Carbon capture and storage (CCS) is an impoitant technology option for reducing CO2 emissions into the atmosphere. The most commercially viable way to deploy CCS on a large scale is via coupling with enhanced oil recovery (EOR) operations. These operations allow the reduction of CO2 emissions through geological sequestration, coupled with generation of additional revenues through increased oil production as a result from CO2 re-injection through EOR. EOR also enables both CO2 utilization and storage (CCUS) as a carbon management strategy with long CO2 storage life. In practice, planning EOR operations takes into account mass balance and temporal aspects of a given site. When multiple oil reservoirs are involved, it is necessary to allocate the available CO2 supply and schedule suitable timing for EOR operations for these reservoirs. CO2 allocation and scheduling are thus important aspects in maximizing the economic benefits that arise from EOR operations. In this work, a mixed integer linear programming (MILP) model is developed to address CO2 allocation and scheduling issues for EOR operations. A discrete-time optimization approach is developed to consider both economic discounting and reservoir depletion. Two illustrative case studies are solved to illustrate the model. (C) 2016 Elsevier Ltd. All rights reserved.