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IPLAB Kohonen1D/2D/3D Classification3D
By IPLAB LLC
Plug-in Attributes
Platform:
Petrel
Lifecycle
Exploration
Challenges:
Unconventional Heavy Oil | Carbonate and Fractures | Unconventional Shale
ECCN:
Russia origin, EAR99
Version
  • 2018 | 2019 | 2020
Supporting Documents
Installation Guide
Release Notes
User Manual
Others
Overview
Provides seismic cube classification using Kohonen 1D, 2D, and 3D neural network. The plug-in can be used for unsupervised classification using a seismic cube waveform based on a Kohonen self-organizing map (SOM) 1D, 2D, or 3D neural network. The results are virtual seismic cubes ready for RGB mixing.
Specifications
The 1D Kohonen neural network will create one index class. The 2D Kohonen neural network will create two indexed classes and thus will require RGB mix visualization. The 3D Kohonen neural network will create three indexed classes and will require RGB mix visualization. During the learning and calculation stages, the plug-in will use parallel processing based on all available CPU cores. It helps calculation performance for the 3D Kohonen neural network and saves significant time.
Features
  • Kohonen 2D or 3D projection provides better showing of object positions in multidimensional space
  • • RGB blending of 2D or 3D neural network projections potentially permits more accurate geological facies interpretation
Additional Information
A defined set of surface properties are used for classification. Optionally, it can be used for seismic waveform classification based on seismic cubes (one or several) and with layer definition (top and bottom surfaces).