John Wiley & Sons Artificial Intelligence and Data Analytics for Energy Exploration and Production Cover ARTIFICAL INTELLIGENCE AND DATA ANALYTICS FOR ENERGY EXPLORATION AND PRODUCTION This groundbreaking.. Product #: 978-1-119-87969-5 Regular price: $214.02 $214.02 In Stock

Artificial Intelligence and Data Analytics for Energy Exploration and Production

Aminzadeh, Fred / Temizel, Cenk / Hajizadeh, Yasin


1. Edition November 2022
608 Pages, Hardcover
Wiley & Sons Ltd

ISBN: 978-1-119-87969-5
John Wiley & Sons

Further versions



This groundbreaking new book is written by some of the foremost authorities on the application of data science and artificial intelligence techniques in exploration and production in the energy industry, covering the most comprehensive and updated new processes, concepts, and practical applications in the field.

The book provides an in-depth treatment of the foundations of Artificial Intelligence (AI) Machine Learning, and Data Analytics (DA). It also includes many of AI-DA applications in oil and gas reservoirs exploration, development, and production. The book covers the basic technical details on many tools used in "smart oil fields". This includes topics such as pattern recognition, neural networks, fuzzy logic, evolutionary computing, expert systems, artificial intelligence machine learning, human-computer interface, natural language processing, data analytics and next-generation visualization. While theoretical details will be kept to the minimum, these topics are introduced from oil and gas applications viewpoints.

In this volume, many case histories from the recent applications of intelligent data to a number of different oil and gas problems are highlighted. The applications cover a wide spectrum of practical problems from exploration to drilling and field development to production optimization, artificial lift, and secondary recovery. Also, the authors demonstrate the effectiveness of intelligent data analysis methods in dealing with many oil and gas problems requiring combining machine and human intelligence as well as dealing with linguistic and imprecise data and rules.

Fred Aminzadeh is an expert in artificial intelligence and energy. He was professor at the University of Houston and University of Southern California. He worked at dGB, Unocal (now part of Chevron) and Bell Laboratories. His work experience includes fossil energy, geothermal energy, and carbon sequestration. He served as the president of Society of Exploration Geophysicists. He has authored over 15 books and holds several patents. He was the editor in chief of The Journal of Sustainable Energy Engineering. Currently, he is president of FACT, an energy services company. He is also a member of technical advisory board of DOE/NETL's SMART initiative and an adjunct Professor at the University of Wyoming.

Cenk Temizel is a Sr. Reservoir Engineer with Saudi Aramco. He has over 15 years of experience in reservoir simulation, data analytics, smart fields, unconventional, enhanced oil recovery with Aera Energy, Schlumberger, and Halliburton in the Middle East, the U.S., and the U.K. He is the recipient of the Aramco Unconventional Resources Technical Contribution Award (2020), 2nd place at SPE Global R&D Competition at ATCE 2014, and the Halliburton Applause Award in Innovation (2012). He holds an MS degree in Petroleum Engineering from University of Southern California and was a research assistant at Stanford University before joining the industry.

Yasin Hajizadeh is the founder and CEO of nowos, a boutique Texas based technology consulting firm with a focus on software product management and workforce development planning for industry 4.0. Previously, he was a program and product manager of Azure ML and IoT at Microsoft. Yasin has also worked for Schlumberger as a data scientist and reservoir engineer, University of Calgary as an associate professor of computer science, and CMG as an optimization and uncertainty quantification scientist. He holds a PhD in petroleum engineering from Heriot-Watt University, and a Masters in technology management from Memorial University of Newfoundland.