Using Big Data to manage safety-related risk in the upstream oil & gas industry: a research agenda

Tan, Kim Hua and Ortiz-Gallardo, Víctor G. and Perrons, Robert K. (2016) Using Big Data to manage safety-related risk in the upstream oil & gas industry: a research agenda. Energy Exploration & Exploitation, 34 (2). pp. 282-289. ISSN 0144-5987

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Abstract

Despite considerable effort and a broad range of new approaches to safety management over the years, the upstream oil & gas industry has been frustrated by the sector’s stubbornly high rate of injuries and fatalities. This short communication points out, however, that the industry may be in a position to make considerable progress by applying ‘‘Big Data’’ analytical tools to the large volumes of safety-related data that have been collected by these organizations. Toward making this case, we examine existing safety-related information management practices in the upstream oil & gas industry, and specifically note that data in this sector often tends to be highly customized, difficult to analyze using conventional quantitative tools, and frequently ignored. We then contend that the application of new Big Data kinds of analytical techniques could potentially reveal patterns and trends that have been hidden or unknown thus far, and argue that these tools could help the upstream oil & gas sector to improve its injury and fatality statistics. Finally, we offer a research agenda toward accelerating the rate at which Big Data and new analytical capabilities could play a material role in helping the industry to improve its health and safety performance.

Item Type: Article
Keywords: Oil & gas, safety, Big Data, health, safety, and environment
Schools/Departments: University of Nottingham, UK > Faculty of Social Sciences > Nottingham University Business School
Identification Number: 10.1177/0144598716630165
Depositing User: Eprints, Support
Date Deposited: 09 Mar 2017 09:48
Last Modified: 13 Oct 2017 01:31
URI: http://eprints.nottingham.ac.uk/id/eprint/41188

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