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Quick-look assessments to identify optimal CO sub(2) EOR storage sites

A newly developed, multistage quick-look methodology allows for the efficient screening of an unmanageably large number of reservoirs to generate a workable set of sites that closely match the requirements for optimal CO sub(2) enhanced oil recovery (EOR) storage. The objective of the study is to qu...

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Bibliographic Details
Published in:Environmental geology (Berlin) 2008-06, Vol.54 (8), p.1695-1706
Main Authors: Nunez-Lopez, Vanessa, Holtz, Mark H, Wood, Derek J, Ambrose, William A, Hovorka, Susan D
Format: Article
Language:English
Online Access:Get full text
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Summary:A newly developed, multistage quick-look methodology allows for the efficient screening of an unmanageably large number of reservoirs to generate a workable set of sites that closely match the requirements for optimal CO sub(2) enhanced oil recovery (EOR) storage. The objective of the study is to quickly identify miscible CO sub(2) EOR candidates in areas that contain thousands of reservoirs and to estimate additional oil recovery and sequestration capacities of selected top options through dimensionless modeling and reservoir characterization. Quick-look assessments indicate that the CO sub(2) EOR resource potential along the US Gulf Coast is 4.7billion barrels, and CO sub(2 )sequestration capacity is 2.6billion metric tons. In the first stage, oil reservoirs are screened and ranked in terms of technical and practical feasibility for miscible CO sub(2) EOR. The second stage provides quick estimates of CO sub(2) EOR potential and sequestration capacities. In the third stage, a dimensionless group model is applied to a selected set of sites to improve the estimates of oil recovery and storage potential using appropriate inputs for rock and fluid properties, disregarding reservoir architecture and sweep design. The fourth stage validates and refines the results by simulating flow in a model that describes the internal architecture and fluid distribution in the reservoir. The stated approach both saves time and allows more resources to be applied to the best candidate sites.
ISSN:0943-0105
1432-0495
DOI:10.1007/s00254-007-0944-y