FUZZY LOGIC-BASED QUANTITATIVE RISK ASSESSMENT MODEL FOR HEALTH SAFETY AND ENVIRONMENT IN OIL AND GAS INDUSTRY

Several approaches of risk assessment process like; qualitative, quantitative and semi-quantitative approaches are used to mitigate the risk level of hazards. Typically, in oil and gas industry, the qualitative risk matrix is applied for evaluating the risk assessment of hazards related to health, safety, and environment (HSE). The existing qualitative risk matrix process may increase the uncertainty to select the critical factors of HSE categories; People, Environment, Asset, and Reputation. In order to overcome this uncertainty, a better approach needs to be developed. The objective of this research is to develop a Fuzzy Logic-Based Quantitative Risk Assessment (FLQRA) model to assess HSE risks more accurately. In this model, decision makers (experts) provide their preference of risk assessment information for severity of consequence and likelihood of HSE categories in numerical scaling. Then the Fuzzy Logic method is used to evaluate the risk level with the combination of consequence and likelihood associated to each category. To develop the model different type of Fuzzy Inference methods; Mamdani and Sugeno Inference System and different types of membership functions are used to generate the results and are compared with the existing method results.