Data Analytics For Drilling Engineering

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Data Analytics for Drilling Engineering

Qilong Xue
Data Analytics for Drilling Engineering Book PDF

Author : Qilong Xue
Publisher : Springer Nature
Page : 312 pages
File Size : 50,7 Mb
Release : 2019-12-30
Category : Science
ISBN : 9783030340353

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Data Analytics for Drilling Engineering by Qilong Xue Pdf

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.

Data Analytics in Reservoir Engineering

Sathish Sankaran,Sebastien Matringe,Mohamed Sidahmed
Data Analytics in Reservoir Engineering Book PDF

Author : Sathish Sankaran,Sebastien Matringe,Mohamed Sidahmed
Publisher : Unknown
Page : 108 pages
File Size : 46,5 Mb
Release : 2020-10-29
Category : Electronic
ISBN : 1613998201

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Data Analytics in Reservoir Engineering by Sathish Sankaran,Sebastien Matringe,Mohamed Sidahmed Pdf

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

Shale Analytics

Shahab D. Mohaghegh
Shale Analytics Book PDF

Author : Shahab D. Mohaghegh
Publisher : Springer
Page : 287 pages
File Size : 52,9 Mb
Release : 2017-02-09
Category : Technology & Engineering
ISBN : 9783319487533

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Shale Analytics by Shahab D. Mohaghegh Pdf

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.

Methods for Petroleum Well Optimization

Rasool Khosravanian,Bernt S. Aadnoy
Methods for Petroleum Well Optimization Book PDF

Author : Rasool Khosravanian,Bernt S. Aadnoy
Publisher : Gulf Professional Publishing
Page : 554 pages
File Size : 50,8 Mb
Release : 2021-09-22
Category : Science
ISBN : 9780323902328

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Methods for Petroleum Well Optimization by Rasool Khosravanian,Bernt S. Aadnoy Pdf

Drilling and production wells are becoming more digitalized as oil and gas companies continue to implement machine learning andbig data solutions to save money on projects while reducing energy and emissions. Up to now there has not been one cohesiveresource that bridges the gap between theory and application, showing how to go from computer modeling to practical use. Methodsfor Petroleum Well Optimization: Automation and Data Solutions gives today’s engineers and researchers real-time data solutionsspecific to drilling and production assets. Structured for training, this reference covers key concepts and detailed approaches frommathematical to real-time data solutions through technological advances. Topics include digital well planning and construction,moving teams into Onshore Collaboration Centers, operations with the best machine learning (ML) and metaheuristic algorithms,complex trajectories for wellbore stability, real-time predictive analytics by data mining, optimum decision-making, and case-basedreasoning. Supported by practical case studies, and with references including links to open-source code and fit-for-use MATLAB, R,Julia, Python and other standard programming languages, Methods for Petroleum Well Optimization delivers a critical training guidefor researchers and oil and gas engineers to take scientifically based approaches to solving real field problems. Bridges the gap between theory and practice (from models to code) with content from the latest research developments supported by practical case study examples and questions at the end of each chapter Enables understanding of real-time data solutions and automation methods available specific to drilling and production wells, suchas digital well planning and construction through to automatic systems Promotes the use of open-source code which will help companies, engineers, and researchers develop their prediction and analysissoftware more quickly; this is especially appropriate in the application of multivariate techniques to the real-world problems of petroleum well optimization

Applied Drilling Engineering

Adam T. Bourgoyne
Applied Drilling Engineering Book PDF

Author : Adam T. Bourgoyne
Publisher : Unknown
Page : 522 pages
File Size : 50,8 Mb
Release : 1986
Category : Oil well drilling
ISBN : STANFORD:36105031120673

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Applied Drilling Engineering by Adam T. Bourgoyne Pdf

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

Machine Learning and Data Science in the Oil and Gas Industry

Patrick Bangert
Machine Learning and Data Science in the Oil and Gas Industry Book PDF

Author : Patrick Bangert
Publisher : Gulf Professional Publishing
Page : 290 pages
File Size : 47,6 Mb
Release : 2021-03-04
Category : Science
ISBN : 9780128209141

