Artificial Intelligence in the Energy Industry
Theory, Case Studies, and Applications
- Publisher's listprice GBP 170.00
-
76 755 Ft (73 100 Ft + 5% VAT)
The price is estimated because at the time of ordering we do not know what conversion rates will apply to HUF / product currency when the book arrives. In case HUF is weaker, the price increases slightly, in case HUF is stronger, the price goes lower slightly.
- Discount 20% (cc. 15 351 Ft off)
- Discounted price 61 404 Ft (58 480 Ft + 5% VAT)
- Discount is valid until: 30 June 2026
Subcribe now and take benefit of a favourable price.
Subscribe
69 080 Ft
Availability
Estimated delivery time: In stock at the publisher, but not at Prospero's office. Delivery time approx. 3-5 weeks.
Not in stock at Prospero.
Why don't you give exact delivery time?
Delivery time is estimated on our previous experiences. We give estimations only, because we order from outside Hungary, and the delivery time mainly depends on how quickly the publisher supplies the book. Faster or slower deliveries both happen, but we do our best to supply as quickly as possible.
Product details:
- Edition number 1
- Publisher CRC Press
- Date of Publication 24 March 2026
- ISBN 9781041020073
- Binding Hardback
- No. of pages730 pages
- Size 234x156 mm
- Weight 1510 g
- Language English
- Illustrations 39 Illustrations, black & white; 31 Halftones, black & white; 8 Line drawings, black & white; 13 Tables, black & white 690
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.
More
