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Fuzzy Classification for Lithology Determination from Well Logs

  • Antoine Toumani
Part of the Modern Approaches in Geophysics book series (MAGE, volume 21)

Abstract

A new hybrid fuzzy classification method has been employed successfully for the discrimination of lithology from well logs. It is based on the correlation of log responses from key boreholes having a known lithology, with the logs from neighbouring boreholes where only well logs are available. The method combines a model-based supervised classification and a model-free unsupervised clustering into a single classification. Both supervised/unsupervised parts are linked together by the fuzzy membership of the log data within the determined lithology. Fuzzy membership of the data serves also as a quality measure of the classification results, and provides valuable information concerning the reliability of the model. The classification approach has been used successfully for determining Upper Carboniferous lithologies from open hole logs in a multi-well study.

Keywords

Coal Seam Fuzziness Measure Fuzzy Classification Hybrid Classification Lithology Column 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media Dordrecht 2003

Authors and Affiliations

  • Antoine Toumani
    • 1
  1. 1.GeoTec Division, Geo-EngineeringDMT GmbHEssenGermany

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