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Machine Learning and Data Science in the Oil and Gas Industry - 1st Edition - ISBN: 9780128207147

Machine Learning and Data Science in the Oil and Gas Industry

1st Edition

Best Practices, Tools, and Case Studies

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Editor: Patrick Bangert
Paperback ISBN: 9780128207147
Imprint: Gulf Professional Publishing
Published Date: 1st January 2021
Page Count: 300
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Description

Machine Learning and Data Science in the Oil and Gas Industry: Best Practices, Tools, and Case Studies explains critical facets around machine learning that are specifically tailored to oil and gas. Practical in its approach, this reference provides a chapter devoted to the early career engineer that is just starting in the industry. It then builds to a full-scale project that is supported by real-world case studies from various industry and academic contributors. Lessons learned and technology drivers are also discussed, creating a path for future engineers to apply.

Rounding out with a glossary, this book delivers a reference that cuts through the hype to help today's petroleum engineers understand machine learning and where it can benefit their operations.

Key Features

  • Helps readers gain a practical understanding of machine learning used in oil and gas operations
  • Presents change management skills that will help readers gain confidence in pursuing new technology
  • Provides the workflow of a full scale project and where machine learning is and isn't impactful

Readership

Oil and gas industry expert and practitioner working either in exploration, drilling, completions, engineering, production, maintenance or management

Table of Contents

  1. Data Science, Statistics and Time-Series
    2. Machine Learning
    3. Introduction to Machine Learning in O&G
    4. Data Management from the DCS to the Historian
    5. Designing the Business Case
    6. Project Management for an ML Project
    7. Choosing the Right Methods and Tools (KPI on how to compare them)
    8. Integration of ML into Plant Architecture
    9. Quantification of Added-Value (benefit and limitations)
    10. Case Studies

Details

No. of pages:
300
Language:
English
Copyright:
© Gulf Professional Publishing 2021
Published:
1st January 2021
Imprint:
Gulf Professional Publishing
Paperback ISBN:
9780128207147

About the Editor

Patrick Bangert

Patrick Bangert is founder and CEO of Algorithmica Technologies, providing real-time process modeling, optimization and predictive maintenance solutions to the process industry with a focus on chemistry and power generation. He is also CTO of APO Offshore Inc, a leading data analytics company responsible for developing predictive maintenance techniques in the O&G industry. His doctorate from UCL specialized in Applied Mathematics, and his academic positions at NASA jet propulsion laboratory and Los Alamos National Laboratory made use of optimization and machine learning for magnetohydrodynamics and particle accelerator experiments. He has published extensively across optimization and machine learning, and relevant applications in the real world.

Affiliations and Expertise

CEO Algorithmica Technologies, Cupertino, California, USA

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