Self-Organizing Map

SOM results defining hydrocarbon contacts

Seismic Interpretation with Machine Learning

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Today’s seismic interpreters must deal with enormous amounts of information, or ‘Big Data’, including seismic gathers, regional 3D surveys with ...
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seismic interpretation in the eagle ford, part 2 -01

Detailed Sub-Seismic Resolution in the Eagle Ford Shale and Identification of Under-Explored Geobodies, Part 2

Geophysical Insights
Results of a Self-Organizing Map (SOM) of many instantaneous attributes to reveal different types of facies and shale that apply ...
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Water Oil Contact - Conventional Multi-Attribute Analysis

Approach Aids Multiattribute Analysis

American Oil and Gas Reporter (AOGR)
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Seismic attributes help identify numerous geologic features in conventional seismic data. Applying principal component analysis can help interpreters identify seismic ...
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Time slice

Seismic Attribute Analysis Can Benefit From Unsupervised Neural Network

Offshore Magazine
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Process identifies anomalies from original data without bias using Unsupervised Neural Networks in Greenfield Exploration ...
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