Parameterization of Complex 3D Heterogeneities: A New CAD Approach

in: SPE Computer Applications, 6:3

Abstract

This paper presents a new method for generating and interpolating complex reservoir shapes in 3D. The method combines integration of quantitative knowledge about the shapes of the geologic bodies being modeled and generation of a large range of possible geometries corresponding to this knowledge. It is a new CAD approach based on the discrete smooth interpolation method (DSI). We apply this method to the geometric modeling of part of a complex turbiditic reservoir. In this example, channels and lobes account for most of the production, and their geometries are critical factors for oil recovery. Data include well logs, statistics about the shapes of main reservoir heterogeneities, and 3D templates representing the most likely shape. Geometric characterization of the sand bodies in this field is performed through stochastic modeling. The method used involves a Boolean approach based on indicator components and emphasizes the importance of honoring well data.

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BibTeX Reference

@ARTICLE{wietzerbin_SPE1994,
    author = { Wietzerbin, L. and Mallet, Jean-Laurent },
     title = { Parameterization of Complex 3D Heterogeneities: A New CAD Approach },
     month = { "may" },
   journal = { SPE Computer Applications },
    volume = { 6 },
    number = { 3 },
      year = { 1994 },
       doi = { 10.2118/26423-pa },
  abstract = { This paper presents a new method for generating and interpolating complex reservoir shapes in 3D. The method combines integration of quantitative knowledge about the shapes of the geologic bodies being modeled and generation of a large range of possible geometries corresponding to this knowledge. It is a new CAD approach based on the discrete smooth interpolation method (DSI). We apply this method to the geometric modeling of part of a complex turbiditic reservoir. In this example, channels and lobes account for most of the production, and their geometries are critical factors for oil recovery. Data include well logs, statistics about the shapes of main reservoir heterogeneities, and 3D templates representing the most likely shape. Geometric characterization of the sand bodies in this field is performed through stochastic modeling. The method used involves a Boolean approach based on indicator components and emphasizes the importance of honoring well data. }
}