Factors Determining Commercially Optimal Development Strategies for CO2 Storage With and Without CO2-EOR
- Advanced Resources International (ARI), Inc., Knoxville, TN (United States)
- Southern States Energy Board, Peachtree Corners, GA (United States)
This report is a draft white paper on the factors determining commercially optimal development strategies for CO2 storage with and without CO2-EOR. The draft report provides a summary of accomplishments during the first budget period of the Southeast Offshore Storage Resource Assessment for the Gulf of Mexico (SECARB Offshore GOM) project. It also identifies “Next Steps” to be undertaken during Budget Period II. A final white paper will be prepared at the end of Budget Period II. The goal of this draft white paper is to expand the knowledge base required for commercially viable, secure, longterm, large-scale carbon dioxide (CO2) subsea storage in the U.S. Gulf of Mexico (GOM), both with and without enhanced hydrocarbon recovery. This effort supports the U.S. Department of Energy’s (DOE) long-term objective of ensuring a comprehensive assessment of the potential for offshore CO2 subsea storage in the GOM. The groundwork that has been completed in the draft white paper advanced by expanding the membership of the Southern States Energy Board’s (SSEB) existing Southeast Offshore Storage Resource Assessment (DE-FE0026082) GOM government-industry partnership during the next budget period. Further, the team plans to consult with U.S. federal and state agencies to develop recommendations to remove barriers and streamline the regulatory process to encourage subsea CO2 storage with or without enhanced hydrocarbon recovery.
- Research Organization:
- Southern States Energy Board, Peachtree Corners, GA (United States)
- Sponsoring Organization:
- USDOE Office of Fossil Energy (FE)
- DOE Contract Number:
- FE0031557
- OSTI ID:
- 1836589
- Report Number(s):
- SSEB-FE0031557-6; SSEB-FE0031557-6
- Country of Publication:
- United States
- Language:
- English
Similar Records
Parametric Study to Assess Technical Prospect Feasibility for Offshore CO2 Storage
Using Machine Learning to Identify Optimum Prospects for Offshore Geologic CO2 Storage and Enhanced Oil Recovery in the Gulf of Mexico