Abstract
Abstract Blowout is one of the most serious accidents in the drilling process of hydrogen sulfide (H2S) oil and gas wells, often accompanied by the leakage of H2S and other toxic gases, which easily causes casualties and huge economic and environmental losses. Therefore, this article uses DEMATEL and ISM hybrid algorithms to establish a blowout accident-causing network model for oil and gas wells with H2S content, thus strengthening the risk management. In this model, firstly, the general causative factors of blowout accidents are extracted by accident statistics. Secondly, expert knowledge is adopted to determine the correlation matrix among factors. Thirdly, based on the DEMATEL algorithm, the degree of the relationship among the factors is analyzed. The importance degree (centrality) of each factor and its status as well as role (causality) in the accident-causing system are given. Finally, the ISM algorithm is used to classify the factors and establish an accident-causing network diagram with hierarchical relationship. The proposed model has been applied in a gas field containing H2S in East Sichuan, China. The results show that causative factors of blowout accidents can be divided into cause group and effect group according to the influence relationship among them. The cause group implies the meaning of the causative factors, and the effect group denotes the meaning of the causative factors. Hence, it would be necessary to control and pay great attention to the cause group factors beforehand. The key causative factors of blowout accidents are geological exploration technology, safety monitoring facilities and on-site safety culture, which belong to the cause group and are at the basic level of the accident-causing network diagram. This model has provided effective decision-making guidance for HSE work in gas field and reduced the incidence of blowout accidents. This model uses a combination of qualitative and quantitative methods to analyze the causes of blowout accidents, not only considering the relationships between factors and accidents, but also considering the relationships between factors and factors. As a result, it provides decision-making basis for the prevention and control of blowout accidents in H2S oil and gas wells.
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