A novel methodology to analyze accident path in deepwater drilling operation considering uncertain information

Meng, Xiangying; Li, Xinhong; Wang, Weigang; Song, Guozheng; Chen, Guo-Ming; Zhu, Jingyu

doi:10.1016/j.ress.2020.107255

Cited by 17 publications

(5 citation statements)

References 46 publications

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“…In high-reliability organizations, the SPAR-H method has been widely used due to its simplicity and practicability. SPAR-H was first used by U.S. nuclear power plants to assess HEPs [ 26 ], and is now also used in the petrochemical industry, such as the chemical plants [ 27 ], oil storage companies [ 28 ], and the deepwater drilling process [ 29 ]. Furthermore, Gould et al (2012) considered that SPAR-H was easier to use in comparison with other human risk analysis (HRA) models, such as HFACS [ 30 ].…”

Section: Literature Reviewmentioning

confidence: 99%

A Practical Risk-Based Model for Early Warning of Seafarer Errors Using Integrated Bayesian Network and SPAR-H

Zhang

Meng

Yang

et al. 2022

IJERPH

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Unsafe crew acts (UCAs) related to human errors are the main contributors to maritime accidents. The prediction of unsafe crew acts will provide an early warning for maritime accidents, which is significant to shipping companies. However, there exist gaps between the prediction models developed by researchers and those adopted by practitioners in human risk analysis (HRA) of the maritime industry. In addition, most research regarding human factors of maritime safety has concentrated on hazard identification or accident analysis, but not on early warning of UCAs. This paper proposes a Bayesian network (BN) version of the Standardized Plant Analysis Risk–Human Reliability Analysis (SPAR-H) method to predict the probability of seafarers’ unsafe acts. After the identification of performance-shaping factors (PSFs) that influence seafarers’ unsafe acts during navigation, the developed prediction model, which integrates the practicability of SPAR-H and the forward and backward inference functions of BN, is adopted to evaluate the probabilistic risk of unsafe acts and PSFs. The model can also be used when the available information is insufficient. Case studies demonstrate the practicability of the model in quantitatively predicting unsafe crew acts. The method allows evaluating whether a seafarer is capable of fulfilling their responsibility and providing an early warning for decision-makers, thereby avoiding human errors and sequentially preventing maritime accidents. The method can also be considered as a starting point for applying the efforts of HRA researchers to the real world for practitioners.

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Section: Literature Reviewmentioning

confidence: 99%

A Practical Risk-Based Model for Early Warning of Seafarer Errors Using Integrated Bayesian Network and SPAR-H

Zhang

Meng

Yang

et al. 2022

IJERPH

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“…The total economic cost to all companies affected and the Gulf Coast states is estimated at 144.98 billion US. 49 The technical failures leading to the disaster have been the subject of expert analyses and publications 50,51 and will not be elaborated here. Much of the earlier analysis points to the technical challenge of the undertaking: Macondo was an exploration well that was in the process of being temporarily abandoned so that a smaller rig could move in and complete it for production.…”

Section: ■ Communication Challenges In Contextmentioning

confidence: 99%

Listening to the Well, Listening to Each Other, and Listening to the Silence─New Safety Lessons from Deepwater Horizon

Espinoza-Gala

Jetter

Alibage

2021

ACS Chem. Health Saf.

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It is common for accident reports and the analysis of large-scale disasters, such as the Deepwater Horizon blowout, to point to communication failures. This narrow explanation implicitly assumes that accidents could be prevented if employees spoke up about safety. In contrast, the first author of this paper, whose professional experience is introduced in this Commentary to provide context, has frequently observed that there are, in fact, many cases when employees speak up but are not listened to. These patterns of communication (or lack thereof) occur at the intersection of personal, leadership, and organizational factors, which jointly affect how safety issues are recognized, communicated, and addressed. As such, communication problems are at "the tip of the iceberg" of safety problems, not at their root. In this paper, we review research on high-reliability organizations (HROs) with excellent safety records to identify their communication patterns and practices and how they contribute to the ability to enact five principles of HROs: preoccupation with failure, reluctance to simplify, deference to expertise, commitment to resilience, and sensitivity to operations. We then apply this lens to investigate the Deepwater Horizon disaster, based on court documents, expert reports, and personal interviews. Specifically, we investigate how the communication patterns between the onshore experts and the offshore crews compared to the recommendations of HRO theory and how existing discrepancies might help explain the accident. We found that many employees were aware of safety issues and communicated concerns openly, but there was little organizational response to the issues they raised. This failure to listen was largely owed to factors that were not directly related to communication, such as time pressure and lack of resources, and a culture that valued a "can do attitude" and getting things done so much that it got in the way of sensitivity to operations, expert-based guidance, and communication about problems. Moreover, the challenges of the project and its aggressive timeline created an extreme, almost toxic, commitment to resilience. Based on these findings, we discuss recommendations for improving safety in offshore oil and gas production.

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“…1 The BP Deepwater Horizon blowout accident happened in 2010, took away 11 lives, and caused serious environmental pollution. 2 Among all the fire types caused by oil leakage on offshore platforms, the probability of pool fires is the highest due to continuous handling of heavy hydrocarbons and large flammable liquid inventories. 3 An oil pool is formed due to the liquid fuel being released accidentally, which, after vaporizing and being ignited, causes the pool fire.…”

Section: Introductionmentioning

confidence: 99%

“…The accident remains the world's most serious offshore platform accident 1 . The BP Deepwater Horizon blowout accident happened in 2010, took away 11 lives, and caused serious environmental pollution 2 . Among all the fire types caused by oil leakage on offshore platforms, the probability of pool fires is the highest due to continuous handling of heavy hydrocarbons and large flammable liquid inventories 3 .…”

Section: Introductionmentioning

confidence: 99%

Modeling and risk analysis of large‐scale crude oil pool fire on an offshore facility

Wang,

Wang

et al. 2023

Process Safety Progress

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Large‐scale pool fires on offshore platforms can have disastrous consequences. Wind load is an essential component of the marine environment; hence, wind‐shielding facilities are installed on the platforms as needed. A computational fluid dynamics technique is used in this study to model large‐scale pool fires. The effects of wind load and windshields on large‐scale pool fires are investigated. Furthermore, the impact of the large‐scale pool fire on personnel is evaluated based on thermal radiation dose. It has been discovered that the growing horizontal momentum of the wind load might result in a significant distance of fatal injury. The windshields have double‐edged effects, including that: (1) they can reduce the injury distance by preventing the spread of fire products; and (2) they could block the release of heat and smoke. It is advised that while installing windshields on offshore platforms, different fire scenarios need to be considered. This research can be used to provide technical support for the development of the emergency evacuation strategy and layout design of offshore platforms.

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A novel methodology to analyze accident path in deepwater drilling operation considering uncertain information

Cited by 17 publications

References 46 publications

A Practical Risk-Based Model for Early Warning of Seafarer Errors Using Integrated Bayesian Network and SPAR-H

A Practical Risk-Based Model for Early Warning of Seafarer Errors Using Integrated Bayesian Network and SPAR-H

Listening to the Well, Listening to Each Other, and Listening to the Silence─New Safety Lessons from Deepwater Horizon

Modeling and risk analysis of large‐scale crude oil pool fire on an offshore facility

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