Artificial Intelligence for a More Sustainable Oil and Gas Industry and the Energy Transition: Case Studies and Code Examples presents a package for academic researchers and industries working on water resources and carbon capture and storage. This book contains fundamental knowledge on artificial intelligence related to oil and gas sustainability and the industry’s pivot to support the energy transition and provides practical applications through case studies and coding flowcharts, addressing gaps and questions raised by academic and industrial partners, including energy engineers, geologists, and environmental scientists. This timely publication provides fundamental and extensive information on advanced AI applications geared to support sustainability and the energy transition for the oil and gas industry.
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Table of Contents
1. Artificial Intelligence (AI) Overview2. Machine Learning (ML)
3. Classification
4. Regression
5. Clustering
6. Semi Supervised Learning Methods
7. Modern Machine Learning Methods
8. Reinforcement Learning
9. Deep Learning
10. AI Applications in Energy Transition and Decarbonization
11. Future Trends
Appendices
A. Statistical Performance Indexes
B. Python Programming Introduction
C. Case Studies Data Base
D. Structured Query Language (SQL) Basics