Data Analytics For Drilling Engineering
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Data Analytics For Drilling Engineering
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Author : Qilong Xue
language : en
Publisher: Springer Nature
Release Date : 2019-12-30
Data Analytics For Drilling Engineering written by Qilong Xue and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-12-30 with Science categories.
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.
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)
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.
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.
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.
Methods For Petroleum Well Optimization
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Author : Rasool Khosravanian
language : en
Publisher: Gulf Professional Publishing
Release Date : 2021-09-22
Methods For Petroleum Well Optimization written by Rasool Khosravanian 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 2021-09-22 with Science categories.
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
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.
Chatgpt For Petroleum Engineers
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Author : Jade Summers
language : en
Publisher: Jade Summers
Release Date :
Chatgpt For Petroleum Engineers written by Jade Summers and has been published by Jade Summers this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.
🌟 Transform Petroleum Engineering with AI! 🌟 Dive into the cutting-edge world of artificial intelligence with this must-read guide tailored for petroleum engineers. Explore how ChatGPT revolutionizes workflows, enhances decision-making, and fosters sustainable practices in the oil and gas industry. 📘 What’s Inside: 🔧 Streamline Operations: Automate routine tasks and improve efficiency with AI-driven solutions. 🛠️ Enhance Safety Protocols: Real-world applications of AI for predictive maintenance and emergency response. 🌍 Sustainable Practices: Reduce carbon footprints with innovative AI tools. 📊 Data-Driven Insights: Learn how AI simplifies complex data analysis for better outcomes. 🚀 Future-Ready Engineers: Prepare for tomorrow with the power of ChatGPT. Unlock the full potential of AI in petroleum engineering and stay ahead in a rapidly evolving industry. Order your copy today!
Artificial Intelligence And Data Analytics For Energy Exploration And Production
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Author : Fred Aminzadeh
language : en
Publisher: John Wiley & Sons
Release Date : 2022-08-26
Artificial Intelligence And Data Analytics For Energy Exploration And Production written by Fred Aminzadeh and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-08-26 with Science categories.
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.
Wellbore Integrity
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Author : Arash Dahi Taleghani
language : en
Publisher: Springer Nature
Release Date : 2023-01-29
Wellbore Integrity written by Arash Dahi Taleghani and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-01-29 with Technology & Engineering categories.
There have been concerns about the integrity of thousands of wells drilled worldwide for different purposes ranging from oil and gas to geological carbon sequestration. This is the first book to integrate different aspects of wellbore integrity into a single volume. It looks at the energy sector's green wave movement by expanding an important topic for practitioners, regulators, and students. It is an area where petroleum and subsurface engineers will increasingly need to be involved in the future to address growing expectations regarding environmental impacts and sustainability. Coverage also includes recent developments in regulations and R&D with indications on emerging areas. Wellbore Integrity: From Theory to Practice will be a valuable resource for practicing engineers and students working on problems related to subsurface energy, subsurface disposals, and environmental impacts of oil and gas wells. In parallel, it will be a valuable reference for engineers and scientists interested in repurposing existing wells for carbon sequestration or geothermal purposes.