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.
| ISBN: | 9780128207147 |
| Publication date: | 8th March 2021 |
| Author: | Patrick Bangert |
| Publisher: | Gulf Professional Publishing an imprint of Elsevier Science |
| Format: | Paperback |
| Pagination: | 306 pages |
| Genres: |
Fossil fuel technologies Petroleum technology Artificial intelligence Energy industries and utilities |
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.
Machine Learning and Data Science in the Oil and Gas Industry features in the following genres: Fossil fuel technologies, Petroleum technology, Artificial intelligence, Energy industries and utilities
Paperback. Not Available.
Machine Learning and Data Science in the Oil and Gas Industry was written by Patrick Bangert and published by Gulf Professional Publishing an imprint of Elsevier Science
Machine Learning and Data Science in the Oil and Gas Industry has 306 pages