Data-driven failure analysis of emergency shutdown systems in oil and gas industry

Abstract

Purpose Emergency shutdown (ESD) systems play a critical role in ensuring safety and availability of oil and gas production. The systems are operated in on-demand mode, and the detection and prediction of their failures is deemed challenging. The purpose of this paper is to develop a logical data-driven approach to enhance the understanding and detectability of ESD system failures. Design/methodology/approach The study was conducted in close collaboration with the Norwegian oil and gas industry. The study and analyses were supported by industrial data, failure data generated in a test facility in Norway and domain experts. Findings The paper demonstrated that there is a considerable potential to improve the decision process and to reduce the workload related to ESD systems by means of a logical data-driven approach. The results showed that the failure analysis process can be executed with more clarity and efficiency. Common cause failures could also be identified based on the suggested approach. The study further underlined the requirements regarding relevant data, new competence and technical supports in order to improve the current practice. Originality/value The paper leveraged the value of real-time data in identifying failures through mapping of the interrelationships between data, failure mechanisms and decisions. The failure analysis process was re-designed, and the understanding and decision making related to the system was improved as a result. The process developed for ESDs can further be adapted as a common practice for other low-demand systems.