Date of Original Version
Abstract or Table of Contents
Large reductions in carbon dioxide (CO2) emissions are needed to mitigate the impacts of climate change. One method of achieving such reductions is CO2 capture and storage (CCS). CCS requires the capture of carbon dioxide (CO2) at a large industrial facility, such as a power plant, and its transport to a geological storage site where CO2 is sequestered. If implemented, CCS could allow fossil fuels to be used with little or no CO2emissions until alternative energy sources are more widely deployed. Large volumes of CO2 are most efficiently transported by pipeline and stored either in deep saline aquifers or in oil reservoirs, where CO2 is used for enhanced oil recovery (EOR). This thesis describes a suite of models developed to estimate the project-specific cost of CO2 transport and storage. Engineering-economic models of pipeline CO2 transport, CO2-flood EOR, and aquifer storage were developed for this purpose. The models incorporate a probabilistic analysis capability that is used to quantify the sensitivity of transport and storage cost to variability and uncertainty in the model input parameters. The cost of CO2 pipeline transport is shown to be sensitive to the region of construction, in addition to factors such as the length and design capacity of the pipeline. The cost of CO2 storage in saline aquifers is shown to be most sensitive to factors affecting site characterization cost. For EOR projects, CO2 storage has traditionally been a secondary effect of oil recovery; thus, a levelized cost of CO2 storage cannot be defined. Instead EOR projects were evaluated based on the breakeven price of CO2 (i.e., the price of CO2 at which the project net present value is zero). The breakeven CO2 price is shown to be most sensitive to oil prices, losses of CO2 outside the productive zone of the reservoir, and reservoir pressure. Future research should include collection and aggregation of more specific data characterizing possible sites for aquifer storage and applications of these models to this data. The implications of alternative regulations and requirements for site characterization should also be studied to more fully assess cost impacts.