Abstract
Dynamic risk analysis (DRA) is a novel industrial approach that aims to capture changes in operational conditions over time and quantify their effect on risk. This aspect may be advantageous for providing insight into the causal factors that have substantial risk contributions and supporting decisions related to risk control. Some DRA methods were developed by the oil and gas industry to support the integration of work processes and the cooperation across virtual clusters, e.g., between offshore and onshore systems and/or oil company and supplier. However, DRA has not been extensively adopted and limited attention is given to its validity in practical applications. The objective of this article is to illustrate how this validity can be established based on common validation approaches for risk analysis. The case study focuses on a DRA method named risk barometer that was developed to support integrated operations across the oil and gas industrial systems. The outcome of this study may serve as a basis for the validation of other DRA methods, the use of DRA in practical cases, and ultimately the achievement of integrated operations (IO) capabilities.
Highlights
Quantitative risk assessment (QRA) has been extensively employed in the design phase of hazardous process facilities to ensure compliance with safety requirements
An advanced approach to support the validation of Dynamic risk analysis (DRA) techniques dedicated to the process industry was illustrated
The validation approach relies on three parallel strategies: (i) Reality check, (ii) benchmark, and (iii) peer review
Summary
Quantitative risk assessment (QRA) has been extensively employed in the design phase of hazardous process facilities to ensure compliance with safety requirements. These requirements may be defined as acceptance criteria that express a tolerable risk level. The risk models applied to the design phase QRAs are suitable for reflecting the technical design of an installation. These models, have a limited focus on changes in the operating and environmental conditions and their potential impact on risk. Appropriate validation for DRA is still an unexplored domain For this reason, this study aims to suggest a set of relevant approaches
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