Spatial Stochastic Modeling of Sedimentary Formations to Assess CO^sub 2^ Storage Potential

• Published in: Environmental science & technology Vol. 48; no. 11; p. 6247
• Main Authors: Popova, Olga H, Small, Mitchell J, McCoy, Sean T, Thomas, A C, Rose, Stephen, Karimi, Bobak, Carter, Kristin, Goodman, Angela
• Format: Journal Article
• Language: English
• Published: Easton American Chemical Society 03-06-2014
• Subjects: Carbon dioxide; Carbon sequestration; Environmental science; Sedimentation & deposition; Stochastic models
• ISSN: 0013-936X

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.