Identification of Safe Assembly Points in Emergencies in a Gas Refinery of the South Pars Gas Complex Using Fuzzy Logic Model

  INTRODUCTION: Crisis management is of critical importance in the oil and gas industries due to the increasing occurrence of accidents in these areas. One of the most important issues regarding crisis management in such industries is the identification of safety assembly points where employees should gather in emergencies. This study aimed to identify the safe points in a refinery using geographic information system (GIS) and fuzzy logic for emergency assembly. METHODS: Regarding the aim of the study purpose, the required data were collected, and a focus group meeting was held with experts to determine the criteria influencing the safety point zoning as well as high-risk units using the HAZOP method. After the identification of the criteria and sub-criteria affecting the zoning, the weight of each zoning parameter was calculated, and the safety zones were determined using the fuzzy logic model and its operators in the GIS environment. FINDINGS: According to the results of the risk assessment, the criteria and sub-criteria affecting zoning were divided into three categories of inconsistent (layer weight: 0.740), consistent (layer weight: 0.094), and access to exit routes (layer weight: 0.167). Moreover, the map results based on the fuzzy logic model revealed three safe points, including the vicinity of the fire station, clinic, and wastewater treatment plant in this refinery where the employees should gather in the event of emergencies. CONCLUSION: The results of this study showed that the selection of appropriate criteria in safe point zoning is of great importance in the emergencies in the industries. Moreover, an initial risk assessment can be effective in determining these criteria and sub-criteria. In addition, the fuzzy logic model has high accuracy and precision in determining the appropriate safe places.

Keywords:

Emergencies , Fuzzy Logic Model , Gas Refinery , Safe Point Zoning , Emergencies , Fuzzy Logic Model , Gas Refinery , Safe Point Zoning