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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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Seismic Interpretation Below Tuning with Multi-Attribute Analysis

Geophysical Insights
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This international webinar describes how multi-attribute seismic analysis is applied using the Paradise software to visualize thin beds and facies ...
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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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Advantages of Machine Learning with Multi Attribute Seismic Surveys Thumbnail-01

Advantages of Machine Learning with Multi-Attribute Seismic Surveys

Geophysical Insights
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Dr. Tom Smith explains the advantages of using machine learning to analyze multiple attributes of seismic surveys simultaneously, including specific ...
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Geobody Interpretation Figure 1

Geobody Interpretation Through Multi-Attribute Surveys, Natural Clusters and Machine Learning

Geophysical Insights
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This paper sets out a unified mathematical framework for the process from seismic samples to geobodies ...
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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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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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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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