Frequency data and modification factors used in QRA studies

Pitblado, Robin; Bain, Brian; Falck, Andreas; Litland, Kjellaug; Spitzenberger, Cynthia

doi:10.1016/j.jlp.2010.09.009

Cited by 24 publications

(16 citation statements)

References 3 publications

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“…The method is suitable for implementation in dynamic risk assessments to provide an update mechanism that allows revision of accident frequency during the lifecycle of an installation. This work also compares TEC20 with other relevant methods for frequency tailoring, such as: CCPS Method (Center of Chemical Process Safety, 2000) based on arbitrary expert judgment evaluation; API 581 Method (American Petroleum Institute, 2000), which is based on the determination of equipment and management modification factors obtained from design data and site inspection; MANAGER (Pitblado, Williams, & Slater, 1990) which is based on the determination of a management modification factor obtained from site inspection, implicitly covering technical aspects; and DNV (Pitblado, Bain, Falck, Litland, & Spitzenberger, 2011) which is based on scoring safety barriers, obtaining frequency reduction factors, and implicitly covering managerial aspects.…”

Section: Review Of Offshore Qra Methodsmentioning

confidence: 99%

Accident Precursor Probabilistic Method (APPM) for modeling and assessing risk of offshore drilling blowouts – A theoretical micro-scale application

Perez

Tan

2018

Safety Science

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This paper proposes and explains the application of an accident precursor probabilistic method (APPM) that aims to overcome the usual limitations of existing quantitative risk analyses (QRA), with a focus on offshore drilling blowouts. This limitation is implicit in generic QRAs that do not appropriately reflect the specificities of the rig and its environment, without considering systems arrangements, risk influencing factors (RIF) or current operational conditions. The proposed method is divided into three pillars: (i) a guideline for modeling the blowout probability considering specific conditions or well, rig, safety barriers and risk influencing factors (RIF) objectives; (ii) a proposed axiom combined with a scoring system to quantify the RIF into the QRA; and (iii) a risk based plan framework, to allow risk update and sequential learning during the operational phase. The APPM is based on a Bayesian Network (BN) mathematical framework. It allows the pre-defined axiom to be entered into a conditional probability table (CPT). This approach, combined with the assessment of the company's safety management system, allows the incorporation of RIF into the QRA. The developed APPM is applied to a theoretical micro-scale calculation. The result demonstrates its suitability for addressing common aspects inherent to the blowout phenomenon, including uncertainty, dependability between variables (common cause factors and redundant failures), and dynamism due to planned or unplanned operational changes in systems, drilling parameters and current conditions of RIF. Limitations of the APPM are also identified, and suggestions are made for future work on this topic.

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Section: Review Of Offshore Qra Methodsmentioning

confidence: 99%

Accident Precursor Probabilistic Method (APPM) for modeling and assessing risk of offshore drilling blowouts – A theoretical micro-scale application

Perez

Tan

2018

Safety Science

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“…Auditing management quality 118 and how to allow for the effect of its results on failure rates 119 was tackled in the ARAMIS project and later discussed by Pitblado et al 120 In Chapters 6 and 7, we shall return to this particular subject with some new insights on human reliability, the influence of management on it, and the effect of dynamic interactions of humans with plant installations. Auditing management quality 118 and how to allow for the effect of its results on failure rates 119 was tackled in the ARAMIS project and later discussed by Pitblado et al 120 In Chapters 6 and 7, we shall return to this particular subject with some new insights on human reliability, the influence of management on it, and the effect of dynamic interactions of humans with plant installations.…”

Section: Step 3 Quantification Of Probability Of Events Failure Ratesmentioning

confidence: 99%

Loss Prevention History and Developed Methods and Tools

Pasman¹

2015

Risk Analysis and Control for Industrial Processes - Gas, Oil and Chemicals

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Section: Introductionmentioning

confidence: 99%

“…Frequency modification factors address site-specific elements related to the facility under review [13,21] and may be updated in (quasi) real-time. The Risk Barometer is a representative example of such approach [22][23][24].…”

Section: Introductionmentioning

confidence: 99%

“…Periodic evaluation and update of risk is not commonly carried out. This leads to static risk estimation in a frozen instant of the system life, without capturing the variation of risks due to operation or changes during the lifecycle of a production plant [12][13][14].International standards (e.g. ISO 31000 on risk management [7] and NORSOK z-013 on risk and emergency preparedness analysis [15]) suggest updates of risk analysis in conjunction with major changes in the plant or organization or every five years.…”

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confidence: 99%

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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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Frequency data and modification factors used in QRA studies

Cited by 24 publications

References 3 publications

Accident Precursor Probabilistic Method (APPM) for modeling and assessing risk of offshore drilling blowouts – A theoretical micro-scale application

Accident Precursor Probabilistic Method (APPM) for modeling and assessing risk of offshore drilling blowouts – A theoretical micro-scale application

Loss Prevention History and Developed Methods and Tools

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

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