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Machine Learning and Data Science in the Oil and Gas Industry by Patrick Bangert Pdf

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)

Understanding Data Analytics and Predictive Modelling in the Oil and Gas Industry

Kingshuk Srivastava,Thipendra P Singh,Manas Ranjan Pradhan,Vinit Kumar Gunjan
Understanding Data Analytics and Predictive Modelling in the Oil and Gas Industry Book PDF

Author : Kingshuk Srivastava,Thipendra P Singh,Manas Ranjan Pradhan,Vinit Kumar Gunjan
Publisher : CRC Press
Page : 187 pages
File Size : 47,6 Mb
Release : 2023-11-20
Category : Technology & Engineering
ISBN : 9781000995114

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Understanding Data Analytics and Predictive Modelling in the Oil and Gas Industry by Kingshuk Srivastava,Thipendra P Singh,Manas Ranjan Pradhan,Vinit Kumar Gunjan Pdf

This book covers aspects of data science and predictive analytics used in the oil and gas industry by looking into the challenges of data processing and data modelling unique to this industry. It includes upstream management, intelligent/digital wells, value chain integration, crude basket forecasting, and so forth. It further discusses theoretical, methodological, well-established, and validated empirical work dealing with various related topics. Special focus has been given to experimental topics with various case studies. Features: Provides an understanding of the basics of IT technologies applied in the oil and gas sector Includes deep comparison between different artificial intelligence techniques Analyzes different simulators in the oil and gas sector as well as discussion of AI applications Focuses on in-depth experimental and applied topics Details different case studies for upstream and downstream This book is aimed at professionals and graduate students in petroleum engineering, upstream industry, data analytics, and digital transformation process in oil and gas.

Drilling Data Vortex

Carlos Damski
Drilling Data Vortex Book PDF

Author : Carlos Damski
Publisher : Genesis Publishing and Services Pty Limited
Page : 138 pages
File Size : 46,7 Mb
Release : 2014-11-10
Category : Electronic
ISBN : 0994164203

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Drilling Data Vortex by Carlos Damski Pdf

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.

Understanding Data Analytics and Predictive Modelling in the Oil and Gas Industry

Kingshuk Srivastava,Thipendra P. Singh,Manas Ranjan Pradhan,Vinit Kumar Gunjan
Understanding Data Analytics and Predictive Modelling in the Oil and Gas Industry Book PDF

Author : Kingshuk Srivastava,Thipendra P. Singh,Manas Ranjan Pradhan,Vinit Kumar Gunjan
Publisher : Unknown
Page : 0 pages
File Size : 46,8 Mb
Release : 2024
Category : Gas industry
ISBN : 1003357873

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Understanding Data Analytics and Predictive Modelling in the Oil and Gas Industry by Kingshuk Srivastava,Thipendra P. Singh,Manas Ranjan Pradhan,Vinit Kumar Gunjan Pdf

This book covers aspects of data science and predictive analytics used in the oil and gas industry by looking into the challenges of data processing and data modelling unique to this industry. It includes upstream management, intelligent/digital wells, value chain integration, crude basket forecasting, and so forth. It further discusses theoretical, methodological, well-established, and validated empirical work dealing with various related topics. Special focus has been given to experimental topics with various case studies. Features: Provides an understanding of the basics of IT technologies applied in the oil and gas sector Includes deep comparison between different artificial intelligence techniques Analyzes different simulators in the oil and gas sector as well as discussion of AI applications Focuses on in-depth experimental and applied topics Details different case studies for upstream and downstream This book is aimed at professionals and graduate students in petroleum engineering, upstream industry, data analytics, and digital transformation process in oil and gas.

