Artificial Intelligence in the Energy Industry
Theory, Case Studies, and Applications
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81 217 Ft
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Product details:
- Edition number 1
- Publisher CRC Press
- Date of Publication 23 March 2026
- ISBN 9781041020073
- Binding Hardback
- No. of pages730 pages
- Size 234x156 mm
- Weight 453 g
- Language English
- Illustrations 39 Illustrations, black & white; 31 Halftones, black & white; 8 Line drawings, black & white; 13 Tables, black & white 700
Categories
Short description:
This comprehensive resource bridges the knowledge gap in applying modern AI and ML methods to the petroleum sector. It explores how AI, ML, and data analytics enhance efficiency, safety, and productivity in operations across the oil and gas value chain, like exploration, drilling, production, reservoir management, and renewables integration.
MoreLong description:
This comprehensive resource bridges the knowledge gap in applying modern artificial intelligence and machine learning methods to the petroleum sector. It explores how artificial intelligence (AI), machine learning (ML), and data analytics enhance efficiency, safety, and productivity in operations across various segments of the oil and gas value chain, including exploration, drilling, production, reservoir management, and renewables integration.
• Covers theoretical and practical aspects of AI/ML applications, from foundational concepts to advanced techniques.
• Features examples and A-to-Z practical workflows, empowering readers to apply what they learn directly to real-world challenges.
• Includes 500 international case studies, highlighting real-world successes, challenges, and lessons learned from a global perspective.
• Offers insights into emerging technologies like Industry 4.0, digital twins, smart fields, and Internet of Things applications, as well as more traditional areas such as drilling optimization and enhanced recovery operations.
With the growing importance of advanced data-driven approaches, this book provides value to both technical professionals looking for hands-on solutions and academics seeking a well-structured textbook for advanced studies.
MoreTable of Contents:
0. Front Matter. 1. Theory and Background on Artificial Intelligences and Machine Learning Methods. 2. AI Applications in Reservoir Characterization, Geology, and Geophysics. 3. AI Applications in Drilling Engineering. 4. AI Applications in Reservoir Engineering Management. 5. AI Applications in Well Completion, Production, Stimulation. 6. AL Applications in Enhanced Recovery. 7. AI Applications in Facilities, Pipelines, Metering. 8. AI Applications in Unconventionals. 9. AI Applications in Fourth Industry Revolution. 10. AI Applications in Renewable Resources. 11. Future Directions in AI Applications in the Energy Industry.
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