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Background and Objective: The development of oil and gas extraction industry involve a number of risks, including environmental pollution and the loss of human resources and material assets. Blowout is one of the most significant and costly risks in the oil and gas drilling industry, which could have severe consequences, such as explosion, human fatality, and environmental disasters. Risk assessment is one of the most important tools for designing the measures targeted toward risk reduction and safety enhancement in this industry. Regarding this, the aim of the present study was to identify and analyze the basic causes of kick and blowout in the Iranian onshore exploratory drilling industry by using bow tie analysis and Bayesian network (BN). Materials and Methods: In this study, the identification and evaluation of the basic events leading to a kick was accomplished using the fault trees analysis (FTA). Furthermore, the event tree analysis (ETA) was employed to investigate the safety barriers to blowout and the possible consequences of a kick (e.g., blowout). The potential scenarios of the blowout incidence and the other consequences of a kick were determined through the integration of FTA and ETA by bow tie analysis. Finally, BN was constructed to investigate the blowout probability and other consequences of the incidence of a kick in the well. Results: The results of the study led to the identification of 24 basic events accounting for the incidence of a kick. The data also revealed seven safety barriers for the prevention of the kick incidence. The probability of kick and blowout was calculated as 9×10 and 3.5×10, respectively. Conclusion: According to the findings, entrance into the high pressure zone and reduction of bottom hole pressure were identified as the most important basic causes of a kick. Furthermore, the early detection of the kick and proper functioning of blowout preventer were recognized as the most important safety barriers to prevent the blowout.

Blow out risk analysis of oil and gas drilling operation in exploration wells using Bow tie analysis (BTA) and Bayesian network