Curtin University Homepage
  • Library
  • Help
    • Admin

    espace - Curtin’s institutional repository

    JavaScript is disabled for your browser. Some features of this site may not work without it.
    View Item 
    • espace Home
    • espace
    • Curtin Research Publications
    • View Item
    • espace Home
    • espace
    • Curtin Research Publications
    • View Item

    Facies-constrained FWI: Toward application to reservoir characterization

    Access Status
    Fulltext not available
    Authors
    Kamath, N.
    Tsvankin, Ilya
    Naeini, E.
    Date
    2017
    Type
    Journal Article
    
    Metadata
    Show full item record
    Citation
    Kamath, N. and Tsvankin, I. and Naeini, E. 2017. Facies-constrained FWI: Toward application to reservoir characterization. The Leading Edge. 36 (11): pp. 924-930.
    Source Title
    The Leading Edge
    DOI
    10.1190/tle36110924.1
    ISSN
    1070-485X
    School
    WASM: Minerals, Energy and Chemical Engineering (WASM-MECE)
    URI
    http://hdl.handle.net/20.500.11937/72091
    Collection
    • Curtin Research Publications
    Abstract

    © 2017 by The Society of Exploration Geophysicists. The most common approach to obtaining reservoir properties from seismic data exploits the amplitude variation with offset response of reflected waves. However, structural complexity and errors in the velocity model can severely reduce the quality of the inverted results. Full-waveform inversion (FWI) has shown a lot of promise in obtaining high-resolution velocity models for depth imaging. We propose supplementing FWI with rock-physics constraints obtained from borehole data to invert for reservoir properties. The constraints are imposed by adding appropriately weighted regularization terms to the objective function. The advantages of this technique over conventional FWI algorithms are shown by conducting synthetic tests for both isotropic and VTI (transversely isotropic with a vertical symmetry axis) models. The medium parameterization for FWI is selected using radiation (scattering) patterns of perturbations in the model parameters.

    Related items

    Showing items related by title, author, creator and subject.

    • Modelling pile capacity and load-settlement behaviour of piles embedded in sand & mixed soils using artificial intelligence
      Alkroosh, Iyad Salim Jabor (2011)
      This thesis presents the development of numerical models which are intended to be used to predict the bearing capacity and the load-settlement behaviour of pile foundations embedded in sand and mixed soils. Two artificial ...
    • Multi-scale modelling of Gibbsite calcination in a fluidized bed reactor
      Amiri, Amirpiran (2013)
      The alumina industry provides the feedstock for aluminium metal production and contributes to around A$6 billion of Australian exports annually. One of the most energy-intensive parts of alumina production, with a strong ...
    • A multi-model approach to stakeholder engagement in complex environmental problems
      Fulton, B.; Jones, Tod; Boschetti, F.; Sporcic, M.; De La Mare, W.; Syme, Geoffrey; Dzidic, Peta; Gorton, R.; Little, L.; Dambacher, G.; Chapman, K. (2011)
      We describe the different types of models we used as part of an effort to inform policy-making aiming at the management of the Ningaloo coast in the Gascoyne region, Western Australia. This provides an overview of how ...
    Advanced search

    Browse

    Communities & CollectionsIssue DateAuthorTitleSubjectDocument TypeThis CollectionIssue DateAuthorTitleSubjectDocument Type

    My Account

    Admin

    Statistics

    Most Popular ItemsStatistics by CountryMost Popular Authors

    Follow Curtin

    • 
    • 
    • 
    • 
    • 

    CRICOS Provider Code: 00301JABN: 99 143 842 569TEQSA: PRV12158

    Copyright | Disclaimer | Privacy statement | Accessibility

    Curtin would like to pay respect to the Aboriginal and Torres Strait Islander members of our community by acknowledging the traditional owners of the land on which the Perth campus is located, the Whadjuk people of the Nyungar Nation; and on our Kalgoorlie campus, the Wongutha people of the North-Eastern Goldfields.