Resource Library

3D Volume

Using Self-Organizing Maps to Define Seismic Facies

Geophysical Insights
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Using multiple attributes to evaluate a 3D volume in offshore South America containing unexpected high pressure zone and the application ...
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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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Som Results B.2

Geologic Pattern Recognition from Seismic Attributes: Principal Component Analysis and Self-Organizing Maps

Interpretation Journal
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Analyzing seismic data through geologic pattern recognition methods like Self-Organizing Maps (SOM) and Principal Component Analysis (PCA) in Paradise machine ...
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SOM

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

Geophysical Society of Houston (GSH)
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Unsupervised neural network searches multi-dimensional data for natural clusters. Neurons are attracted to areas of higher information density. The SOM ...
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Seismic Attributes for Attenuation

Using Self Organizing Maps to Expose Direct Hydrocarbon Indicators

Geophysical Insights
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Utilizing machine learning in Paradise to define and reveal features not seen in conventional interpretation in an offshore Gulf of ...
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BEG Line 53 Full Classification - Copy

Self-Organizing Neural Nets for Automatic Anomaly Identification

Geophysical Insights
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Self-organizing maps are a type of unsupervised neural network which fit themselves to the pattern of information in multi-dimensional data ...
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Machine learning for detailed reservoir — Wisting case study Featured

A multi-disciplinary approach to establish a workflow for the application of machine learning for detailed reservoir description – Wisting case study

First Break
Sharareh Manouchehri, Nam Pham, Terje A. Hellem and Rocky Roden predict lithofacies and reservoir properties using multi-attribute seismic analysis based ...
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Image for machine learning presentation 2018

Comparison of Seismic Amplitude to SOM Classification

Geophysical Insights
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Compare traditional seismic interpretation results with SOM (Self-Organizing Maps) classification achieved with machine learning in Paradise software ...
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Honeycomb Default

Machine Learning Terms

Geophysical Insights
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A glossary defining essential machine learning terms within the seismic interpretation and geoscience community from Principal Component Analysis (PCA) to ...
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