Machine Learning and Data Science in the Oil and Gas Industry
eBook - ePub

Machine Learning and Data Science in the Oil and Gas Industry

Best Practices, Tools, and Case Studies

  1. 306 pages
  2. English
  3. ePUB (mobile friendly)
  4. Only available on web
eBook - ePub

Machine Learning and Data Science in the Oil and Gas Industry

Best Practices, Tools, and Case Studies

Book details
Table of contents
Citations

About This Book

Machine Learning and Data Science in the Oil and Gas Industry explains how machine learning can be specifically tailored to oil and gas use cases. Petroleum engineers will learn when to use machine learning, how it is already used in oil and gas operations, and how to manage the data stream moving forward. Practical in its approach, the book explains all aspects of a data science or machine learning project, including the managerial parts of it that are so often the cause for failure. Several real-life case studies round out the book with topics such as predictive maintenance, soft sensing, and forecasting. Viewed as a guide book, this manual will lead a practitioner through the journey of a data science project in the oil and gas industry circumventing the pitfalls and articulating the business value.

  • Chart an overview of the techniques and tools of machine learning including all the non-technological aspects necessary to be successful
  • Gain practical understanding of machine learning used in oil and gas operations through contributed case studies
  • Learn change management skills that will help gain confidence in pursuing the technology
  • Understand the workflow of a full-scale project and where machine learning benefits (and where it does not)

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Yes, you can access Machine Learning and Data Science in the Oil and Gas Industry by Patrick Bangert in PDF and/or ePUB format, as well as other popular books in Physical Sciences & Energy. We have over one million books available in our catalogue for you to explore.

Information

Publisher
Gulf Professional Publishing
Year
2021
ISBN
9780128209141
Topic
Physical Sciences
Subtopic
Energy

Table of contents

  1. Cover
  2. Dedication
  3. Title page
  4. Contents
  5. Copyright
  6. Contributors
  7. Foreword
  8. Chapter 1: Introduction
  9. Chapter 2: Data Science, Statistics, and Time-Series
  10. Chapter 3: Machine Learning
  11. Chapter 4: Introduction to Machine Learning in the Oil and Gas Industry
  12. Chapter 5: Data Management from the DCS to the Historian
  13. Chapter 6: Getting the Most Across the Value Chain
  14. Chapter 7: Project Management for a Machine Learning Project
  15. Chapter 8: The Business of AI Adoption
  16. Chapter 9: Global Practice of AI and Big Data in Oil and Gas Industry
  17. Chapter 10: Soft Sensors for NOx Emissions
  18. Chapter 11: Detecting Electric Submersible Pump Failures
  19. Chapter 12: Predictive and Diagnostic Maintenance for Rod Pumps
  20. Chapter 13: Forecasting Slugging in Gas Lift Wells
  21. Index