A screening and ranking framework (SRF) has been developed to evaluate potential geologic carbon dioxide (CO2) storage sites on the basis of health, safety, and environmental (HSE) risk arising from CO2 leakage. The approach is based on the assumption that CO2 leakage risk is dependent on three basic characteristics of a geologic CO2 storage site: (1) the potential for primary containment by the target formation; (2) the potential for secondary containment if the primary formation leaks; and (3) the potential for attenuation and dispersion of leaking CO2 if the primary formation leaks and secondary containment fails. The framework is implemented in a spreadsheet in which users enter numerical scores representing expert opinions or published information along with estimates of uncertainty. Applications to three sites in California demonstrate the approach. Refinements and extensions are possible through the use of more detailed data or model results in place of property proxies.

This report describes a screening and ranking framework (SRF) developed to evaluate potential geologic carbon dioxide (CO2) storage sites on the basis of health, safety, and environmental (HSE) risk arising from possible CO2 leakage. The approach is based on the assumption that HSE risk due to CO2 leakage is dependent on three basic characteristics of a geologic CO2 storage site: (1) the potential for primary containment by the target formation, (2) the potential for secondary containment if the primary formation leaks, and (3) the potential for attenuation and dispersion of leaking CO2 if the primary formation leaks and secondary containment fails. The framework is implemented in a spreadsheet in which users enter numerical scores representing expert opinions or general information available from published materials along with estimates of uncertainty to evaluate the three basic characteristics in order to screen and rank candidate sites. Application of the framework to the Rio Vista Gas Field, Ventura Oil Field, and Mammoth Mountain demonstrates the approach. Refinements and extensions are possible through the use of more detailed data or model results in place of property proxies. Revisions and extensions to improve the approach are anticipated in the near future as it is used and tested by colleagues and collaborators.