Abstract
The mooring system of a floating offshore structure plays a vital role in protecting critical infrastructure links between the seabed and the floating structure. While mooring systems are designed to withstand a large range of environmental conditions, industry experience has shown that, even in recent years, mooring failures occur at a rate higher than anticipated in regulatory guidance and design practices. As such, monitoring during the operations phase forms a key part of an offshore asset integrity management strategy. The advancement of asset owners' digital architectures over recent years has started to unlock significant improvements in the capabilities of remote monitoring of offshore assets. However, the ubiquity of sensors and data from modern assets introduces its own challenges. Operators can easily be deluged with information with no clear insights or path to action. This raises the importance of smart supervisory monitoring systems that synthesize the available data into useful insights while still providing operators with the information required to understand the system's behavior.
This paper presents a case study in the deployment of a field-proven remote mooring integrity monitoring system, for the world's largest floating structure – the Prelude FLNG. As the monitoring system was introduced to an already operational asset, the case study provides an example of a successful retrofit of a new monitoring methodology into existing infrastructure with no new sensors or other hardware. For example, the deployment was reliant on interfacing smoothly with the operator's existing cloud data infrastructure, the architecture of which was critical in ensuring a reliable data feed into the monitoring system. The mooring integrity monitoring system synthesized data from a range of sources including metocean data, vessel position and thruster data, and mooring inclinometer data.
The paper outlines some of the practical challenges in the deployment of retrofit software-based integrity monitoring systems for offshore assets, including factors that can affect the quality of the data available and how this data quality influences subsequent engineering assessments. The paper then presents an innovative approach to how the data sources were combined to provide a mooring monitoring system that is robust against multiple sensor failure and data loss. The result is a monitoring system with a high level of redundancy, which can detect a failure in any mooring line even when only a small percentage of the original sensors are generating reliable data.
Through the successful demonstration and deployment of a remote monitoring system which leverages existing sensors without the need for additional offshore works, the project outlined in this paper demonstrates a new frontier in mooring integrity management of floating platforms.
