Extending a model of loss seismic risk resulting from production interrupt at gas refinery units (case study: Parsian Gas Refinery)

Predicting monetary loss models due to production interrupt caused by an earthquake in industrial units is an important tool in making intelligent management decision. This study aims to extend a loss seismic risk model for the aforementioned subject. Production interruption in large industrial units after the earthquake is the cause of significant economic losses. The decline in revenues is the short-term consequence of this production interruption, and the market share loss is the long-term consequence of the earthquake. Earthquake “parametric insurance” offers a promising perspective to overcome this challenge ahead. Parametric insurance is a type of insurance in which the criteria for compensating payments exceed the event intensity parameters of the specified limit. The present method can be used for designing parametric insurance mechanisms to transfer the subsequent risk caused by an earthquake to the insurer. The Parsian gas refinery complex was investigated as a case study located in Zagros, a seismic-prone area in southern Iran. By means of a well-known seismic hazard model and using OQ software, a 50,000-year-old synthetic catalogue for the study area, Parsian Gas Refinery, was developed using the Monte Carlo simulation method. For this purpose, four ground motion models with different weights were applied in the EMME model to predict the resulting ground motions. Seismic source models and ground motion models were considered as inputs to the Open Quake (OQ) platform, and the event-based hazard analysis module was used. The whole gas refinery system was divided into 10 separate production paths and key components were specified in each path. The compatible fragility functions, as well as the restoration functions, based on HAZUS were assigned to different components in each production path and combined with the expected monetary loss related to daily interruption in that path. As a result, a prediction risk model for monetary loss was obtained for the entire refinery as a function of each arbitrary earthquake scenario.