Machine Learning and Data Science in the Oil and Gas Industry | Best Practices, Tools, and Case Studies

Patrick Bangert

ISBN 10: 0128207140 / ISBN 13: 9780128207147

Published by Gulf Professional Publishing, 2021

About this Item

Machine Learning and Data Science in the Oil and Gas Industry | Best Practices, Tools, and Case Studies | Patrick Bangert | Taschenbuch | Einband - fest (Hardcover) | Englisch | 2021 | Gulf Professional Publishing | EAN 9780128207147 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.

Seller Inventory # 118713064

Bibliographic Details

• Title: Machine Learning and Data Science in the Oil and Gas Industry | Best Practices, Tools, and Case Studies
• Publisher: Gulf Professional Publishing
• Publication Date: 2021
• Language: English
• ISBN 10: 0128207140
• ISBN 13: 9780128207147
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 13W x 152H x 229D millimeters 13 millimeters width by 152 millimeters height by 229 millimeters depth
• Weight: 473 grams
• Seller catalogs:
  • Bücher

About this title

Synopsis

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)

About the Author

Dr. Patrick Bangert is the Vice President of Artificial Intelligence at Samsung SDS where he leads both the AI software development and AI consulting groups that each provide various offerings to the industry. He is the founder and Board Chair 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. His doctorate from UCL specialized in applied mathematics, and his academic positions at NASA’s 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 their relevant applications in the real world.