Uncertainties arise from several sources and may introduce diverse risks within the oil supply chain (OSC), hindering its management, besides raising costs and lowering margins. The purpose of this work is to present a new stochastic approach to deal with different sources of uncertainty, by correlating the uncertainties through a probability tree diagram along with a scenario tree approach, and then applying the outputs into a multistage stochastic programming model that defines the tactical planning for the downstream OSC. Scenario reduction algorithms are used for generating smaller subsets of scenarios and reduce the problem complexity. An example based on the Portuguese OSC is used to illustrate the application of the new methodology. The results show that the proposed approach not only presents a great performance with respect to the operational and financial indicators, but also is able to accommodate the risks arising from unstable market conditions.