Farhan Hussain, Razin (PhD Candidate, University of Louisiana at Lafayette, Lafayette, LA, USA)

IoT for Smart Operations in the Oil and Gas Industry: From Upstream to Downstream Farhan Hussain, Razin (PhD Candidate, University of Louisiana at Lafayette, Lafayette, LA, USA)

The oil and gas industry look for ways to utilize machine learning, AI, and more advanced computing technologies to improve their operations. IoT for Smart Operations in the Oil and Gas Industry elaborates on how the synergy between state-of-the-art computing platforms, such as Internet of Things (IOT), cloud computing and artificial intelligence, in particular modern machine learning methods, can be harnessed to serve the purpose of a more efficient oil and gas industry. The reference explores the operations performed in each sector of the industry and then introduces the computing platforms and advanced technologies that can enhance the operation, lower costs, and lower carbon footprint. Safety and security content is included, in particular, cybersecurity and potential threats to smart oil and gas solutions, focusing on adversarial effects of smart solutions, problems resulted from interference of smart solutions, and problems related to the interoperability of human-machine intelligence in the context of oil and gas industry. Detailed case studies are included throughout to learn and research for further application. Covering the latest topics and solutions, IoT for Smart Operations in the Oil and Gas Industry delivers a much-needed reference for the engineer and manager to understand upcoming computing technologies for the oil and gas industry.