Reliability Assurance of Subsea Production Systems: A Systems Engineering Framework


1 Brunel University

2 Aker Solution London


​Due to the high investment costs for deep-water subsea production systems of high-value subsea fields, it is crucial to ensure a high availability to recover the investment. The problem is compounded by the cost of recovery, repair and replacement of failed equipment. Testing and reliability analyses are two pillars of reliability assurance; neither of them on their own assures the delivery of a reliable system. Possibly with more imaginative use of reliability methods, it is possible to optimise testing. It is suggested to use reliability analysis as a guide for allocating resources for testing. This paper outlines a Systems Engineering Framework to link the Client’s requirements for equipment reliability, as a means of proving the desired level of performance. This framework allows a better understanding of verification settings and strategies to handle constraints (e.g. costs, expandability, repair-ability, maintainability, intervention procedures, downtime, automation etc.) and performance measures, to achieve highly reliable production systems.  The bilateral links between the Client’s requirements and subsea equipment performance are established using the systems engineering V-model. These links relate equipment performance to one or more of the Client’s requirements, which helps establish verification and validation testing strategies to enhance reliability and reduce project risk. The proposed procedure also assists risk management efforts by feeding the results of reliability analyses, testing and project risk analysis into validation processes, the systems engineering measurement process ensures enhanced reliability. We define reliability assurance as a part of the systems engineering processes to ensure the continued function and resilience of the production system from the downhole valve to the subsea equipment, housed on the topside or at an onshore terminal, in their operating environment and condition using the “Fit-For-Service” notion.


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