Soft Computing and Intelligent Data Analysis in Oil Exploration

M. Nikravesh,L.A. Zadeh,Fred Aminzadeh
Soft Computing and Intelligent Data Analysis in Oil Exploration Book PDF

Author : M. Nikravesh,L.A. Zadeh,Fred Aminzadeh
Publisher : Elsevier
Page : 755 pages
File Size : 53,6 Mb
Release : 2003-04-22
Category : Science
ISBN : 9780080541327

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Soft Computing and Intelligent Data Analysis in Oil Exploration by M. Nikravesh,L.A. Zadeh,Fred Aminzadeh Pdf

This comprehensive book highlights soft computing and geostatistics applications in hydrocarbon exploration and production, combining practical and theoretical aspects. It spans a wide spectrum of applications in the oil industry, crossing many discipline boundaries such as geophysics, geology, petrophysics and reservoir engineering. It is complemented by several tutorial chapters on fuzzy logic, neural networks and genetic algorithms and geostatistics to introduce these concepts to the uninitiated. The application areas include prediction of reservoir properties (porosity, sand thickness, lithology, fluid), seismic processing, seismic and bio stratigraphy, time lapse seismic and core analysis. There is a good balance between introducing soft computing and geostatistics methodologies that are not routinely used in the petroleum industry and various applications areas. The book can be used by many practitioners such as processing geophysicists, seismic interpreters, geologists, reservoir engineers, petrophysicist, geostatistians, asset mangers and technology application professionals. It will also be of interest to academics to assess the importance of, and contribute to, R&D efforts in relevant areas.

Data Analytics Applied to the Mining Industry

Ali Soofastaei
Data Analytics Applied to the Mining Industry Book PDF

Author : Ali Soofastaei
Publisher : CRC Press
Page : 273 pages
File Size : 54,6 Mb
Release : 2020-11-12
Category : Computers
ISBN : 9780429781773

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Data Analytics Applied to the Mining Industry by Ali Soofastaei Pdf

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

Machine Learning Guide for Oil and Gas Using Python

Hoss Belyadi,Alireza Haghighat
Machine Learning Guide for Oil and Gas Using Python Book PDF

Author : Hoss Belyadi,Alireza Haghighat
Publisher : Gulf Professional Publishing
Page : 478 pages
File Size : 53,9 Mb
Release : 2021-04-09
Category : Science
ISBN : 9780128219300

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Machine Learning Guide for Oil and Gas Using Python by Hoss Belyadi,Alireza Haghighat Pdf

Machine Learning Guide for Oil and Gas Using Python: A Step-by-Step Breakdown with Data, Algorithms, Codes, and Applications delivers a critical training and resource tool to help engineers understand machine learning theory and practice, specifically referencing use cases in oil and gas. The reference moves from explaining how Python works to step-by-step examples of utilization in various oil and gas scenarios, such as well testing, shale reservoirs and production optimization. Petroleum engineers are quickly applying machine learning techniques to their data challenges, but there is a lack of references beyond the math or heavy theory of machine learning. Machine Learning Guide for Oil and Gas Using Python details the open-source tool Python by explaining how it works at an introductory level then bridging into how to apply the algorithms into different oil and gas scenarios. While similar resources are often too mathematical, this book balances theory with applications, including use cases that help solve different oil and gas data challenges. Helps readers understand how open-source Python can be utilized in practical oil and gas challenges Covers the most commonly used algorithms for both supervised and unsupervised learning Presents a balanced approach of both theory and practicality while progressing from introductory to advanced analytical techniques

Advanced Analytics in Mining Engineering

Ali Soofastaei
Advanced Analytics in Mining Engineering Book PDF

Author : Ali Soofastaei
Publisher : Springer Nature
Page : 746 pages
File Size : 53,8 Mb
Release : 2022-02-23
Category : Business & Economics
ISBN : 9783030915896

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Advanced Analytics in Mining Engineering by Ali Soofastaei Pdf

