Risk Based Integrity Assessment and Control of Ageing Subsea Pipelines: An Expert System Based Approach

Many of the subsea pipelines around the world are reaching the end of their design life, and some are already under operation beyond the design life. Inherently, it is expensive to replace or repair subsea pipelines. This is mainly due to the fact that cost of replacement or repair necessitates the cost of loss of production during the shutdown period. Hence, it is vital to maintain the integrity of pipelines at an anticipated level to optimize replacements and repairs. To conserve the integrity of pipelines, it is necessary to allocate a larger proportion of budgets for inspection, maintenance and subsequently for necessary replacements and repairs. In addition, in the light of a number of high profile incidents, political and regulatory pressure has grown on asset owners to certify that they maintain pipeline integrity at an anticipated level. Regulatory authorities shall check up on the integrity assessment and control (IA&C) process of pipeline systems to confirm that the risk of a potential failure is as low as reasonably possible (ALARP). Assessments of the risk of potential failures of ageing pipelines provide an opportunity to optimize expenditures on IA&C. In this context, setting economic inspection intervals to prevent failures, limit risks to ALARP, quantify the present integrity (using available design data and as-built data, inspection data, loading and environmental data), and predict the future integrity (forecast operating conditions using past and present operating conditions) play a significant role. There is a need to employ expert systems to undertake risk based IA&C to minimize the variability in the assessments and evaluations caused by frequent migration of experts from one organization to another and new recruits with lack of experience. This manuscript provides the state of the art of the IA&C of subsea systems and proposes an expert-systems-based approach to minimize the variability caused in the IA&C process.