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Webinar Intro Tao Zhao 20Mar2019

Applications of Convolutional Neural Networks (CNN) to Seismic Interpretation

Geophysical Insights
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As part of our quarterly series on machine learning, we were delighted to have had Dr. Tao Zhao present applications ...
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Future of Seismic Interpretation with Machine Learning and Deep Learning

Future of Seismic Interpretation with Machine Learning and Deep Learning

Geophysical Insights
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By: Iván Marroquín, Ph.D. - Senior Research Geophysicist I am very excited to participate as a speaker in the workshop ...
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Neural Network Classification

Unsupervised vs. Supervised classifiers – Comparing classification results

Geophysical Insights
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By: Ivan Marroquin, Ph.D. - Senior Research Geophysicist In machine learning, there is a very interesting challenge in comparing the ...
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Comparison of Seismic Inversion and SOM Seismic Multi-Attribute Analysis

Comparison of Seismic Inversion and SOM Seismic Multi-Attribute Analysis

Geophysical Insights
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Self-Organizing Maps (SOM) is a relatively new approach for seismic interpretation in our industry and should not be confused with ...
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Austin chalk SOM image

The Value of Instantaneous Attributes

American Oil and Gas Reporter (AOGR)
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Self-Organizing Maps (SOM) is a relatively new approach for seismic interpretation in our industry and should not be confused with ...
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Thumbnail of colorful neurons

Machine Learning – The Next Generation Seismic Interpretation

American Oil and Gas Reporter (AOGR)
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Most people associate neural networks, big data and big number crunching as parts of a single paradigm for access to ...
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Image of truck

Machine Learning and Truck Driving

American Oil and Gas Reporter (AOGR)
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Every day, 2.5 quintillion bytes of data get created and in the last two years, 90% of the world's data ...
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