Resource Library

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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identify reservoir rock

Net Reservoir Discrimination through Multi-Attribute Analysis at Single Sample Scale

First Break
Published in the special Machine Learning edition of First Break, this paper lays out results from multi-attribute analysis using Paradise, ...
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Seismic Interpretation Below Tuning with Multiattribute Analysis figure 10

Seismic Interpretation Below Tuning with Multi-attribute Analysis

The Leading Edge
Seismic interpretation of thin beds below tuning has always been a challenge in the oil and gas industry. A multi-attribute ...
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multi attribute analysis for unconventionals

Attribute Analysis in Unconventional Resource Plays Using Unsupervised Neural Networks

Geophysical Insights
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A case study of 10 square mile Eagle Ford Shale Trend utilizing machine learning in Paradise to apply inversion and ...
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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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Unsupervised Machine Learning Techniques for Subtle Thumbnail

Unsupervised Machine Learning Techniques for Subtle Fault Detection

First Break
In this paper, authors suggest a workflow that enables interpreters to apply principal component analysis (PCA) and self- organizing maps ...
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systematic workflow for reservoir thumbnail

Systematic Workflow for Reservoir Characterization in Northwestern Colombia using Multi-attribute Classification

First Break
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A workflow is presented which includes data conditioning, finding the best combination of attributes for ML classification aided by Principal ...
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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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