figures cluster world oct. 2004 opendtect article for optimal printing quality do not copy figures...
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Figures Cluster World Oct. 2004 OpendTect article
• For optimal printing quality do not copy Figures 3, 4 and 6a, 6b and 6c from this Powerpoint file. Instead use original tif images!
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Third Party
dGB-Group
Ownership, M&S Responsibility License and M&S fees Waived fees (dGB plugins)
Commercial Users
Academic Users
Commercial Plug-ins
Base
Free Plug-ins
Figure 1. Open Source model.
Figure 2. OpendTect impression.
Figure 3. Geometrically consistent tracking of horizons and faults.
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Energy
Input Attributes: Energy, Frequency, Cube Similarity Continuity, Dip Var., Azimuth Var.,
Absorption, Curvature, ..
Interpreter’s
Knowledge
Meta-Attribute
ANN
Figure 4. “Meta-attribute” concept. Multiple attributes and interpreter’s knowledge are combined by a neural network to give the optimal view of the object of
interest. In this case a salt dome.
Figure 5. Application examples of dip-steering and neural network plugins to OpendTect.
Chimneys
& dGB plugins
Salt
… and turbidites, 4D bodies, ….
Faults
Object
detection
Rock properties
Inversion
Before
After dip-steered median filter
Filtering
Facies / Channels
Patternrecognition
a b c
Figure 6. Generating TheChimneyCube®: a) Picked examples b) neural network performance graphs (RMS error vs. training cycles, percentage mis-classification and input attributes colored to indicate relative importance, with red being
most important) and c) overlay of chimney “probability” on seismic data.