The process of an oil refinery contains both discrete event and continuous variables and can be characterized as a hybrid system. It is extremely challenging to schedule such a system. The short-term scheduling problem of crude oil operations addressed in this chapter is one of the most difficult parts. With jobs to be scheduled being unknown at the beginning, heuristics and meta-heuristics are unable to be applied. Thus, by the existing methods, this problem is formulated as a mathematical programming problem and solved by using exact methods. However, because it is NP-hard in nature, mathematical programming is not computationally efficient and cannot be applied in practice. Up to now, there is no software designed to this problem. In this chapter, for the first time, the problem is studied in a control theory perspective. The problem is modeled by a type of hybrid Petri nets. Based on the model, a two-level control architecture is presented. At the lower level, it solves the schedulability and detailed scheduling problem in a hybrid control theory perspective. At the upper level, it solves a refining scheduling problem, a relative simple problem, with the schedulability conditions as constraints. Consequently, it results in a breakthrough solution such that the large practical application problem can be solved.