Systems, methods, and computer medium to produce efficient, consistent, and high-confidence image-based electrofacies analysis in stratigraphic interpretations across multiple wells
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United States of America Patent
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Apr 10, 2018
Grant Date -
Aug 27, 2015
app pub date -
Jun 30, 2014
filing date -
Feb 24, 2014
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Abstract
Embodiments of systems, computer-implemented methods, and non-transitory computer-readable medium having one or more computer programs stored therein are provided to enhance borehole image analysis associated with a hydrocarbon reservoir. A neural network mapping process can first be performed, responsive to openhole log data and core data, to thereby generate a material-type scheme. Then, an image-based petrophysical analysis process can distribute and calibrate borehole image data, responsive to the core data and material-type scheme. Consequently, an approximated material type and an approximated grain size can be produced for each borehole image reading. The openhole log data, the core data, the material-type scheme, and the approximated material types and grain sizes, for example, can then be displayed to thereby increase consistency in categorizing subsurface material associated with hydrocarbon wells by material type and enhance interpretation of subsurface material texture, fabric, and features to predict subsurface material composition of the hydrocarbon reservoir.
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