Data Analytics for Drilling Engineering PDF Download

Author: Qilong Xue
Publisher: Springer Nature
ISBN: 303034035X
Category : Science
Languages : en
Pages : 324

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Book Description
This book presents the signal processing and data mining challenges encountered in drilling engineering, and describes the methods used to overcome them. In drilling engineering, many signal processing technologies are required to solve practical problems, such as downhole information transmission, spatial attitude of drillstring, drillstring dynamics, seismic activity while drilling, among others. This title attempts to bridge the gap between the signal processing and data mining and oil and gas drilling engineering communities. There is an urgent need to summarize signal processing and data mining issues in drilling engineering so that practitioners in these fields can understand each other in order to enhance oil and gas drilling functions. In summary, this book shows the importance of signal processing and data mining to researchers and professional drilling engineers and open up a new area of application for signal processing and data mining scientists.

Author: Sathish Sankaran
Publisher:
ISBN: 9781613998205
Category :
Languages : en
Pages : 108

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Book Description
Data Analytics in Reservoir Engineering describes the relevance of data analytics for the oil and gas industry, with particular emphasis on reservoir engineering.

Author: Shahab D. Mohaghegh
Publisher: Springer
ISBN: 3319487531
Category : Technology & Engineering
Languages : en
Pages : 292

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Book Description
This book describes the application of modern information technology to reservoir modeling and well management in shale. While covering Shale Analytics, it focuses on reservoir modeling and production management of shale plays, since conventional reservoir and production modeling techniques do not perform well in this environment. Topics covered include tools for analysis, predictive modeling and optimization of production from shale in the presence of massive multi-cluster, multi-stage hydraulic fractures. Given the fact that the physics of storage and fluid flow in shale are not well-understood and well-defined, Shale Analytics avoids making simplifying assumptions and concentrates on facts (Hard Data - Field Measurements) to reach conclusions. Also discussed are important insights into understanding completion practices and re-frac candidate selection and design. The flexibility and power of the technique is demonstrated in numerous real-world situations.

Author: Patrick Bangert
Publisher: Gulf Professional Publishing
ISBN: 0128209143
Category : Science
Languages : en
Pages : 290

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Book Description
Machine Learning and Data Science in the Oil and Gas Industry explains how machine learning can be specifically tailored to oil and gas use cases. Petroleum engineers will learn when to use machine learning, how it is already used in oil and gas operations, and how to manage the data stream moving forward. Practical in its approach, the book explains all aspects of a data science or machine learning project, including the managerial parts of it that are so often the cause for failure. Several real-life case studies round out the book with topics such as predictive maintenance, soft sensing, and forecasting. Viewed as a guide book, this manual will lead a practitioner through the journey of a data science project in the oil and gas industry circumventing the pitfalls and articulating the business value. - Chart an overview of the techniques and tools of machine learning including all the non-technological aspects necessary to be successful - Gain practical understanding of machine learning used in oil and gas operations through contributed case studies - Learn change management skills that will help gain confidence in pursuing the technology - Understand the workflow of a full-scale project and where machine learning benefits (and where it does not)

Author: Adam T. Bourgoyne
Publisher:
ISBN:
Category : Business & Economics
Languages : en
Pages : 522

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Book Description
Applied Drilling Engineering presents engineering science fundamentals as well as examples of engineering applications involving those fundamentals.

Author: Carlos Damski
Publisher: Genesis Publishing and Services Pty Limited
ISBN: 9780994164209
Category :
Languages : en
Pages : 138

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Book Description
In today's world, traditional methods of drilling oil wells don't work. Yesterday's practices are being superseded by a universal trend towards the extensive use of historical and real-time data to understand, learn and predict all well intervention operations. This book explores the impact of data analytics on well operations. Drawn from the author's extensive experience in data analysis, it examines, in easily understandable terms, today's data management processes. The book explores issues related to: Basic concepts of data management for drilling; Methods of using data as a basis for improving and optimizing process control; Achieving a common understanding of the issues involved among information technology personnel and field engineers; A roadmap for the implementation of a drilling process improvement system; Business Intelligence as the ultimate goal of any data management process; Discussions about data acquisition, quality control, storage, retrieval and analyses; Map intelligence; Understanding operational time and trouble analyses; learning curve, technical limit and benchmarking; Real business cases to illustrate the concepts explored in the book. The book is designed for a broad audience, including drilling personnel, managers, data analysts, and all professionals involved in the use of data to improve drilling operations.

Author: Usman Ahmed
Publisher: CRC Press
ISBN: 1498759416
Category : Science
Languages : en
Pages : 862

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Book Description
As the shale revolution continues in North America, unconventional resource markets are emerging on every continent. In the next eight to ten years, more than 100,000 wells and one- to two-million hydraulic fracturing stages could be executed, resulting in close to one trillion dollars in industry spending. This growth has prompted professionals ex

Author: Ali Soofastaei
Publisher: CRC Press
ISBN: 0429781776
Category : Computers
Languages : en
Pages : 273

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Book Description
Data Analytics Applied to the Mining Industry describes the key challenges facing the mining sector as it transforms into a digital industry able to fully exploit process automation, remote operation centers, autonomous equipment and the opportunities offered by the industrial internet of things. It provides guidelines on how data needs to be collected, stored and managed to enable the different advanced data analytics methods to be applied effectively in practice, through use of case studies, and worked examples. Aimed at graduate students, researchers, and professionals in the industry of mining engineering, this book: Explains how to implement advanced data analytics through case studies and examples in mining engineering Provides approaches and methods to improve data-driven decision making Explains a concise overview of the state of the art for Mining Executives and Managers Highlights and describes critical opportunity areas for mining optimization Brings experience and learning in digital transformation from adjacent sectors

Author: Abdolhossein Hemmati-Sarapardeh
Publisher: Gulf Professional Publishing
ISBN: 0128223855
Category : Science
Languages : en
Pages : 324

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Book Description
Applications of Artificial Intelligence Techniques in the Petroleum Industry gives engineers a critical resource to help them understand the machine learning that will solve specific engineering challenges. The reference begins with fundamentals, covering preprocessing of data, types of intelligent models, and training and optimization algorithms. The book moves on to methodically address artificial intelligence technology and applications by the upstream sector, covering exploration, drilling, reservoir and production engineering. Final sections cover current gaps and future challenges. - Teaches how to apply machine learning algorithms that work best in exploration, drilling, reservoir or production engineering - Helps readers increase their existing knowledge on intelligent data modeling, machine learning and artificial intelligence, with foundational chapters covering the preprocessing of data and training on algorithms - Provides tactics on how to cover complex projects such as shale gas, tight oils, and other types of unconventional reservoirs with more advanced model input

Author: Shahab Mohaghegh
Publisher: CRC Press
ISBN: 1315280795
Category : Science
Languages : en
Pages : 308

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Book Description
Data-driven analytics is enjoying unprecedented popularity among oil and gas professionals. Many reservoir engineering problems associated with geological storage of CO2 require the development of numerical reservoir simulation models. This book is the first to examine the contribution of artificial intelligence and machine learning in data-driven analytics of fluid flow in porous environments, including saline aquifers and depleted gas and oil reservoirs. Drawing from actual case studies, this book demonstrates how smart proxy models can be developed for complex numerical reservoir simulation models. Smart proxy incorporates pattern recognition capabilities of artificial intelligence and machine learning to build smart models that learn the intricacies of physical, mechanical and chemical interactions using precise numerical simulations. This ground breaking technology makes it possible and practical to use high fidelity, complex numerical reservoir simulation models in the design, analysis and optimization of carbon storage in geological formations projects.