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    Analysis of time lapse seismic signal for an EOR and CCS site, Cranfield, MS

    Access Status
    Fulltext not available
    Authors
    Ditkof, J.
    Meckel, T.
    Hovorka, S.
    Caspari, Eva
    Pevzner, Roman
    Urosevic, Milovan
    Date
    2012
    Type
    Conference Paper
    
    Metadata
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    Citation
    Ditkof, Julie and Meckel, Tip and Hovorka, Susan and Caspari, Eva and Pevzner, Roman and Urosevic, Milovan. 2012. Analysis of time lapse seismic signal for an EOR and CCS site, Cranfield, MS, in Proceedings of the Annual Meeting of the Society of Exploration Geophysicists (SEG), Nov 4-9 2012. Las Vegas: SEG.
    Source Title
    SEG Technical Program Expanded Abstracts
    Source Conference
    SEG/Las Vegas 2012
    DOI
    10.1190/segam2012-0912.1
    ISSN
    1052-3812
    URI
    http://hdl.handle.net/20.500.11937/7173
    Collection
    • Curtin Research Publications
    Abstract

    The Cranfield, MS EOR field site has been under CO2 flood by Denbury Onshore, LLC since 2008. More than 3 million tons of CO2 has been injected. Time-lapse 3D surface seismic data displayed a readily observable signal related to CO2 injection into the lower Tuscaloosa Formation. The intensity and the spatial distribution of time-lapse (TL) signal required further analysis. For that purpose, we carried out fluid substitution analysis, followed by volumes cross-equalization, well ties, and acoustic impedance inversions. A Gassmann workflow was used to predict the response to injected CO2 at two well locations. The 31F-2 observation well, located in a detailed area of study (DAS), was used to compare the results of time-lapse sonic data with fluid substitution results. The objective was to predict a post-injection saturation curve. A second well, well 28-1, was used to help predict an acoustic impedance change in the reservoir to use for subsequent inversion. Finally, a model based inversion was performed to quantify the impedance change between two cross-equalized time-lapse data sets. The acoustic impedance (AI) difference obtained through the inversion process is higher than that predicted for in the 28-1 injection well. The time-lapse AI signal is however in agreement with the large velocity change computed from the time delay along the marker horizon below the reservoir.

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