This book presents data driven approaches to improve drilling performance in geothermal, coiled tubing, and conventional operations. It begins with transformer models for forecasting rate of penetration in geothermal wells, followed by methods for predicting both penetration and downhole shock in coiled tubing drilling. A variational autoencoder framework is introduced for diagnosing resistivity tool anomalies to support reliable geosteering. Subsequent chapters examine the use of deep aut...

Seismic imaging is a key component of subsurface exploration, and it depends on a high-quality seismic data acquisition system with effective seismic processing algorithms. Seismic data quality concerns various factors such as acquisition design, environmental constraints, sampling resolution, and noises. The focus of this book is to investigate efficient seismic data representation and signal enhancement solutions by leveraging the powerful feature engineering capability of deep learning....

This book presents a comprehensive introduction to well logging and the inverse problem. It explores challenges such as conventional data processing methods’ inability to handle local minima issues, and presents the explanations in an easy-to-follow way.The book describes statistical data interpretation by introducing the fundamentals behind the approach, as well as a range of sampling methods. In each chapter, a specific method is comprehensively introduced, together with represen...