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Understanding data analytics and predictive modelling in the oil and gas industry
Hardback
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- Book Synopsis
- 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.
- About The Author
- Kingshuk Srivastava is working as a faculty at UPES, Dehradun, India with over 12 years of extensive experience of Data Analytics in the field of Oil and Gas sector. He has earned his Ph.D in Computer Science Engineering from UPES and his field of research is in AI, Data Science and NOSQL databases. He has designed, developed, and delivered training to Birlasoft Technologies on different IT aspects in Oil & Gas value chain. He has published multiple papers in his field of interest in national and international journals.Thipendra P Singh is currently positioned as a Professor in the School of Computer Science Engg & Technology, Bennett University, Greater Noida, NCR, India. Prior to this, he has been associated with UPES University and Sharda University. He holds Doctorate in Computer Science from Jamia Millia Islamia University, New Delhi. He carries 26 years of rich experience with him. He is supervising PhD scholars with French and UK universities also. He has been a widely traveled academician and participated at various platforms across the countries including UK, France, UAE, and Singapore. He has been the editor of 10 books on various allied topics of Computer Science. Dr. Singh is a senior member of IEEE and a member of various other professional bodies including IEI, ACM, EAI, ISTE, IAENG etc., and also on the editorial/reviewer panel of different journals. He is a fellow of IETA-India since 2019. He is also on the board of studies of different Indian and abroad UniversitiesManas Ranjan Pradhan holds a PhD (Computer Science) from University of Mysore, India, and Master of Technology (Computer Science) from Utkal university, India. He has vast experience in teaching, research, and academic administration in India and abroad. He is currently working at Skyline University College, Sharjah, UAE. He has been associating with IT industry for industry-academic collaboration, internship, placement, and workshops. He has executed IBM Center of Education for Cloud Computing and Business Analytics at INTI International University, Malaysia under Laureate International Universities, USA. He has presented and published many research papers in various conferences and journals. He has 3 Indian patents and 3 Australian patents to his credit. His areas of expertise are Business Analytics, Datamining, Data warehouse, Retail/Ecommerce Analytics, Artificial Intelligence, Machine Learning and Business process modeling.Dr Vinit Kumar Gunjan is Associate Professor in Department of Computer Science & Engineering and Dean of Academic affairs at CMR Institute of Technology Hyderabad. He has published research papers in IEEE, Elsevier & Springer Conferences, authored several books and edited volumes of Springer series, most of which are indexed in SCOPUS database.
- Product Details
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- ISBN
- 9781032413877
- Format
- Hardback
- Publisher
- CRC Press, (20 November 2023)
- Number of Pages
- 168
- Weight
- 620 grams
- Language
- English
- Dimensions
- 234 x 244 x 19 mm
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