Machine Learning Applications In Subsurface Energy Resource Management
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Machine Learning Applications in Subsurface Energy Resource Management
The utilization of machine learning (ML) techniques to understand hidden patterns and build data-driven predictive models from complex multivariate datasets is rapidly increasing in many applied science and engineering disciplines, including geo-energy. Motivated by these developments, Machine Learning Applications in Subsurface Energy Resource Management presents a current snapshot of the state of the art and future outlook for ML applications to manage subsurface energy resources (e.g., oil and gas, geologic carbon sequestration, and geothermal energy). Covers ML applications across multiple application domains (reservoir characterization, drilling, production, reservoir modeling, and predictive maintenance) Offers a variety of perspectives from authors representing operating companies, universities, and research organizations Provides an array of case studies illustrating the latest applications of several ML techniques Includes a literature review and future outlook for each application domain This book is targeted at practicing petroleum engineers or geoscientists interested in developing a broad understanding of ML applications across several subsurface domains. It is also aimed as a supplementary reading for graduate-level courses and will also appeal to professionals and researchers working with hydrogeology and nuclear waste disposal.
Machine Learning Applications in Subsurface Energy Resource Management
The utilization of machine learning (ML) techniques to understand hidden patterns and build data-driven predictive models from complex multivariate datasets is rapidly increasing in many applied science and engineering disciplines, including geo-energy. Motivated by these developments, Machine Learning Applications in Subsurface Energy Resource Management presents a current snapshot of the state of the art and future outlook for ML applications to manage subsurface energy resources (e.g., oil and gas, geologic carbon sequestration, and geothermal energy). Covers ML applications across multiple application domains (reservoir characterization, drilling, production, reservoir modeling, and predictive maintenance) Offers a variety of perspectives from authors representing operating companies, universities, and research organizations Provides an array of case studies illustrating the latest applications of several ML techniques Includes a literature review and future outlook for each application domain This book is targeted at practicing petroleum engineers or geoscientists interested in developing a broad understanding of ML applications across several subsurface domains. It is also aimed as a supplementary reading for graduate-level courses and will also appeal to professionals and researchers working with hydrogeology and nuclear waste disposal.
Managed Pressure Drilling: Fundamentals, Methods and Applications
Managed Pressure Drilling Fundamentals, Methods and Applications, First Edition provides the basic infrastructure and extended support necessary for drilling engineers to apply managed pressure drilling to their operations. Enhanced with multiple new chapters and contributions from both academic and corporate authors, this reference provides engineers with the basic processes and equipment behind MPD. Other sections explain the latest technology and real-world case studies, such as how to optimize the managed pressure drilling system, how to choose the best well candidate for MPD, and how to lower costs for land-based operations. Packed with a glossary, list of standards, and a well classification system, this book is a flagship reference for drilling engineers on how to understand basics and advances in this fast-paced area of oil and gas technology. - Demonstrates the value in safety improvement, time and cost savings, sustainability and reduced carbon footprint that adoption of MPD brings to well construction. - Delivers a fundamental collection on managed pressure drilling equipment, methods, procedures, best practices, and field cases. - Presents a balance of information that ranges from historical details and background theory to practical application - Includes multiple critical chapters dealing with all major MPD variants, MPD event detection, control systems and automation, how to plan and risk MPD, where MPD fits in the well delivery process, and its future outlook.