Digitalized Drilling Systems: Modeling, Automation and Control
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Beschreibung
This book presents a comprehensive and accessible guide to how data, mathematical modeling, control engineering, and intelligent systems work together to create safer, more efficient, and increasingly autonomous drilling operations. Modern drilling operations are undergoing a profound transformation driven by digital technology, automation, and artificial intelligence.
Rather than treating drilling as a purely mechanical process, the book introduces a systems-based perspective. It explains how raw sensor data is converted into reliable information, how engineering models are developed and validated, and how advanced control strategies such as PID, optimal control, and model predictive control are implemented in real time. Building on this foundation, the book explores modern developments including digital twins, machine learning, reinforcement learning, and AI-assisted decision support.
A distinctive feature of the book is its layered architecture approach, which clearly connects data quality, modeling, control, optimization, and intelligent automation into a unified framework. Rich illustrations, structured workflows, practical examples, and carefully designed problems support understanding across disciplines.
By bridging traditional engineering with emerging AI technologies, this book provides readers with both foundational knowledge and a forward-looking roadmap toward intelligent and autonomous energy.
This book presents a comprehensive and accessible guide to how data, mathematical modeling, control engineering, and intelligent systems work together to create safer, more efficient, and increasingly autonomous drilling operations. Modern drilling operations are undergoing a profound transformation driven by digital technology, automation, and artificial intelligence.
Rather than treating drilling as a purely mechanical process, the book introduces a systems-based perspective. It explains how raw sensor data is converted into reliable information, how engineering models are developed and validated, and how advanced control strategies such as PID, optimal control, and model predictive control are implemented in real time. Building on this foundation, the book explores modern developments including digital twins, machine learning, reinforcement learning, and AI-assisted decision support.
A distinctive feature of the book is its layered architecture approach, which clearly connects data quality, modeling, control, optimization, and intelligent automation into a unified framework. Rich illustrations, structured workflows, practical examples, and carefully designed problems support understanding across disciplines.
By bridging traditional engineering with emerging AI technologies, this book provides readers with both foundational knowledge and a forward-looking roadmap toward intelligent and autonomous energy.
Explains modern drilling by bringing together data, modeling, control, and AI Shows how real time automation, digital twins, and machine learning transform drilling safety and efficiency Makes complex engineering concepts accessible through layered architecture, workflows, and practical examples
Autor*in
Dan Sui
Themen in »Digitalized Drilling Systems: Modeling, Automation and Control«
Drilling Automation Drilling Control Systems Drilling Data Management Drilling Models Drilling Intelligence Drilling Optimization Digital Twin Machine Learning Autonomous Systems