Generalized Net Model of the Crude Oil Selection Process in an Oil Refinery

Abstract

Petroleum refining is of great importance for the global energy and chemical industries. It provides fuels and raw materials that are needed for transportation, energy and chemical industry. The cost of purchasing crude oil is the main part of refining costs – often exceeding 90%. Therefore, the selection of appropriate feedstocks is crucial for overall profitability. Processing cheaper “opportunistic feedstocks” can have a strong positive impact on the economics of an individual refinery, but it is also associated with serious operational challenges that arise from higher levels of contaminants such as asphaltenes, metals and naphthenic acids. Therefore, optimizing the selection of crude oil is a key factor in achieving efficient and reliable refinery operation.

The current study employs the capabilities of intercriteria analysis and generalized net toolkit to model the process of crude oil selection for any refinery around the globe. The developed model, after its programmatic implementation, can be used to streamline and optimize the crude oil selection process for each refinery worldwide.