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.

针对具有润滑油基础油（LBO）生产能力的精炼厂，针对原油的选择开发了基于优化的策略。根据粘度指数（VI）和真空瓦斯油（VGO）的成分，原油分为五类。基于体积特性，为VGO开发了VI（LBO处理中最重要的质量变量）的预测模型。对于每种原油，都建立了润滑油加氢处理过程中产率和VI变化与转化率的预测模型。然后将润滑油加氢处理模型合并到整个炼油厂优化中，以最大程度地提高总利润，同时满足润滑油和燃料产品的所有规格。