The Level of Automation in Emergency Quick Disconnect Decision Making

• Published in: Journal of marine science and engineering Vol. 6; no. 1; p. 17
• Main Authors: Marius, Imset, Kristin, Falk, Marianne, Kjørstad, Salman, Nazir
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 12-02-2018
• Subjects: Accidents; Artificial intelligence; Automation; Autonomy; Decision making; Decision support systems; Drills; dynamic positioning; Economic impact; Emergencies; Emergency procedures; Emergency Quick Disconnect; Environmental protection; Frameworks; human factors; Human performance; Impact analysis; marine environment; Offshore; Offshore drilling rigs; Procedures; Vulnerability
• ISSN: 2077-1312; 2077-1312
• DOI: 10.3390/jmse6010017

As a key measure for safety and environmental protection during offshore well operations, drill rigs are equipped with Emergency Quick Disconnect (EQD) systems. However, an EQD operation is in itself considered a risky operation with a major economic impact. For this reason, it is of great importance to aid the operators in their assessment of the situation at all times, and help them make the best decisions. However, despite the availability of such systems, accidents do happen. This demonstrates the vulnerability of our human decision-making capabilities in extremely stressful situations. One way of improving the overall human-system performance with respect to EQD is to increase the level and quality of the automation and decision support systems. Although there is plenty of evidence that automated systems have weaknesses, there is also evidence that advanced software systems outperform humans in complex decision-making. The major challenge is to make sure that EQD is performed when necessary, but there is also a need to decrease the number of false EQDs. This paper applies an existing framework for levels of automation in order to explore the critical decision process leading to an EQD. We provide an overview of the benefits and drawbacks of existing automation and decision support systems vs. manual human decision-making. Data are collected from interviews of offshore users, suppliers, and oil companies, as well as from formal operational procedures. Findings are discussed using an established framework for the level of automation. Our conclusion is that there is an appropriate level of automation in critical situations related to the loss of the position of the drill rig, and that there is the promising potential to increase the autonomy level in a mid- and long-term situation assessment.