FEATURED RESOURCES
Machine Learning is changing the way interpretation is done. Find out how geoscientists are using machine learning to reveal unprecedented levels of detail in seismic data.
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ATTRIBUTE SELECTION
Identify attributes having the highest variance and contribution among a set of attributes in a geologic setting
MULTI-ATTRIBUTE CLASSIFICATION
Classify multiple attribute volumes simultaneously utilizing Self-Organizing Maps (SOM), an unsupervised machine learning process
ATTRIBUTE GENERATION
Generate attributes to extract meaningful geological information and as input into machine learning analysis for advanced interpretation
MACHINE LEARNING (ML) GEOBODIES
Estimate the volume of reserves/resources and geologic features
DEEP LEARNING (DL) SEISMIC FACIES CLASSIFICATION
Capture seismic facies based on distinctive seismic amplitude patterns using deep learning technology
DEEP LEARNING (DL) FAULT DETECTION
Produce fault probability volumes based on already generated fault engines (models) or from interpreter guided trained engines
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