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

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.

Machine Learning and Data Science in the Oil and Gas Industry 

• 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)

Machine Learning and Data Science in the Oil and Gas Industry: Best Practices, Tools, and Case Studies and published by Gulf Professional Publishing. The Digital and eTextbook ISBNs for Machine Learning and Data Science in the Oil and Gas Industry are 9780128209141, 0128209143 and the print ISBNs are 9780128207147, 0128207140. Save up to 80% versus print by going digital with VitalSource.