Providing a comprehensive approach to oil well blowout risk assessment.

Drilling is one of the most dangerous activities in the oil and gas process industries. Therefore, a holistic approach was presented to prevent and control risks and reduce the uncertainty of blowouts, kick scenarios, and control layers based on the Fuzzy Bayesian Network (FBN). Four independent protection layers (IPLs) were used to evaluate the blowout outcome, and the failure probabilities of IPL1 and IPL2 were calculated with Fault Tree Analysis (FTA). Then, different events were transferred to the Bayesian Network (BN) in GeNIe software, and updated the probabilities. The Fuzzy Fault Tree (FFT) results reveal that the failure probabilities for IPL1 and IPL2 amount to 8.94×10-4 and 4.97×10-21, respectively. Also, the blowout probability results based on FFT were larger than FBN. According to FBN, the probability of the kick event was equal to 6.60×10-34. Sensitivity analysis showed that X1 (Mud volume/flow change) had the highest degree of importance in the blowout of oil wells. The results of this study can be used in both a preventive and reactive approach. Deductive and inductive reasoning, the dynamic nature and conditional dependencies, and causal relationships between events can make the model more realistic.

Safety, health, and environmental risk assessment of the aromatic outlet of Imam Khomeini Petrochemical Company using LOPA and fuzzy-LOPA and pollutants and control actions using the Bow-tie method.

Background: Today, with the development of the industry, the occurrence of accidents caused by the release and explosion of chemical and toxic substances in industrial units has increased, and these accidents sometimes cause irreparable damage to human life and the environment. According to a study by the American Petroleum Institute, of the recent major accidents in the last 30 years, 44% are related to machinery failure and 12% are caused by unknown factors and lack of information. Therefore, equipment risk control is aimed at preventing large and dangerous accident. The present study, the performance of LOPA and fuzzy-LOPA methods was compared toward the risk assessment of Imam Khomeini Petrochemical Company under certainty and uncertainty of data. This comparison was done in order to a conceptual method with high certainty to assess high-level hazards leading to health and safety risks and environmental pollution. Methods: First, the health, safety hazards and environmental aspects were identified via the HAZOP method. Then, a risk assessment was performed using the LOPA method. The fuzzification, severity, and likelihood of each risk were considered as an input variable and risk probability as an output variable. Finally, was the methods used in our analysis were compared and the Bow-tie software was used to draw a Bow-tie diagram to control and reduce the risks. Results: As a result, a total of 50 safety and health hazards and 37 environmental aspects were identified in the aromatic outlet of the studied company using the HAZOP method. The most critical risks identified were operational activities in feed and product tanks; flammable materials pumping; blocking the flare path; and releasing H2S gas. The results showed that the production of air pollutants in the power supply unit, disposal of waste from reactor tanks, disposal of waste from condensate tanks, and fire and explosion of the reactor are high-level environmental risks. Conclusion: In the conditions of uncertainty or the absence of information related to the probability and severity of the risk scenario, among the mentioned methods. The result showed that errors in the risk assessment were reduced to an acceptable extent by using Fuzzy LOPA method.