(106b) Human Reliability Analysis for Oil and Gas Operations: Analysis of Existing Methods

Quantitative Risk Analysis (QRA) has been one of the main tools for risk management in the petroleum industry,. QRAs differ on the extent to which they incorporate human and organizational factors. To date, QRA has mostly focused on technical barriers, despite many accidents having human failure as a primary cause or a contributing factor. Human Reliability Analysis (HRA) allows for the assessment of the human contribution to risk to be assessed, both qualitatively and quantitatively. HRA identifies, models, and quantifies human failure events (HFE) in the context of various accident scenarios. Such analyses can, in turn, form the basis for prioritizing and developing effective safeguards to prevent or reduce the likelihood of human caused accidents.

To date there is no generally accepted requirement for HRA in QRAs in the petroleum sector, and there is a lack of research on how to apply HRA in the petroleum industry. In addition, most credible and highly advanced HRA methods have largely been developed and applied in support of nuclear power plants control room operations and in the context of probabilistic risk analysis. They may, thus, not reflect the particularities of the petroleum industry regarding interactions between the crew and the systems, possible operator errors, and contextual factors.

Moreover, many of the HRA methods have issues that have led to inconsistencies, insufficient traceability and reproducibility in both the qualitative and quantitative aspects. These issues have even greater relevance because they cause (i) significant variability in the results seen in the application of different HRA methods, and (ii) significant variability in cases where different HRA analysts apply the same method.

Given the need to assess human error in the context of the oil industry, it is necessary to evaluate available HRA methodologies and asses its applicability to petroleum operations. Furthermore, it is fundamental to assess these methods against good practices of HRA. This paper accomplishes this by analyzing nine HRA methods. The assessment of the methods was performed in two stages. The first stage consisted of an initial screening, in which we selected five attributes that are desirable in an HRA method and evaluated if and how they were presented in the analyzed methods. The methods were also evaluated regarding the level of adaptations that would be required to be tailored for Oil and Gas operations. The methods that presented a higher ranking in the first stage are thus the ones that i) present HRA desirable attributes at an adequate level ; ii) have a high potential for applications to Oil and Gas operations. The methods with the higher rankings from Stage 1 were assessed against the attributes that are necessary for a robust HRA method, in Stage 2. This paper provides the results of the investigation.