TexasScholarWorks
    • Login
    • Submit
    View Item 
    •   Repository Home
    • UT Faculty/Researcher Works
    • UT Faculty/Researcher Works
    • View Item
    • Repository Home
    • UT Faculty/Researcher Works
    • UT Faculty/Researcher Works
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Characterizing Curvilinear Features Using The Localized Normal-Score Ensemble Kalman Filter

    Thumbnail
    View/Open
    2012_03_Characterizing_Curvilinear.pdf (12.43Mb)
    Date
    2012-03
    Author
    Zhou, Haiyan
    Li, Liangping
    Gomez-Hernandez, J. Jaime
    Share
     Facebook
     Twitter
     LinkedIn
    Metadata
    Show full item record
    Abstract
    The localized normal-score ensemble Kalman filter is shown to work for the characterization of non-multi-Gaussian distributed hydraulic conductivities by assimilating state observation data. The influence of type of flow regime, number of observation piezometers, and the prior model structure are evaluated in a synthetic aquifer. Steady-state observation data are not sufficient to identify the conductivity channels. Transient-state data are necessary for a good characterization of the hydraulic conductivity curvilinear patterns. Such characterization is very good with a dense network of observation data, and it deteriorates as the number of observation piezometers decreases. It is also remarkable that, even when the prior model structure is wrong, the localized normal-score ensemble Kalman filter can produce acceptable results for a sufficiently dense observation network.
    Department
    Petroleum and Geosystems Engineering
    Subject
    sequential data assimilation
    flow
    parameters
    transient
    mathematics, applied
    mathematics
    URI
    http://hdl.handle.net/2152/31072
    xmlui.dri2xhtml.METS-1.0.item-citation
    Haiyan Zhou, Liangping Li, and J. Jaime Gómez-Hernández, “Characterizing Curvilinear Features Using the Localized Normal-Score Ensemble Kalman Filter,” Abstract and Applied Analysis, vol. 2012, Article ID 805707, 18 pages, 2012. doi:10.1155/2012/805707
    Collections
    • UT Faculty/Researcher Works

    University of Texas at Austin Libraries
    • facebook
    • twitter
    • instagram
    • youtube
    • CONTACT US
    • MAPS & DIRECTIONS
    • JOB OPPORTUNITIES
    • UT Austin Home
    • Emergency Information
    • Site Policies
    • Web Accessibility Policy
    • Web Privacy Policy
    • Adobe Reader
    Subscribe to our NewsletterGive to the Libraries

    © The University of Texas at Austin

     

     

    Browse

    Entire RepositoryCommunities & CollectionsDate IssuedAuthorsTitlesSubjectsDepartmentsThis CollectionDate IssuedAuthorsTitlesSubjectsDepartments

    My Account

    Login

    Statistics

    View Usage Statistics

    Information

    About Contact Policies Getting Started Glossary Help FAQs

    University of Texas at Austin Libraries
    • facebook
    • twitter
    • instagram
    • youtube
    • CONTACT US
    • MAPS & DIRECTIONS
    • JOB OPPORTUNITIES
    • UT Austin Home
    • Emergency Information
    • Site Policies
    • Web Accessibility Policy
    • Web Privacy Policy
    • Adobe Reader
    Subscribe to our NewsletterGive to the Libraries

    © The University of Texas at Austin