Understanding Data Analytics And Predictive Modelling In The Oil And Gas Industry
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Understanding Data Analytics And Predictive Modelling In The Oil And Gas Industry
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Author : Kingshuk Srivastava
language : en
Publisher: CRC Press
Release Date : 2023-11-20
Understanding Data Analytics And Predictive Modelling In The Oil And Gas Industry written by Kingshuk Srivastava and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-11-20 with Technology & Engineering categories.
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.
Understanding Data Analytics And Predictive Modelling In The Oil And Gas Industry
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Author : Kingshuk Srivastava
language : en
Publisher:
Release Date : 2024
Understanding Data Analytics And Predictive Modelling In The Oil And Gas Industry written by Kingshuk Srivastava and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024 with Gas industry categories.
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.
Machine Learning And Data Science In The Oil And Gas Industry
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Author : Patrick Bangert
language : en
Publisher: Gulf Professional Publishing
Release Date : 2021-03-04
Machine Learning And Data Science In The Oil And Gas Industry written by Patrick Bangert and has been published by Gulf Professional Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-03-04 with Science categories.
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)
Rheological Measurement Techniques And Analysis Methods
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Author : Jian Wang
language : en
Publisher: BoD – Books on Demand
Release Date : 2024-12-04
Rheological Measurement Techniques And Analysis Methods written by Jian Wang and has been published by BoD – Books on Demand this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-04 with Technology & Engineering categories.
Rheological Measurement Techniques and Analysis Methods provides a comprehensive exploration of modern rheological analysis, offering key insights into the flow and deformation behaviors of complex materials across various industries. This edited volume brings together advanced techniques and methodologies, with a particular focus on real-time measurements, modeling of viscoelastic materials, and practical applications in fields such as plastics and petroleum. By bridging theoretical concepts with practical solutions, the book serves as an invaluable resource for researchers and professionals seeking to understand and apply rheological principles in material design, quality control, and process optimization. The book covers a wide range of topics, from fundamental rheology to cutting-edge applications, making it a versatile tool for anyone working with fluids or investigating the mechanical properties of complex materials. With clear explanations of rheological techniques and their relevance to industries such as manufacturing and energy, this volume offers readers practical approaches to solving material challenges and optimizing performance. Whether you are a researcher, engineer, or industry professional, this book provides the tools needed to deepen your understanding of rheology and apply it to real-world problems.
Soft Computing And Intelligent Data Analysis In Oil Exploration
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Author : M. Nikravesh
language : en
Publisher: Elsevier Science
Release Date : 2003-05-06
Soft Computing And Intelligent Data Analysis In Oil Exploration written by M. Nikravesh and has been published by Elsevier Science this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003-05-06 with Science categories.
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.
Machine Learning In The Oil And Gas Industry
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Author : Yogendra Narayan Pandey
language : en
Publisher: Apress
Release Date : 2020-11-03
Machine Learning In The Oil And Gas Industry written by Yogendra Narayan Pandey and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-03 with Computers categories.
Apply machine and deep learning to solve some of the challenges in the oil and gas industry. The book begins with a brief discussion of the oil and gas exploration and production life cycle in the context of data flow through the different stages of industry operations. This leads to a survey of some interesting problems, which are good candidates for applying machine and deep learning approaches. The initial chapters provide a primer on the Python programming language used for implementing the algorithms; this is followed by an overview of supervised and unsupervised machine learning concepts. The authors provide industry examples using open source data sets along with practical explanations of the algorithms, without diving too deep into the theoretical aspects of the algorithms employed. Machine Learning in the Oil and Gas Industry covers problems encompassing diverse industry topics, including geophysics (seismic interpretation), geological modeling, reservoir engineering, and production engineering. Throughout the book, the emphasis is on providing a practical approach with step-by-step explanations and code examples for implementing machine and deep learning algorithms for solving real-life problems in the oil and gas industry. What You Will Learn Understanding the end-to-end industry life cycle and flow of data in the industrial operations of the oil and gas industry Get the basic concepts of computer programming and machine and deep learning required for implementing the algorithms used Study interesting industry problems that are good candidates for being solved by machine and deep learning Discover the practical considerations and challenges for executing machine and deep learning projects in the oil and gas industry Who This Book Is For Professionals in the oil and gas industry who can benefit from a practical understanding of the machine and deep learning approach to solving real-life problems.
