IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0263962.html
   My bibliography  Save this article

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

Author

Listed:
  • Arnaud Mignan
  • Matteo Spada
  • Peter Burgherr
  • Ziqi Wang
  • Didier Sornette

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.

Suggested Citation

  • Arnaud Mignan & Matteo Spada & Peter Burgherr & Ziqi Wang & Didier Sornette, 2022. "Dynamics of severe accidents in the oil & gas energy sector derived from the authoritative ENergy-related severe accident database," PLOS ONE, Public Library of Science, vol. 17(2), pages 1-14, February.
  • Handle: RePEc:plo:pone00:0263962
    DOI: 10.1371/journal.pone.0263962
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0263962
    Download Restriction: no

    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0263962&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pone.0263962?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Christian Otto & Franziska Piontek & Matthias Kalkuhl & Katja Frieler, 2020. "Event-based models to understand the scale of the impact of extremes," Nature Energy, Nature, vol. 5(2), pages 111-114, February.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Mustafa, Faizan E & Ahmed, Ijaz & Basit, Abdul & Alvi, Um-E-Habiba & Malik, Saddam Hussain & Mahmood, Atif & Ali, Paghunda Roheela, 2023. "A review on effective alarm management systems for industrial process control: Barriers and opportunities," International Journal of Critical Infrastructure Protection, Elsevier, vol. 41(C).
    2. Arnaud Mignan, 2022. "A Digital Template for the Generic Multi-Risk (GenMR) Framework: A Virtual Natural Environment," IJERPH, MDPI, vol. 19(23), pages 1-22, December.
    3. Arnaud Mignan, 2022. "Categorizing and Harmonizing Natural, Technological, and Socio-Economic Perils Following the Catastrophe Modeling Paradigm," IJERPH, MDPI, vol. 19(19), pages 1-32, October.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Nikas, A. & Gambhir, A. & Trutnevyte, E. & Koasidis, K. & Lund, H. & Thellufsen, J.Z. & Mayer, D. & Zachmann, G. & Miguel, L.J. & Ferreras-Alonso, N. & Sognnaes, I. & Peters, G.P. & Colombo, E. & Howe, 2021. "Perspective of comprehensive and comprehensible multi-model energy and climate science in Europe," Energy, Elsevier, vol. 215(PA).
    2. Yongxiang Liu & Hongmei Zhao & Guangying Zhao & Xinyuan Cao & Xuelei Zhang & Aijun Xiu, 2023. "Estimates of Dust Emissions and Organic Carbon Losses Induced by Wind Erosion in Farmland Worldwide from 2017 to 2021," Agriculture, MDPI, vol. 13(4), pages 1-15, March.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0263962. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.