Accident modeling and risk assessment framework for safety critical decision-making: application to deepwater drilling operation

Samith Rathnayaka, Faisal Khan and Paul Amayotte

Journal of Risk and Reliability, 2013, vol. 227, issue 1, 86-105

Abstract: Rising global energy demand is encouraging oil companies to invest in deepwater drilling. However, there are numerous engineering and safety challenges involved in this activity. The BP Deepwater Horizon accident (Macondo well blowout) has raised serious concerns about the safety of deepwater drilling. The major reasons for such a catastrophic blowout event are the lack of continuous assessment of risk and the lack of risk-based decision making to take timely and adequate preventive actions. The present work proposes an accident modeling and risk assessment framework based on accident precursors (early warnings). This framework uses the system hazard identification, prediction and prevention methodology to model the unwanted situation. The proposed risk assessment framework generates results that can be used to: (1) analyze the dynamic performance of safety barriers, (2) analyze the probability of occurrence of different severity levels, (3) analyze the dynamic risk profile of different severity levels and the aggregated risk profile, and (4) help to make safety-critical decisions based on aggregated risk profile. The present work provides an assessment of offshore deepwater drilling risk assessment and a basis to make timely and precise safety critical decisions. The risk assessment methodology is demonstrated on the Macondo well blowout accident. This case study highlighted the applicability and advantages of using the proposed method in drilling operations.

Keywords: Deepwater drilling; Macondo well blowout; system hazard identification; prediction and prevention accident model; safety barriers; aggregated risk profile (search for similar items in EconPapers)
Date: 2013
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Persistent link: https://EconPapers.repec.org/RePEc:sae:risrel:v:227:y:2013:i:1:p:86-105

DOI: 10.1177/1748006X12472158

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