Quantitative risk analysis of offshore drilling operations: A Bayesian approach

Khakzad, Nima; Khan, Faisal; Amyotte, Paul

doi:10.1016/j.ssci.2013.01.022

Cited by 334 publications

(148 citation statements)

References 23 publications

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“…In the literature, important works are found on the construction of offshore wells, using risk analysis techniques, such as Bayesian network, fault tree, event tree and bow tie (Bhandari et al 2015;Khakzad et al 2013;Abimbola et al 2014). Such studies help to determine the probability of blowouts, facilitating the preventive and mitigating actions for undesired events.…”

Section: Eds State-of-the-art Surveymentioning

confidence: 99%

Integrated risk management: a Petrobras application in offshore well construction safety to minimize critical emergency disconnections

et al. 2018

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In order to avoid mistakes and to save a great deal of time in analysis, an innovative methodology was developed that can analyze the well operations and rig characteristics involved to define the best emergency disconnect sequence (EDS) available. A solution was developed based on the characteristics of the rigs and blowout preventers (BOPs), and six variables were considered that directly affect the choice of EDS. All possible combinations of 64 scenarios were analyzed, and the priority of choice of the EDS was defined empirically. This paper presents an approach to EDS risk management and examples of exposure time (time without riser safety margin and shear capability) for the same well, which can be lowered from 13% to 0.1%. The impact of this reduction is related to the ability of the BOP to cut some of the heavy casings, in addition to improved availability of EDS modes. This implementation opened up many possibilities for the performance of risk exposure analysis, enabling comparison of several BOP configurations of contracted rigs and selection of the best options. This innovative approach allowed a better management of the rig schedules, prioritizing safety aspects and making it possible to allocate the fleet in a systematic way.

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Section: Eds State-of-the-art Surveymentioning

confidence: 99%

Integrated risk management: a Petrobras application in offshore well construction safety to minimize critical emergency disconnections

et al. 2018

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“…Thus, the total risk is the sum of the risks of each transaction (Khakzad et al, 2013b), providing a more structured and accurate model (Carvalho & Chiann, 2013). These procedures underpin the formulation of the prior probability distribution on exposure to the occupational risk, which will be put to test in subsequent phases.…”

Section: Ordination Of Data (Od)mentioning

confidence: 99%

“…Two softwares have been used more, the Netica Bayesian Network (Norsys Software Corporation, 2007) and Hugin Researcher (Hugin Expert, 2014). However, in spite of having powerful computational tools, it is worth noting that even with the use of learning through computer algorithms, the human perception is essential for a successful application of the BN in the analysis of occupational risk (Chen et al, 2009;García-Herrero et al, 2012a;Khakzad et al, 2013b).…”

Section: Model Construction (Mc)mentioning

confidence: 99%

Modeling Bayesian Networks from a conceptual framework for occupational risk analysis

Vieira

Silva

2017

Prod.

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“…Moreover, dynamic risk assessment methods were developed in order to evaluate the risk by updating initial failure probabilities of events (causes) and safety barriers as new information are made available during a specific operation [20]. However, the mentioned techniques are not widely applied in the common O&G offshore practice due to several reasons, among which their complexity has a primary role.…”

Section: Introductionmentioning

confidence: 99%

Real-Time Data for Risk Assessment in the Offshore Oil and Gas Industry

Paltrinieri

Landucci

Rossi

2017

Volume 3B: Structures, Safety and Reliability

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Recent major accidents in the offshore oil and gas (O&G) industry have showed inadequate assessment of system risk and demonstrated the need to improve risk analysis. While direct causes often differ, the failure to update risk evaluation on the basis of system changes/modifications has been a recurring problem. Risk is traditionally defined as a measure of the accident likelihood and the magnitude of loss, usually assessed as damage to people, to the environment, and/or economic loss. Recent revisions of such definition include also aspects of uncertainty. However, Quantitative Risk Assessment (QRA) in the offshore O&G industry is based on consolidated procedures and methods, where periodic evaluation and update of risk is not commonly carried out. Several methodologies were recently developed for dynamic risk analysis of the offshore O&G industry. Dynamic fault trees, Markov chain models for the lifecycle analysis, and Weibull failure analysis may be used for dynamic frequency evaluation and risk assessment update. Moreover, dynamic risk assessment methods were developed in order to evaluate the risk by updating initial failure probabilities of events (causes) and safety barriers as new information are made available. However, the mentioned techniques are not widely applied in the common O&G offshore practice due to several reasons, among which their complexity has a primary role. More intuitive approaches focusing on a selected number of critical factors have also been suggested, such as the Risk Barometer or the TEC2O. Such techniques are based on the evaluation of technical, operational and organizational factors. The methodology allows supporting periodic update of QRA by collecting and aggregating a set of indicators. However, their effectiveness relies on continuous monitoring activity and realtime data capturing. For this reason, this contribution focuses on the coupling of such methods with sensors of different nature located in or around and offshore O&G system. The inheritance from the Centre for Integrated Operations in the Petroleum Industries represents the basis of such study. Such approach may be beneficial for several cases in which (quasi) real-time risk evaluation may support critical operations. Two representative cases have been described: i) erosion and corrosion issues due to sand production; and ii) oil production in environmental sensitive areas. In both the cases, dynamic risk analysis may employ real-time data provided by sand, corrosion and leak detectors. A simulation of dynamic risk analysis has demonstrated how the variation of such data can affect the overall risk picture. In fact, this risk assessment approach has not only the capability to continuously iterate and outline improved system risk pictures, but it can also compare its results with sensor-measured data and allow for calibration. This can potentially guarantee progressive improvement of the method reliability for appropriate support to safety-critical decisions. Direct causes of such events often differed, but...

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Quantitative risk analysis of offshore drilling operations: A Bayesian approach

Cited by 334 publications

References 23 publications

Integrated risk management: a Petrobras application in offshore well construction safety to minimize critical emergency disconnections

Integrated risk management: a Petrobras application in offshore well construction safety to minimize critical emergency disconnections

Modeling Bayesian Networks from a conceptual framework for occupational risk analysis

Real-Time Data for Risk Assessment in the Offshore Oil and Gas Industry

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