Rocky Roden

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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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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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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Making Sense of Machine Learning

Geophysical Insights
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Machine Learning is revolutionizing geoscience and the Oil and Gas industry. As an interpreter, Rocky Roden, explores how machine learning ...
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wiggle trace seismic data

Significant Advancements in Seismic Reservoir Characterization with Machine Learning

SPE Norway
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Geophysicists, Rocky Roden & Patricia Santogrossi, discuss machine learning applications enabling refined assessment of thin beds and DHI characteristics ...
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Seismic Interpretation of DHI Characteristics with Machine Learning

Geophysical Insights
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The accurate interpretation of DHI characteristics has proven to significantly improve the success rates of drilling commercial wells. In this ...
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Conventional Stacked Seismic Amplitude Display

Interpretation of DHI Characteristics with Machine Learning

First Break
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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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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 Attributes for Attenuation

Using Self Organizing Maps to Expose Direct Hydrocarbon Indicators

Geophysical Insights
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Utilizing machine learning in Paradise to define and reveal features not seen in conventional interpretation in an offshore Gulf of ...
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