An optimization based strategy for crude selection in a refinery with lube hydro-processing

Abstract

An optimization-based strategy is developed for crude selection in a refinery with lube base oil (LBO) producing capability. Crude oil is classified into five types based on the viscosity index (VI) and the compositional aspect of vacuum gas oil (VGO). A prediction model for the VI, the most important quality variable in LBO processing, is developed for VGO based on its bulk properties. For each crude type, prediction models for the yield and the VI change vs. the conversion rate during lube hydro-processing are developed. The lube hydro-processing models are then incorporated into the overall refinery optimization to maximize the overall margin while satisfying all the specifications of the lube and fuel products simultaneously. A case study involving several price scenarios illustrates the benefits from using the model-based optimization method for deciding crude procurement, the grade of the LBO to be produced, and the conversion rate in the lube process.