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Litho-Seismic, Waveform, and Rock Type Classifications for Rock Type and Fluid Prediction

One of the leading challenges in hydrocarbon recovery is predicting rock types and fluid content distribution throughout the reservoir away from the boreholes.  This is because rock property determination is a major source of uncertainty in reservoir modeling studies. Spatial determination of the lateral and vertical heterogeneities has a direct impact on a reservoir model because it will affect the property distributions.

We will present three methods for predicting rock type and fluid distributions using seismic data: 

  1. LithoSeismic Classification is based on the classical cross-plot method.
  2. Waveform Classification is the Kohonen Self Organizing Map method, which has been an industry standard in Stratimagic since the 1990s.
  3. Rock Type Classification is a new neural network-based methodology called Democratic Neural Network Association (DNNA) .

1 day


  • Background in geosciences
  • Experience with any modern seismic interpretation software

 Who should attend?
Geoscientists, engineers, or other technical personnel interested in using litho-seismic, waveform and rock type classification tools.

This class uses the Paradigm 2017 Classification for Interpreters plug-in to the SeisEarth seismic interpretation platform. It does not use the Stratimagic software product, although the Classification for Interpreters plug-in uses algorithms from Stratimagic.

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