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

Objectives:
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) .

Duration:
1 day

Prerequisites:

• 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.

Contents:
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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