“Carbon capture” is the process of capturing carbon dioxide (CO₂) from large point sources such as power plants and industrial facilities. The captured CO₂ can be safely stored in underground structures to reduce greenhouse gas emissions, converted to renewable fuels, or utilized in industrial applications. While current research and federal investments in carbon capture have largely been based on its potential as a pollution control technology in the electric sector, “enhanced oil recovery” (EOR) is an industrial application using captured carbon. The EOR process, which involves injecting carbon dioxide underground to boost production, has proven to be more efficient when compared to conventional oil production. Large-scale deployment has been lacking to date but sustained government support for R&D investments and incentive mechanisms could help jumpstart “carbon capture utilization and storage” (CCUS) deployment in the US. Thus, an understanding of the impact of the level of R&D investments and other factors on CCUS deployment and its use with EOR are critical to help guide policy decisions to incentivize CCUS and EOR technology deployment in the US.  

NERA was engaged by the Carbon Utilization Research Council (CURC) and ClearPath Foundation to evaluate the potential deployment of carbon capture within the US power sector for use with EOR. NERA examined how reducing the cost of carbon capture via a research, development, and deployment (RD&D) program can enable new coal and natural gas power projects for use with EOR using its NewERA electricity sector model, a linear programming dispatch and long-term capacity planning model for the US electricity sector. A total of eight scenarios were developed structured around different assumptions regarding economic growth, fuel prices, and RD&D levels relating to carbon capture technology. For each of these scenarios, the study projected electric sector capacity and generation by technology, cumulative CO₂ delivered to various EOR basins, and state-level delivered electricity rates.

NERA added functionality to the model to better evaluate potential CCS deployment, while also representing EOR basin limits. These included:

• Multiple vintages of coal, combined cycle, coal with CCS, and combined cycle with CCS, with declining costs and heat rates over time.
• An adder on the costs of capital for new coal and combined cycle builds without CCS to simulate the risk of a new, uncontrolled unit becoming subject to carbon emission regulation during its useful life.
• “Post-combustion” carbon capture retrofits as an option to existing coal-fired generators in the model, with the cost and performance characteristics of the retrofit provided by CURC and ClearPath.
• A credit derived from CO₂ sales for EOR that was developed based on the crude oil price in the various scenarios and varying over time, and the inclusion of the section “45Q tax credit” for carbon capture projects in select years.
• Updated transport costs from states to EOR basins and annual, cumulative limits on CO₂ demand by EOR basin.

The two variables that dominate the deployment of carbon capture across the various scenarios analyzed are fuel prices and the existence of an aggressive RD&D program. For the scenarios analyzed with higher crude oil and natural gas fuel prices, coal was found to dominate carbon capture deployment throughout the study period, while for the scenarios with lower or base energy prices, natural gas dominates carbon capture deployment. Further, it was noted that projected carbon capture deployment was approximately two to three times as large for a given simulation year after 2030 under an aggressive RD&D program compared to the same year for scenarios with a less aggressive RD&D program. The resulting retail electricity prices were also lower for the scenarios with lower fuel and crude oil prices.