Description

Book Synopsis


Table of Contents
Part 1: Traditional Machine Learning Approaches 1. User Vs. Machine Seismic Attribute Selection for Unsupervised Machine Learning Techniques: Does Human Insight Provide Better Results Than Statistically Chosen Attributes? 2. Relative Performance of Support Vector Machine, Decision Trees, and Random Forest Classifiers for Predicting Production Success in US unconventional Shale Plays Part 2: Deep Learning Approaches 3. Recurrent Neural Network: application in facies classification 4. Recurrent Neural Network for Seismic Reservoir Characterization 5. Application of Convolutional Neural Networks for the Classification of Siliciclastic Core Photographs 6. Convolutional Neural Networks for Fault Interpretation – Case Study Examples around the World Part 3: Physics-based Machine Learning Approaches 7. Scientific Machine Learning for Improved Seismic Simulation and Inversion 8. Prediction of Acoustic Velocities using Machine Learning 9. Regularized Elastic Full Waveform Inversion using Deep Learning 10. A Holistic Approach to Computing First-arrival Traveltimes using Neural Networks Part 4: New Directions 11. Application of Artificial Intelligence to Computational Fluid Dynamics

Advances in Subsurface Data Analytics

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A Paperback by Shuvajit Bhattacharya, Haibin Di

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    View other formats and editions of Advances in Subsurface Data Analytics by Shuvajit Bhattacharya

    Publisher: Elsevier Science
    Publication Date: 5/20/2022 12:00:00 AM
    ISBN13: 9780128222959, 978-0128222959
    ISBN10: 0128222956
    Also in:
    Operational research Computing Enterprise software

    Description

    Book Synopsis


    Table of Contents
    Part 1: Traditional Machine Learning Approaches 1. User Vs. Machine Seismic Attribute Selection for Unsupervised Machine Learning Techniques: Does Human Insight Provide Better Results Than Statistically Chosen Attributes? 2. Relative Performance of Support Vector Machine, Decision Trees, and Random Forest Classifiers for Predicting Production Success in US unconventional Shale Plays Part 2: Deep Learning Approaches 3. Recurrent Neural Network: application in facies classification 4. Recurrent Neural Network for Seismic Reservoir Characterization 5. Application of Convolutional Neural Networks for the Classification of Siliciclastic Core Photographs 6. Convolutional Neural Networks for Fault Interpretation – Case Study Examples around the World Part 3: Physics-based Machine Learning Approaches 7. Scientific Machine Learning for Improved Seismic Simulation and Inversion 8. Prediction of Acoustic Velocities using Machine Learning 9. Regularized Elastic Full Waveform Inversion using Deep Learning 10. A Holistic Approach to Computing First-arrival Traveltimes using Neural Networks Part 4: New Directions 11. Application of Artificial Intelligence to Computational Fluid Dynamics

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