This book covers aspects of data science and predictive analytics used in the oil and gas industry by looking into the challenges of data processing and data modelling unique to this industry. It includes upstream management, intelligent/digital wells, value chain integration, crude basket forecasting, and so forth. It further discusses theoretical, methodological, well-established, and validated empirical work dealing with various related topics. Special focus has been given to experimental topics with various case studies. Features: Provides an understanding of the basics of IT technologies applied in the oil and gas sector Includes deep comparison between different artificial intelligence techniques Analyzes different simulators in the oil and gas sector as well as discussion of AI applications Focuses on in-depth experimental and applied topics Details different case studies for upstream and downstream This book is aimed at professionals and graduate students in petroleum engineering, upstream industry, data analytics, and digital transformation process in oil and gas.
| ISBN-13: | 9781032413877 |
| ISBN-10: | 1032413875 |
| Publisher: | Taylor & Francis Group |
| Publication date: | 2023-11-20 |
| Edition description: | 1 |
| Pages: | 168 |
| Product dimensions: | Height: 9.2098241 inches, Length: 6.1401452 inches, Weight: 1.09790206476 Pounds, Width: 0.61 inches |
| Author: | Kingshuk Srivastava, Thipendra P. Singh, Manas Ranjan Pradhan, Vinit Kumar Gunjan |
| Language: | en |
| Binding: | Hardcover |
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