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60th Annual Exploration Meeting

Applications of Machine Learning for Geoscientists – Permian Basin

Geophysical Insights
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Carrie Laudon, Senior Geoscience Consultant with Geophsyical Insights, explores new Machine Learning applications in E&P for geoscientists in the Permian ...
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Significant Advancements in Seismic Reservoir Characterization with Machine Learning

SPE Norway
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The application of machine learning to classify seismic attributes at single sample resolution is producing results that reveal more reservoir ...
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Seismic Interpretation Below Tuning with Multiattribute Analysis

Seismic Interpretation Below Tuning with Multiattribute Analysis

The Leading Edge
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Applying Self-Organizing Maps (SOM) and Principal Component Analysis (PCA) in sub-seismic resolution to reveal facies and shale ...
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Eagle Ford Case Study

Houston Geological Society (HGS)
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Latest Technology for Seismic Interpretation: Direct detection & delineation of facies architecture in the Eagle Ford Group or How did ...
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2D Color Map

First Steps in the Sub-Seismic Resolution of the Eagle Ford, Part I

Geophysical Insights
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Using machine learning to analyze 5 instantaneous attributes helped reveal patterns across 5 instantaneous attributes and unique Eagle Ford facies ...
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Detailed Sub-Seismic Resolution in the Eagle Ford Shale and Identification of Under-Explored Geobodies, Part 2

Detailed Sub-Seismic Resolution in the Eagle Ford Shale and Identification of Under-Explored Geobodies, Part 2

Geophysical Insights
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Results of a Self-Organizing Map (SOM) of many instantaneous attributes to reveal different types of facies and shale that apply ...
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Resolution of Faults in the Eagle Ford, Part 3

Resolution of Faults in the Eagle Ford, Part 3

Geophysical Insights
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Applying Principal Component Analysis (PCA) and Self-Organizing Map (SOM) process to show faults on the base amplitude seismic survey and ...
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Stratigraphic and Structural Resolution Using Instantaneous Attributes on Spectral Decomp Sub-Bands, Buda and Austin Chalk Formations, Part 4

Stratigraphic and Structural Resolution Using Instantaneous Attributes on Spectral Decomp Sub-Bands, Buda and Austin Chalk Formations, Part 4

Geophysical Insights
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Concurrent analysis of multiple attributes through machine learning to spectral decomposition sub-bands and other geology that apply attributes for stratigraphic ...
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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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