Spatial Stochastic Modeling of Sedimentary Formations to Assess CO2 Storage Potential

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• 作者：Olga H. Popova ; Mitchell J. Small ; Sean T. McCoy ; A. C. Thomas ; Stephen Rose ; Bobak Karimi ; Kristin Carter ; Angela Goodman
• 刊名：Environmental Science & Technology
• 出版年：2014
• 出版时间：June 3, 2014
• 年：2014
• 卷：48
• 期：11
• 页码：6247-6255
• 全文大小：407K
• 年卷期：v.48,no.11(June 3, 2014)
• ISSN：1520-5851

文摘

Carbon capture and sequestration (CCS) is a technology that provides a near-term solution to reduce anthropogenic CO₂ emissions to the atmosphere and reduce our impact on the climate system. Assessments of carbon sequestration resources that have been made for North America using existing methodologies likely underestimate uncertainty and variability in the reservoir parameters. This paper describes a geostatistical model developed to estimate the CO₂ storage resource in sedimentary formations. The proposed stochastic model accounts for the spatial distribution of reservoir properties and is implemented in a case study of the Oriskany Formation of the Appalachian sedimentary basin. Results indicate that the CO₂ storage resource for the Pennsylvania part of the Oriskany Formation has substantial spatial variation due to heterogeneity of formation properties and basin geology leading to significant uncertainty in the storage assessment. The Oriskany Formation sequestration resource estimate in Pennsylvania calculated with the effective efficiency factor, E = 5%, ranges from 0.15 to 1.01 gigatonnes (Gt) with a mean value of 0.52 Gt of CO₂ (E = 5%). The methodology is generalizable to other sedimentary formations in which site-specific trend analyses and statistical models are developed to estimate the CO₂ sequestration storage capacity and its uncertainty. More precise CO₂ storage resource estimates will provide better recommendations for government and industry leaders and inform their decisions on which greenhouse gas mitigation measures are best fit for their regions.