Tom Smith

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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Machine Learning Essentials Course

NEW e-Course by Dr. Tom Smith: Machine Learning Essentials for Seismic Interpretation

Geophysical Insights
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Dr. Tom Smith presents an e-course on Machine Learning Essentials for Seismic Interpretation originally hosted by the Geophysical Society of ...
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The Holy Grail of Machine Learning in Seismic Interpretation

Geophysical Society of Houston (GSH)
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Dr. Tom Smith shares the "Holy Grail" of Machine Learning in Seismic Interpretation with the Geophysical Society of Houston ...
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Geobodies in Paradise: a Machine Learning Application

Geophysical Insights
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Dr. Tom Smith presents "Geobodies in Paradise: a Machine Learning Application" at the 2018 SEG Convention in Anaheim, California. Dr ...
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Machine Learning Essentials for Seismic Interpretation | Geophysical Society of Houston (GSH) Webinar

Geophysical Insights
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A Live Webinar featuring, Dr. Tom Smith, President & CEO, Geophysical Insights - Machine Learning Essentials for Seismic Interpretation ...
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Machine Learning Revolutionizing Seismic Interpretation

American Oil and Gas Reporter (AOGR)
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Machine learning is enabling a new world of seismic interpretation as oil and gas activity pivots toward a new phase ...
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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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Machine Learning – The Next Generation Seismic Interpretation

Geophysical Insights
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In the oil and gas exploration and reservoir replacement business – particularly at this time – we “must” place neural ...
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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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