The upgrading operations in the Oil Sands are a key asset to Canadas economy since they currently process more than 60% of the crude bitumen extracted from this region. Despite their significance and relevance, mathematical tools that can evaluate the infrastructure and economy of the upgraders operations under fluctuations and variability in key operational and economic factors are limited. It is the purpose of this study to present a stochastic optimization model that has been developed to specify the optimal infrastructure that may be required by the Oil Sands upgraders to satisfy the projected production demands at minimum cost in the presence of uncertainty in key economic and operational parameters. A multiscenario approach, describing the potential realizations in the uncertain parameters affecting the upgrading operations, is employed in this work to identify the upgraders infrastructure that can simultaneously accommodate the projected production demands and the uncertainty in the systems parameters. A case study featuring the upgrading operations for year 2035 under uncertainty in key economic and operational factors is presented. The results show significant variability in the upgraders infrastructure, and their corresponding energy costs, when this system is evaluated under different uncertain scenarios.