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What Interpreters Should Know About Machine Learning

What Interpreters Should Know About Machine Learning

Geophysical Insights
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By Rocky Roden | May 2020 Introduction to Machine Learning for Interpreters ● Why Machine Learning now? ● Address terminology ...
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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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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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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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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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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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3D view of neurons

Machine Learning Applied to 3D Seismic Data from the Denver-Julesburg Basin Improves Stratigraphic Resolution in the Niobrara

Unconventional Resources Technology Conference
In a paper presented at URTeC 2019, Geophysical Insights uses Paradise machine learning software to improve resolution the reservoir intervals ...
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The Oil Industry's Cyber

The Oil Industry’s Cyber–Transformation Is Closer Than You Think

AAPG Explorer
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Dr. Tom Smith, President and CEO of Geophysical Insights, shares his predictions on the evolution of digital transformation in oil ...
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