Using multiple attributes to evaluate a 3D volume in offshore South America containing unexpected high pressure zone and the application of seismic attributes in a SOM to help define seismic facies and isolate the pressure zone.
Stratigraphic and Structural Resolution Using Instantaneous Attributes on Spectral Decomp Sub-Bands, Buda and Austin Chalk Formations, Part 4
Concurrent analysis of multiple attributes through machine learning to spectral decomposition sub-bands and other geology that apply attributes for stratigraphic and structural resolution.
Exploring shallow Yegua formation as an independent method to accurately identify anomalies and exposing direct hydrocarbon indicators using Self-Organizing Map (SOM) analysis to enhance conventional seismic interpretation to reveal anomalies.
Geologic Pattern Recognition from Seismic Attributes: Principal Component Analysis and Self-Organizing Maps
Current computing technology has allowed for the application of new machine learning techniques in analyzing seismic data through pattern recognition methods such as Self-Organizing Maps in Paradise.