Semi-automatic interpretation of 3D-Sedimentological Structures on Geological Images: an object-based approach.

in: 35th Gocad Meeting - 2015 RING Meeting, ASGA

Abstract

The characterization of sedimentary structures is an important step to construct quantitative models of sedimentary deposits from digital images such as 3D seismic data, satellite images or digital outcrops. However, the interpretation of these structures generally consists in tedious line pickings followed by surface modeling to define geobodies. Automatic geobody extraction is an alternative but it is sensitive to image noise and does not account for prior sedimentary knowledge. We propose to combine minimal picking by an interpreter with object-guided image processing and optimization to achieve fast and semi-automatic geobody interpretation. Our approach uses a realistic volumetric geobody representation based on Non-Uniform Rational B-Splines (NURBS) which can easily be deformed by the interpreter and numerical optimization. A custom edge detection guided by some initial rough interpretations is performed to strengthen the most relevant edges in the picture. An automatic optimization is then computed to fit the initial geobody to these highlighted edges. This approach is applied on satellite pictures showing alluvial channels and some preliminary results on 3D seismic time slices are also presented. The interpreted channels are then used in a retro-deformation process to automatically reconstruct the point bars. This semiautomatic method opens new perspectives to help interpreters rapidly come up with 3D models of sedimentary structures from subsurface and analog surface data sets.

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BibTeX Reference

@INPROCEEDINGS{RuiuGM2015,
    author = { Ruiu, Jeremy and Caumon, Guillaume and Viseur, Sophie },
     title = { Semi-automatic interpretation of 3D-Sedimentological Structures on Geological Images: an object-based approach. },
 booktitle = { 35th Gocad Meeting - 2015 RING Meeting },
      year = { 2015 },
 publisher = { ASGA },
  abstract = { The characterization of sedimentary structures is an important step to construct quantitative models of sedimentary deposits from digital images such as 3D seismic data, satellite images or digital outcrops. However, the interpretation of these structures generally consists in tedious line pickings followed by surface modeling to define geobodies. Automatic geobody extraction is an alternative but it is sensitive to image noise and does not account for prior sedimentary knowledge. We propose to combine minimal picking by an interpreter with object-guided image processing and optimization to achieve fast and semi-automatic geobody interpretation. Our approach uses a realistic volumetric geobody representation based on Non-Uniform Rational B-Splines (NURBS) which can easily be deformed by the interpreter and numerical optimization. A custom edge detection guided by some initial rough interpretations is performed to strengthen the most relevant edges in the picture. An automatic optimization is then computed to fit the initial geobody to these highlighted edges. This approach is applied on satellite pictures showing alluvial channels and some preliminary results on 3D seismic time slices are also presented. The interpreted channels are then used in a retro-deformation process to automatically reconstruct the point bars. This semiautomatic method opens new perspectives to help interpreters rapidly come up with 3D models of sedimentary structures from subsurface and analog surface data sets. }
}