Artificial Intelligence in the Energy Industry Theory, Case Studies, and Applications

This comprehensive resource bridges the knowledge gap in applying modern artificial intelligence and machine learning methods to the petroleum sector. It explores how AI, 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 IoT applications, as well as more traditional areas such as drilling optimization and enhanced recovery operations. * Provides readers with downloadable Python codes for several chapters. 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.