The Bureau of Economic Geology The University of Texas at Austin Jackson School of Geosciences
spt2
 

From Bureau of Economic Geology, The University of Texas at Austin (www.beg.utexas.edu).
For more information, please contact the author.

Bureau Seminar, February 25, 2011

Self-Organization and Learning Machines - A Seismic Interpretation Perspective

Link to streaming video TBA: available 02.25.2011 at 8:55am

Dr. Tom Smith
Geophysical Insights

Tom Smith
Self-organizing assemblages such as flocks of geese and schools of fish are examples of organizations whose members follow simple rules. With geese, the rule is to follow to the left or right of the goose in front and follow about a foot behind. While the rules for individuals are simple, the properties of assemblages are vastly different. Self-organizing Maps (SOM), discovered by T. Kohonen in the 1990's and brought to exploration geophysics by T. Taner and S. Treitel in the 2000's, are a type of computer learning machine which adapts to properties in the input data space. We illustrate SOM with simple examples from other fields and conclude with results where SOM has automatically identified seismic anomalies of geologic interest using multiple attributes of 3D seismic surveys.

 

 

 
Department of Geological Sciences
Institute for Geophysics
 
 
The University of Texas
 
Contact information
Facilities
Maps and Directions
Media Contacts
Employment Opportunities
Bureau Reports
Calendar
 
 
spb2
©2010 Bureau of Economic Geology, The University of Texas at Austin