
Artificial Intelligence and Data Analytics for Energy Exploration and Production
- English
- PDF
- Available on iOS & Android
Artificial Intelligence and Data Analytics for Energy Exploration and Production
About this book
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.
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Information
Table of contents
- Cover
- Title Page
- Copyright Page
- Dedication Page
- Contents
- Foreword
- Preface
- Chapter 1 Introduction to Modern Intelligent Data Analysis
- Chapter 2 Machine Learning and Human Computer Interface
- Chapter 3 Artificial Neural Networks
- Chapter 4 Fuzzy Logic
- Chapter 5 Integration of Conventional and Unconventional Methods
- Chapter 6 Natural Language Processing
- Chapter 7 Data Science and Big Data Analytics
- Chapter 8 Applications of Machine Learning in Exploration
- Chapter 9 Applications in Oil and Gas Drilling
- Chapter 10 Applications in Reservoir Characterization and Field Development Optimization
- Chapter 11 Machine Learning Applications in Production Forecasting
- Chapter 12 Applications in Production Optimization, Well Completion and Stimulation
- Chapter 13 Machine Learning Applications in Reservoir Engineering and Reservoir Simulation
- Chapter 14 Machine Learning Applications in Artificial Lift
- Chapter 15 Machine Learning Applications in Enhanced Oil Recovery (EOR)
- Chapter 16 Conclusions and Future Directions
- References
- Index
- EULA