Modeling Human and Organizational Factors for Operational Risk Analysis
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In terms of accident sequences in the offshore oil and gas industry, technical factors have beenfocused on the risk analysis area widely. However, there are still accidents and losses occurredfrequently. To understand the impact of other factors on accident sequences, this thesis focuseson human and organizational factors instead of technical factors. The aimis to provide readersa method about how to model human and organizational factors of offshore lifting operationby a case study. Firstly, the risk model consists of Event Tree, Fault Tree and Bayesian network.Then, to measure the risk influence factors in the model, potential indicators are identified byresearching the literature information. Next, there is a comparison and evaluation about howto model non-linear effects by Barrier and Operational Risk Analysis and Bayesian conditionalprobability. We predict that the Bayesian method is a more correct way to model non-lineareffects. However, regardless of which method, the biggest challenge is how to obtain availabledatasets since there is no suitable datasets covering human and organizational factors. Thus,the further work will still focus on collecting reliable datasets.