This paper presents a new approach developed for high-level scoping analysis, forecasting and scheduling of CO2 EOR projects for multiple reservoirs and fields. The approach utilizes available reservoir simulation, analytical predictions and analog data on a full-field scale and approximates them with analytical functions. This allows for very fast forecasting of oil and CO2 production rates and determines the requirements for make-up CO2 under different potential development scenarios, including piloting phases. Built in MicrosoftTM Excel with VBA code and an advanced solver add-in, this scheduling tool enables the timely use of probabilistic Monte Carlo simulation for estimating the impact of uncertain input parameters on CO2 flood performance from multiple reservoirs. A numerical optimization algorithm searches for the best development schedule by optimizing the start-up times for a number of planned CO2 injection projects subject to allowable oil rate and CO2 supply constraints. Another optimization algorithm matches the estimated CO2 demand with supply from multiple natural and industrial sources and predicts the best time to commission CO2 capture facilities, thus maximizing CO2 utilization by EOR schemes rather than disposing it in depleted reservoirs or saline aquifers.