Dynamics of severe accidents in the oil & gas energy sector derived from the authoritative ENergy-related severe accident database

Mignan, Arnaud; Spada, Matteo; Burgherr, Peter; Wang, Ziqi; Sornette, Didier

doi:10.1371/journal.pone.0263962

Please use this identifier to cite or link to this item: https://doi.org/10.21256/zhaw-24475

Publication type:	Article in scientific journal
Type of review:	Peer review (publication)
Title:	Dynamics of severe accidents in the oil & gas energy sector derived from the authoritative ENergy-related severe accident database
Authors:	Mignan, Arnaud Spada, Matteo Burgherr, Peter Wang, Ziqi Sornette, Didier
et. al:	No
DOI:	10.1371/journal.pone.0263962 10.21256/zhaw-24475
Published in:	PLOS ONE
Volume(Issue):	17
Issue:	2
Page(s):	e0263962
Issue Date:	2022
Publisher / Ed. Institution:	Public Library of Science
ISSN:	1932-6203
Language:	English
Subject (DDC):	363: Environmental and security problems
Abstract:	Organized into a global network of critical infrastructures, the oil & gas industry remains to this day the main energy contributor to the world's economy. Severe accidents occasionally occur resulting in fatalities and disruption. We build an oil & gas accident graph based on more than a thousand severe accidents for the period 1970-2016 recorded for refineries, tankers, and gas networks in the authoritative ENergy-related Severe Accident Database (ENSAD). We explore the distribution of potential chains-of-events leading to severe accidents by combining graph theory, Markov analysis and catastrophe dynamics. Using centrality measures, we first verify that human error is consistently the main source of accidents and that explosion, fire, toxic release, and element rupture are the principal sinks, but also the main catalysts for accident amplification. Second, we quantify the space of possible chains-of-events using the concept of fundamental matrix and rank them by defining a likelihood-based importance measure γ. We find that chains of up to five events can play a significant role in severe accidents, consisting of feedback loops of the aforementioned events but also of secondary events not directly identifiable from graph topology and yet participating in the most likely chains-of-events.
URI:	https://digitalcollection.zhaw.ch/handle/11475/24475
Fulltext version:	Published version
License (according to publishing contract):	CC BY 4.0: Attribution 4.0 International
Departement:	School of Engineering
Organisational Unit:	Institute of Sustainable Development (INE)
Appears in collections:	Publikationen School of Engineering

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Mignan, A., Spada, M., Burgherr, P., Wang, Z., & Sornette, D. (2022). Dynamics of severe accidents in the oil & gas energy sector derived from the authoritative ENergy-related severe accident database. Plos One, 17(2), e0263962. https://doi.org/10.1371/journal.pone.0263962

Mignan, A. et al. (2022) ‘Dynamics of severe accidents in the oil & gas energy sector derived from the authoritative ENergy-related severe accident database’, PLOS ONE, 17(2), p. e0263962. Available at: https://doi.org/10.1371/journal.pone.0263962.

A. Mignan, M. Spada, P. Burgherr, Z. Wang, and D. Sornette, “Dynamics of severe accidents in the oil & gas energy sector derived from the authoritative ENergy-related severe accident database,” PLOS ONE, vol. 17, no. 2, p. e0263962, 2022, doi: 10.1371/journal.pone.0263962.

MIGNAN, Arnaud, Matteo SPADA, Peter BURGHERR, Ziqi WANG und Didier SORNETTE, 2022. Dynamics of severe accidents in the oil & gas energy sector derived from the authoritative ENergy-related severe accident database. PLOS ONE. 2022. Bd. 17, Nr. 2, S. e0263962. DOI 10.1371/journal.pone.0263962

Mignan, Arnaud, Matteo Spada, Peter Burgherr, Ziqi Wang, and Didier Sornette. 2022. “Dynamics of Severe Accidents in the Oil & Gas Energy Sector Derived from the Authoritative ENergy-Related Severe Accident Database.” Plos One 17 (2): e0263962. https://doi.org/10.1371/journal.pone.0263962.

Mignan, Arnaud, et al. “Dynamics of Severe Accidents in the Oil & Gas Energy Sector Derived from the Authoritative ENergy-Related Severe Accident Database.” Plos One, vol. 17, no. 2, 2022, p. e0263962, https://doi.org/10.1371/journal.pone.0263962.