Understanding Data Analytics and Predictive Modelling in the Oil and Gas Industry

This book covers aspects of data science and predictive analytics used in 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 well, value chain integration, crude basket forecasting and so forth.

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.

Contributor: Kingshuk Srivastava (Edited by), Thipendra P Singh (Edited by), Manas Ranjan Pradhan (Edited by), Vinit Kumar Gunjan (Edited by)

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