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AI and Blockchain Applications in the Oil and Gas Industry

Shashi Bhushan Fasee Ullah Hilmi Hasan

$406.95   $325.64

Paperback

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English
Business Science Reference
19 March 2026
The convergence of artificial intelligence (AI) and blockchain is reshaping the oil and gas industry, offering innovative solutions to longstanding operational and safety challenges. As companies face increasing pressure to reduce environmental impact and improve transparency across complex supply chains, these technologies provide powerful tools for data-driven decision-making and secure, decentralized information management. These emerging technologies are transforming exploration and logistics ultimately driving greater efficiency and sustainability in an evolving global energy landscape. AI and Blockchain Applications in the Oil and Gas Industry explores how AI and blockchain are reshaping the oil and gas industry. This book explains how these technologies enhance supply chain transparency, reduce costs, and improve sustainability within this sector. Covering topics such as AI, blockchain, and industries, this book is an excellent resource for industry professionals, technology developers, investors, and academicians.
Edited by:   , ,
Imprint:   Business Science Reference
Country of Publication:   United States
Dimensions:   Height: 254mm,  Width: 178mm, 
ISBN:   9798337354583
Pages:   342
Publication Date:  
Audience:   College/higher education ,  Professional and scholarly ,  Primary ,  Undergraduate
Format:   Paperback
Publisher's Status:   Active

Fasee Ullah is currently working as an Associate Professor with the Department of Computing, Universiti Teknologi PETRONAS, Seri Iskandar, Perak Darul Ridzuan, Malaysia. He received a Ph.D. degree from the Faculty of Computing, Universiti Teknologi Malaysia (UTM), Malaysia. He has also completed the postdoctoral fellowship from the University of Macau, Macao, the academic talented program of the Government of Macau. He has published many research papers in reputed impact factor journals and conferences. He was a recipient of the Chancellor Award and the Best Student Award at UTM during his Ph.D. degree. His research interests include cloud security, cybersecurity, Computer Forensics, information security, smart hash security designing, cognitive smart cities, big data analytics, WBAN, deep learning, and IoT. He is currently providing reviewing services to IEEE Transactions journals, IEEE Access, ACM, Scientific Reports, and so on.

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