摘要
Over the last decades,people from almost all over the world have realized that it is necessary to quickly develop strategies for the control and reduction of greenhouse gases (GHG) emissions.Among various GHGs,carbon dioxide (CO2) is the most abundant GHG.Its underground storage involves less risk and lower levels of dangerousness.The paper briefly describes the most effective technologies available in the market for background processes to storage (capture and transport) CO2,as well as the more secure solutions for its storage,in particular for the geological storage in carboniferous formations.This paper also outlines the methodologies for the risk assessment involved in storage of CO2,with a particular focus on cases where the injection is made into unminable coal seams and in abandoned coalmines.Methodologies used for risk analysis are described in detail with particular emphasis on Bayesian network (BN).Some applications regarding the risk assessment of CO2 injection processes and CO2 storage in carboniferous formations and contamination of aquifers are presented and analyzed.Finally,based on the applications of BN,several conclusions are drawn.
Over the last decades,people from almost all over the world have realized that it is necessary to quickly develop strategies for the control and reduction of greenhouse gases (GHG) emissions.Among various GHGs,carbon dioxide (CO2) is the most abundant GHG.Its underground storage involves less risk and lower levels of dangerousness.The paper briefly describes the most effective technologies available in the market for background processes to storage (capture and transport) CO2,as well as the more secure solutions for its storage,in particular for the geological storage in carboniferous formations.This paper also outlines the methodologies for the risk assessment involved in storage of CO2,with a particular focus on cases where the injection is made into unminable coal seams and in abandoned coalmines.Methodologies used for risk analysis are described in detail with particular emphasis on Bayesian network (BN).Some applications regarding the risk assessment of CO2 injection processes and CO2 storage in carboniferous formations and contamination of aquifers are presented and analyzed.Finally,based on the applications of BN,several conclusions are drawn.
基金
support from the State Administration of Foreign Experts Affairs,China,for the research project "Risk assessment of CO 2 injection processes in carboniferous formations" at State Key Laboratory for Geomechanics and Deep Underground Engineering,China University of Science and Technology (Beijing)
