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:
- LithoSeismic Classification is based on the classical cross-plot method.
- Waveform Classification is the Kohonen Self Organizing Map method, which has been an industry standard in Stratimagic since the 1990s.
- 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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