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Significant Advancements in Seismic Reservoir Characterization with Machine Learning

SPE Norway
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The application of machine learning to classify seismic attributes at single sample resolution is producing results that reveal more reservoir ...
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Self Organizing Map SOM - Attributes

Using Self-Organizing Maps to Explore the Yegua in the Texas Gulf Coast

Geophysical Insights
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Exploring shallow Yegua formation as an independent method to accurately identify anomalies and exposing direct hydrocarbon indicators using Self-Organizing Map ...
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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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How Self-Orgazining Maps (SOM) and Principal Componenrt Analysis (PCA) greatly enhances the interpretation process to identify geology in diffferent settings ...
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