A Technique for the Retrospective and Predictive Analysis of Cognitive Errors for the Oil and Gas Industry (TRACEr-OGI)

Journal article


Theophilus, S., Ekpenyong, I., Ifelebuegu, A., Arewa, A., Agyekum-Mensah, G. and Ajare, T. (2017). A Technique for the Retrospective and Predictive Analysis of Cognitive Errors for the Oil and Gas Industry (TRACEr-OGI). Safety. 3(4) (23). https://doi.org/10.3390/safety3040023
AuthorsTheophilus, S., Ekpenyong, I., Ifelebuegu, A., Arewa, A., Agyekum-Mensah, G. and Ajare, T.
Abstract

Human error remains a major cause of several accidents in the oil and gas (O&G) industry. While human error has been analysed in several industries and has been at the centre of many debates and commentaries, a detailed, systematic and comprehensive analysis of human error in the O&G industry has not yet been conducted. Hence, this report aims to use the Technique for Retrospective and Predictive Analysis of Cognitive Errors (TRACEr) to analyse historical accidents in the O&G industry. The study has reviewed 163 major and/or fatal O&G industry accidents that occurred between 2000 and 2014. The results obtained have shown that the predominant context for errors was internal communication, mostly influenced by factors of perception. Major accident events were crane accidents and falling objects, relating to the most dominant accident type: ‘Struck by’. The main actors in these events were drillers and operators. Generally, TRACEr proved very useful in identifying major task errors. However, the taxonomy was less useful in identifying both equipment errors and errors due to failures in safety critical control barriers and recovery measures. Therefore, a modified version of the tool named Technique for the Retrospective and Predictive Analysis of Cognitive Errors for the Oil and Gas Industry (TRACEr-OGI) was proposed and used. This modified analytical tool was consequently found to be more effective for accident analysis in the O&G industry.

Year2017
JournalSafety
Journal citation3(4) (23)
PublisherMDPI
ISSN2313-576X
Digital Object Identifier (DOI)https://doi.org/10.3390/safety3040023
Publication dates
Online25 Sep 2017
Publication process dates
Accepted12 Sep 2017
Deposited20 Jul 2022
Publisher's version
License
File Access Level
Open
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