Presentation on theme: "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."— Presentation transcript:
Figures Cluster World Oct 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! The OpendTect logo is delivered in EPS format. Contact for other formats and/or
Third Party dGB-Group Ownership, M&S Responsibility License and M&S fees Waived fees (dGB plugins) Commercia l 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.
O O O O O O Energy Input Attributes : Energy, Frequency, Cube Similarity Continuity, Dip Var., Azimuth Var., Absorption, Curvature,.. Interpreters Knowledge Meta- Attribute ANN Figure 4. Meta-attribute concept. Multiple attributes and interpreters 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 Pattern recognition
abc 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.