Next Generation Three-Dimensional Geologic Modeling and Inversion

Mark Jessell and Laurent Ailleres and Mark Lindsay and Florian Wellmann and Michael Hillier and Gautier Laurent and Thomas Carmichael and Roland Martin. ( 2014 )
in: Society of Economic Geologists, Special Publication, 18 (261--272)

Abstract

Existing three-dimensional (3-D) geologic systems are well adapted to high data-density environments, such as at the mine scale where abundant drill core exists, or in basins where 3-D seismic provides stratigraphic constraints but are poorly adapted to regional geologic problems. There are three areas where improvements in the 3-D workflow need to be made: (1) the handling of uncertainty, (2) the model-building algorithms themselves, and (3) the interface with geophysical inversion. All 3-D models are underconstrained, and at the regional scale this is especially critical for choosing modeling strategies. The practice of only producing a single model ignores the huge uncertainties that underlie modelbuilding processes, and underpins the difficulty in providing meaningful information to end-users about the inherent risk involved in applying the model to solve geologic problems. Future studies need to recognize this and focus on the characterization of model uncertainty, spatially and in terms of geologic features, and produce plausible model suites, rather than single models with unknown validity. The most promising systems for understanding uncertainty use implicit algorithms because they allow the inclusion of some geologic knowledge, for example, age relationships of faults and onlap-offlap relationships. Unfortunately, existing implicit algorithms belie their origins as basin or mine modeling systems because they lack inclusion of normal structural criteria, such as cleavages, lineations, and recognition of polydeformation, all of which are primary tools for the field geologist that is making geologic maps in structurally complex areas. One area of future research will be to establish generalized structural geologic rules that can be built into the modeling process. Finally, and this probably represents the biggest challenge, there is the need for geologic meaning to be maintained during the model-building processes. Current data flows consist of the construction of complex 3-D geologic models that incorporate geologic and geophysical data as well as the prior experience of the modeler, via their interpretation choices. These inputs are used to create a geometric model, which is then transformed into a petrophysical model prior to geophysical inversion. All of the underlying geologic rules are then ignored during the geophysical inversion process. Examples exist that demonstrate that the loss of geologic meaning between geologic and geophysical modeling can be at least partially overcome by increased use of uncertainty characteristics in the workflow.

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    BibTeX Reference

    @ARTICLE{Jessell2014,
        author = { Jessell, Mark and Ailleres, Laurent and Lindsay, Mark and Wellmann, Florian and Hillier, Michael and Laurent, Gautier and Carmichael, Thomas and Martin, Roland },
         title = { Next Generation Three-Dimensional Geologic Modeling and Inversion },
       journal = { Society of Economic Geologists, Special Publication },
        volume = { 18 },
          year = { 2014 },
         pages = { 261--272 },
      abstract = { Existing three-dimensional (3-D) geologic systems are well adapted to high data-density environments, such
    as at the mine scale where abundant drill core exists, or in basins where 3-D seismic provides stratigraphic constraints
    but are poorly adapted to regional geologic problems. There are three areas where improvements in the
    3-D workflow need to be made: (1) the handling of uncertainty, (2) the model-building algorithms themselves,
    and (3) the interface with geophysical inversion.
    All 3-D models are underconstrained, and at the regional scale this is especially critical for choosing modeling
    strategies. The practice of only producing a single model ignores the huge uncertainties that underlie modelbuilding
    processes, and underpins the difficulty in providing meaningful information to end-users about the
    inherent risk involved in applying the model to solve geologic problems. Future studies need to recognize this
    and focus on the characterization of model uncertainty, spatially and in terms of geologic features, and produce
    plausible model suites, rather than single models with unknown validity.
    The most promising systems for understanding uncertainty use implicit algorithms because they allow the
    inclusion of some geologic knowledge, for example, age relationships of faults and onlap-offlap relationships.
    Unfortunately, existing implicit algorithms belie their origins as basin or mine modeling systems because they
    lack inclusion of normal structural criteria, such as cleavages, lineations, and recognition of polydeformation,
    all of which are primary tools for the field geologist that is making geologic maps in structurally complex areas.
    One area of future research will be to establish generalized structural geologic rules that can be built into the
    modeling process.
    Finally, and this probably represents the biggest challenge, there is the need for geologic meaning to be
    maintained during the model-building processes. Current data flows consist of the construction of complex 3-D
    geologic models that incorporate geologic and geophysical data as well as the prior experience of the modeler,
    via their interpretation choices. These inputs are used to create a geometric model, which is then transformed
    into a petrophysical model prior to geophysical inversion. All of the underlying geologic rules are then ignored
    during the geophysical inversion process. Examples exist that demonstrate that the loss of geologic meaning
    between geologic and geophysical modeling can be at least partially overcome by increased use of uncertainty
    characteristics in the workflow. }
    }