Advanced Analytics For Industry 4 0
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Author : Ali Soofastaei
language : en
Publisher: CRC Press
Release Date : 2025-07-17
Advanced Analytics For Industry 4 0 written by Ali Soofastaei and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-17 with Computers categories.
The evolution of modern technology has affected all the industry dimensions. Mother industries play a critical role in providing the precursor materials for other industries, and a small improvement in these can make a big change in others. This book covers the analytics revolution in Industry 4.0 for the mother industries, such as mining, oil and gas, and steel. It focuses on the use of advanced analytics and artificial intelligence to improve the business decisions aimed at increasing the quality and quantity of mother industries' products. It helps to design and implement their digital transformation strategies in these industries. Key Features: Provides a concise overview of state of the art for mother industries' executives and managers. Highlights and describes critical opportunity areas for industry operations optimization. Explains how to implement advanced data analytics through case studies and examples. Provides approaches and methods to improve data-driven decision-making. Brings experience and learning in digital transformation from adjacent sectors. This book is aimed at researchers, professionals, and graduate students in data science, manufacturing, automation, and computer engineering.
Shale Analytics
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Author : Shahab D. Mohaghegh
language : en
Publisher: Springer
Release Date : 2017-02-09
Shale Analytics written by Shahab D. Mohaghegh and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-02-09 with Technology & Engineering categories.
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.
Applied Statistical Modeling And Data Analytics
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Author : Srikanta Mishra
language : en
Publisher: Elsevier
Release Date : 2017-10-27
Applied Statistical Modeling And Data Analytics written by Srikanta Mishra and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-10-27 with Science categories.
Applied Statistical Modeling and Data Analytics: A Practical Guide for the Petroleum Geosciences provides a practical guide to many of the classical and modern statistical techniques that have become established for oil and gas professionals in recent years. It serves as a "how to" reference volume for the practicing petroleum engineer or geoscientist interested in applying statistical methods in formation evaluation, reservoir characterization, reservoir modeling and management, and uncertainty quantification. Beginning with a foundational discussion of exploratory data analysis, probability distributions and linear regression modeling, the book focuses on fundamentals and practical examples of such key topics as multivariate analysis, uncertainty quantification, data-driven modeling, and experimental design and response surface analysis. Data sets from the petroleum geosciences are extensively used to demonstrate the applicability of these techniques. The book will also be useful for professionals dealing with subsurface flow problems in hydrogeology, geologic carbon sequestration, and nuclear waste disposal. - Authored by internationally renowned experts in developing and applying statistical methods for oil & gas and other subsurface problem domains - Written by practitioners for practitioners - Presents an easy to follow narrative which progresses from simple concepts to more challenging ones - Includes online resources with software applications and practical examples for the most relevant and popular statistical methods, using data sets from the petroleum geosciences - Addresses the theory and practice of statistical modeling and data analytics from the perspective of petroleum geoscience applications
Revolutionizing Ai And Robotics In The Oil And Gas Industry
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Author : Abdullayev, Vugar
language : en
Publisher: IGI Global
Release Date : 2025-04-23
Revolutionizing Ai And Robotics In The Oil And Gas Industry written by Abdullayev, Vugar and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-23 with Business & Economics categories.
The oil and gas industry remains the main source of energy and is one of the valuable areas of the energy market. In this sector, the replacement of human labor by technology is particularly important for the implementation of all stages. With the application of smart technology, it was possible to replace not only the physical aspect of human labor but also a number of mental activities. The integration of smart technology, such as artificial intelligence (AI) and robotics, has made it possible to automate processes such as design, risk assessment, forecasting, ensuring safety and optimizing production. Revolutionizing AI and Robotics in the Oil and Gas Industry addresses all aspects and principles of the joint integration of AI and Robotics for process automation in the oil and gas industry. It discusses the modern environment created by the integration of digital technologies into this field, the extent to which progress has been made with the automation of processes through AI, and the consequences of the application of robotics and automation to the industry. Covering topics such as leak detection, petroleum engineering, and oil reservoir behavior, this book is an excellent resource for industry professionals, engineers, computer scientists, professionals, researchers, scholars, academicians and more.