cases, DNV GL’s machine-learning algorithm can identify accurately the condition of mooring lines
Failure of mooring systems is a persistent problem for floating offshore facilities such as floating production, storage and offloading (FPSO) vessels. On average, about two incidents of permanent mooring systems failing were reported annually between 2000 and 2013, according to various analysts.1,2,3 One of these studies found that nearly half of such incidents reported over a decade involved failures of multiple mooring lines. Another estimated that 150 mooring lines were repaired or replaced in the period cited above.
For example, the Gryphon Alpha FPSO vessel came off station in a storm in the UK North Sea in 2011 when four of its 10 mooring lines parted.4 This reportedly cost an estimated USD1.8 billion to reinstate, and another USD300 million later that year when five of 10 lines parted and the vessel again came off station.1
The consequences of mooring system failure can be dangerous and costly. In the severest cases, vessels have drifted and risers connecting floating structures to subsea systems have ruptured. Such incidents have resulted in extended field shutdowns and raised risk to life, property, and the environment. Despite this, no formally published study has yet quantified both the likelihood of failure and its consequences at specific points along a mooring line.
Traditional ways of detecting and predicting mooring line failure have limitations
Traditional methods of failure detection rely on either a ‘watch circle’ approach or the measurement of mooring line tension.
In essence, the watch circle method establishes a ring inside of which the vessel is assumed to operate with all mooring lines intact. However, this approach lacks accuracy and reliability and is not very practical in operational use. Physical tension sensors on mooring lines are expensive and problematic to maintain. Field experience suggests that they are prone to failure within a few years of installation.