• journal_title：Environmental Geosciences
• Contributor：Olga H. Popova ; Mitchell J. Small ; Sean T. McCoy ; A. C. Thomas ; Bobak Karimi ; Angela Goodman ; Kristin M. Carter
• Publisher：American Association of Petroleum Geologists (AAPG)
• Date：2012-
• Format：text/html
• Language：en
• Identifier：10.1306/eg.06011212002
• journal_abbrev：Environmental Geosciences
• issn：1075-9565
• volume：19
• issue：3
• firstpage：105
• section：Articles

Today, an increased emphasis on the distribution, potential volume, and cost to develop CO₂ geologic sequestration resources exists. In the presence of climate change, the need to make accurate and clearly understandable assessments of carbon sequestration potential, which can be used by the government and industry to plan for technology deployment, has never been greater. We compare three CO₂ storage assessment methodologies: the approach applied by the U.S. Department of Energy in its Carbon Atlas III, the modified U.S. Geological Survey methodology, and the CO₂ Geological Storage Solutions methodology. All three methodologies address storage resources in porous geologic media in sedimentary basins, namely oil and gas reservoirs and saline formations. Based on our analyses, these methodologies are similar in terms of computational formulation. We find that each of the proposed methodologies is science and engineering based. As such, they are important in identifying the geographical distribution of CO₂ storage resource and regional carbon sequestration potential at the national and basin-scale levels for use in energy-related government policy and business decisions. Policy makers need these high-level estimates to evaluate the prospective function that carbon capture and sequestration technologies can play in reducing CO₂ emissions over the long term. The value of these high-level assessments of CO₂ storage resource is to help inform decision makers in governments and industry as to whether carbon capture and sequestration is a climate mitigation option worth pursuing in particular regions.