The major accident risk (MAR) process - developing the profile of major accident risk for a large multi national oil company

2009 ◽  
Vol 87 (1) ◽  
pp. 59-63 ◽  
Author(s):  
M. Considine ◽  
S.M. Hall
Keyword(s):  
Accident Risk ◽  
Major Accident ◽  
Oil Company

Self-Verification Program in bp: Success Story of Major Accident Risk Management via Bowtie Barrier Model

2021 ◽  
pp. 1-13
Author(s):  
Roman Bulgachev ◽  
Michael Cromarty ◽  
Lee Milburn ◽  
Kevan Davies
Keyword(s):  
Risk Management ◽  
Risk Function ◽  
Lessons Learned ◽  
Management Tool ◽  
Accident Risk ◽  
Component Level ◽  
Holistic View ◽  
Operational Risks ◽  
Program Evolution ◽  
Major Accident

Summary bp’s (“the company’s”) wells organization manages its operational risks through what is known as the “three lines of defense” model. This is a three-tiered approach; the first line of defense is self-verification, which wells assets apply to prevent or mitigate operational risks. The second line of defense is conducted by the safety and operational risk function using deep technical expertise. The third line of defense is provided by group audit. In this paper, we discuss the wells self-verification program evolution from its first implementation and share case studies, results, impact, lessons learned, and further steps planned as part of the continuous improvement cycle. The company’s wells organization identified nine major accident risks that have the potential to result in significant health, safety, and environment (HSE) impacts. Examples include loss of well control (LoWC), offshore vessel collision, and dropped objects. The central risk team developed bowties for these risks, with prevention barriers on cause legs and mitigation barriers on consequence legs. Detailed risk bowties are fundamental to wells self-verification, adding technical depth to allow more focused verification to be performed when compared with the original bowties, because verification is now conducted using checklists targeting barriers at their component level, defined as critical tasks and equipment. Barriers are underpinned by barrier enablers (underlying supporting systems and processes) such as control of work, safe operating limits, inspection and maintenance, etc. Checklists are standardized and are available through a single, global digital application. This permits the verifiers, typically wellsite leaders, to conduct meaningful verification conversations, record the resulting actions, track them to closure within the application, and gain a better understanding of any cumulative impacts, ineffective barriers, and areas to focus on. Self-verification results are reviewed at rig, region, wells, and upstream levels. Rigs and regions analyze barrier effectiveness and gaps and implement corrective actions with contractors at the rig or region level. Global insights are collated monthly and presented centrally to wells leadership. Common themes and valuable learnings are then addressed at the functional level, shared across the organization, or escalated by the leadership. The self-verification program at the barrier component level proved to be an effective risk management tool for the company’s wells organization. It helps to continuously identify risks, address gaps, and learn from them. Recorded assessments not only provide the wells organization with barrier performance data but also highlight opportunities to improve. Leadership uses the results from barrier verification to gain a holistic view of how major accident risks are managed. Program evolution has also eliminated duplicate reviews, improved clarity of barrier components, and improved sustainability through applying a systematic approach, standardization, digitization, and procedural discipline.

Collective Knowledge for Industrial Disaster Prevention

2017 ◽  
Author(s):  
Sarah Maslen
Keyword(s):  
Risk Management ◽  
Organizational Performance ◽  
Oil And Gas ◽  
Economic Value ◽  
Gas Production ◽  
Accident Risk ◽  
Disaster Prevention ◽  
Information And Communications Technologies ◽  
Industrial Disaster ◽  
Major Accident

Since the 1990s there has been an increasing interest in knowledge, knowledge management, and the knowledge economy due to recognition of its economic value. Processes of globalization and developments in information and communications technologies have triggered transformations in the ways in which knowledge is shared, produced, and used to the extent that the 21st century was forecasted to be the knowledge century. Organizational learning has also been accepted as critical for organizational performance. A key question that has emerged is how knowledge can be “captured” by organizations. This focus on knowledge and learning demands an engagement with what knowledge means, where it comes from, and how it is affected by and used in different contexts. An inclusive definition is to say that knowledge is acquired theoretical, practical, embodied, and intuitive understandings of a situation. Knowledge is also located socially, geographically, organizationally, and it is specialized; so it is important to examine knowledge in less abstract terms. The specific case engaged with in this article is knowledge in hazardous industry and its role in industrial disaster prevention. In hazardous industries such as oil and gas production, learning and expertise are identified as critical ingredients for disaster prevention. Conversely, a lack of expertise or failure to learn has been implicated in disaster causation. The knowledge needs for major accident risk management are unique. Trial-and-error learning is dangerously inefficient because disasters must be prevented before they occur. The temporal, geographical, and social scale of decisions in complex sociotechnical systems means that this cannot only be a question of an individual’s expertise, but major accident risk management requires that knowledge is shared across a much larger group of people. Put another way, in this context knowledge needs to be collective. Incident reporting systems are a common solution, and organizations and industries as a whole put substantial effort into gathering information about past small failures and their causes in an attempt to learn how to prevent more serious events. However, these systems often fall short of their stated goals. This is because knowledge is not collective by virtue of being collected and stored. Rather, collective knowing is done in the context of social groups and it relies on processes of sensemaking.

A Framework Addressing Major Accident Risk in the Maritime Industry

2015 ◽  
Author(s):  
Ole C. Astrup ◽  
Anne M. Wahlstrøm ◽  
Tobias King
Keyword(s):  
Occupational Accidents ◽  
Accident Risk ◽  
Maritime Industry ◽  
Gas Industry ◽  
Lost Time ◽  
Major Accident ◽  
Industry Needs ◽  
The Impact ◽  
Incident Rates ◽  
Common Misunderstanding

Avoiding accidents and ensuring the safety of on-board personnel represents one of the most complex challenges faced by the maritime industry. A common misunderstanding in the industry has led to a focus on occupational accidents to reduce lost time injuries in the belief that this would also lead to a reduction of major accidents. The complexity related to preventing and mitigating major accidents requires an understanding of the differences in occupational risk compared to major accident risk. An ever increasing complexity in systems and operations calls for increased vigilance with regards to safety. Rather than focusing on individual components, the industry would benefit by embracing a more comprehensive approach to safety, one that establishes effective barriers that prevent or mitigate the impact of accidents. The oil & gas industry has a long experience in handling complex operations and major accident hazards and offshore vessels can document significant lower incident rates than conventional merchant vessels. Introducing the concept of barrier management from the oil & gas industry to the maritime industry can provide the framework this industry needs to better manage major accident hazards.

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