In this book, Dr. Soofastaei and his colleagues reveal how all mining managers can effectively deploy advanced analytics in their day-to-day operations- one business decision at a time. Most mining companies have a massive amount of data at their disposal. However, they cannot use the stored data in any meaningful way. The powerful new business tool-advanced analytics enables many mining companies to aggressively leverage their data in key business decisions and processes with impressive results. From statistical analysis to machine learning and artificial intelligence, the authors show how many analytical tools can improve decisions about everything in the mine value chain, from exploration to marketing. Combining the science of advanced analytics with the mining industrial business solutions, introduce the “Advanced Analytics in Mining Engineering Book” as a practical road map and tools for unleashing the potential buried in your company’s data. The book is aimed at providing mining executives, managers, and research and development teams with an understanding of the business value and applicability of different analytic approaches and helping data analytics leads by giving them a business framework in which to assess the value, cost, and risk of potential analytical solutions. In addition, the book will provide the next generation of miners – undergraduate and graduate IT and mining engineering students – with an understanding of data analytics applied to the mining industry. By providing a book with chapters structured in line with the mining value chain, we will provide a clear, enterprise-level view of where and how advanced data analytics can best be applied. This book highlights the potential to interconnect activities in the mining enterprise better. Furthermore, the book explores the opportunities for optimization and increased productivity offered by better interoperability along the mining value chain – in line with the emerging vision of creating a digital mine with much-enhanced capabilities for modeling, simulation, and the use of digital twins – in line with leading “digital” industries.

Fundamentals of Sustainable Drilling Engineering

M. E. Hossain,Abdulaziz Abdullah Al-Majed
Fundamentals of Sustainable Drilling Engineering Book PDF

Author : M. E. Hossain,Abdulaziz Abdullah Al-Majed
Publisher : John Wiley & Sons
Page : 786 pages
File Size : 50,7 Mb
Release : 2015-02-04
Category : Technology & Engineering
ISBN : 9781119100294

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Fundamentals of Sustainable Drilling Engineering by M. E. Hossain,Abdulaziz Abdullah Al-Majed Pdf

The book clearly explains the concepts of the drilling engineering and presents the existing knowledge ranging from the history of drilling technology to well completion. This textbook takes on the difficult issue of sustainability in drilling engineering and tries to present the engineering terminologies in a clear manner so that the new hire, as well as the veteran driller, will be able to understand the drilling concepts with minimum effort. This textbook is an excellent resource for petroleum engineering students, drilling engineers, supervisors & managers, researchers and environmental engineers for planning every aspect of rig operations in the most sustainable, environmentally responsible manner, using the most up-to-date technological advancements in equipment and processes.

Artificial Intelligence and Data Analytics for Energy Exploration and Production

Fred Aminzadeh,Cenk Temizel,Yasin Hajizadeh
Artificial Intelligence and Data Analytics for Energy Exploration and Production Book PDF

Author : Fred Aminzadeh,Cenk Temizel,Yasin Hajizadeh
Publisher : John Wiley & Sons
Page : 613 pages
File Size : 44,8 Mb
Release : 2022-09-21
Category : Science
ISBN : 9781119879695

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Artificial Intelligence and Data Analytics for Energy Exploration and Production by Fred Aminzadeh,Cenk Temizel,Yasin Hajizadeh Pdf

ARTIFICAL INTELLIGENCE AND DATA ANALYTICS FOR ENERGY EXPLORATION AND PRODUCTION This groundbreaking new book is written by some of the foremost authorities on the application of data science and artificial intelligence techniques in exploration and production in the energy industry, covering the most comprehensive and updated new processes, concepts, and practical applications in the field. The book provides an in-depth treatment of the foundations of Artificial Intelligence (AI) Machine Learning, and Data Analytics (DA). It also includes many of AI-DA applications in oil and gas reservoirs exploration, development, and production. The book covers the basic technical details on many tools used in “smart oil fields”. This includes topics such as pattern recognition, neural networks, fuzzy logic, evolutionary computing, expert systems, artificial intelligence machine learning, human-computer interface, natural language processing, data analytics and next-generation visualization. While theoretical details will be kept to the minimum, these topics are introduced from oil and gas applications viewpoints. In this volume, many case histories from the recent applications of intelligent data to a number of different oil and gas problems are highlighted. The applications cover a wide spectrum of practical problems from exploration to drilling and field development to production optimization, artificial lift, and secondary recovery. Also, the authors demonstrate the effectiveness of intelligent data analysis methods in dealing with many oil and gas problems requiring combining machine and human intelligence as well as dealing with linguistic and imprecise data and rules.