Introduction to Self-Organzing Maps in Multi-Attribute Seismic Data

Introduction to Self-Organzing Maps in Multi-Attribute Seismic Data

Unsupervised neural network searches multi-dimensional data for natural clusters. Neurons are attracted to areas of higher information density. The SOM analysis relates to subsurface geometry and rock properties while noting multi-attribute seismic properties at the wells, correlating to rock lithologies, with those away from the wells.

Submitting....

X

What can we help you find today ?

More information about machine learning
More information about Paradise
More information on attributes
Identifying DHIs using SOM
Identifying thin beds / interpreting below tuning
Identifying geobodies using SOM
Something else...
Just looking around

Please tell us a bit about yourself so that we can provide the right information.

Your Role

Geoscience manager
Geophysicist
Geologist
IT
Senior Manager
G&G Technology
Other

And where you work in the industry?

E&P company
Consulting
Student
Technology / Equipment company
Other
X

Send Message