Data Driven Analytics For The Geological Storage Of Co2
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Data Driven Analytics For The Geological Storage Of Co2
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Author : Shahab Mohaghegh
language : en
Publisher: CRC Press
Release Date : 2018-05-20
Data Driven Analytics For The Geological Storage Of Co2 written by Shahab Mohaghegh and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-05-20 with Science categories.
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.
Data Driven Analytics For The Geological Storage Of Co2
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Author : Shahab D. Mohaghegh
language : en
Publisher: CRC Press
Release Date : 2018
Data Driven Analytics For The Geological Storage Of Co2 written by Shahab D. Mohaghegh and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with Computers categories.
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.
Artificial Intelligence For Science And Engineering Applications
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Author : Shahab D. Mohaghegh
language : en
Publisher: CRC Press
Release Date : 2024-04-01
Artificial Intelligence For Science And Engineering Applications written by Shahab D. Mohaghegh and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-04-01 with Computers categories.
Artificial Intelligence (AI) is defined as the simulation of human intelligence through the mimicking of the human brain for analysis, modeling, and decision‐making. Science and engineering problem solving requires modeling of physical phenomena, and humans approach the solution of scientific and engineering problems differently from other problems. Artificial Intelligence for Science and Engineering Applications addresses the unique differences in how AI should be developed and used in science and engineering. Through the inclusion of definitions and detailed examples, this book describes the actual and realistic requirements as well as what characteristics must be avoided for correct and successful science and engineering applications of AI. This book: Offers a brief history of AI and covers science and engineering applications Explores the modeling of physical phenomena using AI Discusses explainable AI (XAI) applications Covers the ethics of AI in science and engineering Features real‐world case studies Offering a probing view into the unique nature of scientific and engineering exploration, this book will be of interest to generalists and experts looking to expand their understanding of how AI can better tackle and advance technology and developments in scientific and engineering disciplines.
Smart Proxy Modeling
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Author : Shahab D. Mohaghegh
language : en
Publisher: CRC Press
Release Date : 2022-10-27
Smart Proxy Modeling written by Shahab D. Mohaghegh and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-10-27 with Computers categories.
Numerical simulation models are used in all engineering disciplines for modeling physical phenomena to learn how the phenomena work, and to identify problems and optimize behavior. Smart Proxy Models provide an opportunity to replicate numerical simulations with very high accuracy and can be run on a laptop within a few minutes, thereby simplifying the use of complex numerical simulations, which can otherwise take tens of hours. This book focuses on Smart Proxy Modeling and provides readers with all the essential details on how to develop Smart Proxy Models using Artificial Intelligence and Machine Learning, as well as how it may be used in real-world cases. Covers replication of highly accurate numerical simulations using Artificial Intelligence and Machine Learning Details application in reservoir simulation and modeling and computational fluid dynamics Includes real case studies based on commercially available simulators Smart Proxy Modeling is ideal for petroleum, chemical, environmental, and mechanical engineers, as well as statisticians and others working with applications of data-driven analytics.
Unconventional Resources
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Author : Cenk Temizel
language : en
Publisher: CRC Press
Release Date : 2025-02-27
Unconventional Resources written by Cenk Temizel and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-27 with Technology & Engineering categories.
The oil and gas sector is a vital player in the energy transition. With their vast resource potential, unconventional shale plays will be an essential part in enabling this change. Unconventional Resources serves as a comprehensive reference covering the latest technologies, methodologies, and applications of unconventional shale resources in the oil and gas industry, and their role in the evolution of the sector's energy transition. This book: Offers an overview of geophysics, geology, and reservoir characterization in unconventional resources Discusses drilling, well stimulation and completion, production engineering, and artificial lift Covers reservoir management and surveillance, recovery enhancement, production forecasting, and surface facilities and testing Details technical and technological advances, including machine learning, AI, data analytics, and Industry 4.0 Explores the latest methods/workflows in performance analysis in unconventional plays Employs integrated and hybrid approaches to the energy transition The book provides surface and subsurface technical professionals in the oil and gas industry a thorough overview of unconventionals along with the integrated/hybrid applications that will enable them to stay current with the industry's transition.
Unconventional Shale Gas Development
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Author : Rouzbeh G. Moghanloo
language : en
Publisher: Gulf Professional Publishing
Release Date : 2022-02-23
Unconventional Shale Gas Development written by Rouzbeh G. Moghanloo 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 2022-02-23 with Science categories.
Unconventional Shale Gas Development: Lessons Learned gives engineers the latest research developments and practical applications in today's operations. Comprised of both academic and corporate contributors, a balanced critical review on technologies utilized are covered. Environmental topics are presented, including produced water management and sustainable operations in gas systems. Machine learning applications, well integrity and economic challenges are also covered to get the engineer up-to-speed. With its critical elements, case studies, history plot visuals and flow charts, the book delivers a critical reference to get today's petroleum engineers updated on the latest research and applications surrounding shale gas systems. - Bridges the gap between the latest research developments and practical applications through case studies and workflow charts - Helps readers understand the latest developments from the balanced viewpoint of academic and corporate contributors - Considers environmental and sustainable operations in shale gas systems, including produced water management
Reservoir Characterization Modeling And Quantitative Interpretation
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Author : Shib Sankar Ganguli
language : en
Publisher: Elsevier
Release Date : 2023-10-27
Reservoir Characterization Modeling And Quantitative Interpretation written by Shib Sankar Ganguli and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-10-27 with Science categories.
Reservoir Characterization, Modeling and Quantitative Interpretation: Recent Workflows to Emerging Technologies offers a wide spectrum of reservoir characterization techniques and technologies, focusing on the latest breakthroughs and most efficient methodologies in hydrocarbon exploration and development. Topics covered include 4D seismic technologies, AVAz inversion, fracture characterization, multiscale imaging technologies, static and dynamic reservoir characterization, among others. The content is delivered through an inductive approach, which will help readers gain comprehensive insights on advanced practices and be able to relate them to other subareas of reservoir characterization, including CO2 storage and data-driven modeling. This will be especially useful for field scientists in collecting and analyzing field data, prospect evaluation, developing reservoir models, and adopting new technologies to mitigate exploration risk. They will be able to solve the practical and challenging problems faced in the field of reservoir characterization, as it will offer systematic industrial workflows covering every aspect of this branch of Earth Science, including subsurface geoscientific perspectives of carbon geosequestration. This resource is a 21st Century guide for exploration geologists, geoscience students at postgraduate level and above, and petrophysicists working in the oil and gas industry. - Covers the latest and most effective technologies in reservoir characterization, including Avo analysis, AVAz inversion, wave field separation and Machine Learning techniques - Provides a balanced blend of both theoretical and practical approaches for solving challenges in reservoir characterization - Includes detailed industry-standard practical workflows, along with code structures for algorithms and practice exercises
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
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.
Quantitative Geosciences Data Analytics Geostatistics Reservoir Characterization And Modeling
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Author : Y. Z. Ma
language : en
Publisher: Springer
Release Date : 2019-07-15
Quantitative Geosciences Data Analytics Geostatistics Reservoir Characterization And Modeling written by Y. Z. Ma and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-07-15 with Technology & Engineering categories.
Earth science is becoming increasingly quantitative in the digital age. Quantification of geoscience and engineering problems underpins many of the applications of big data and artificial intelligence. This book presents quantitative geosciences in three parts. Part 1 presents data analytics using probability, statistical and machine-learning methods. Part 2 covers reservoir characterization using several geoscience disciplines: including geology, geophysics, petrophysics and geostatistics. Part 3 treats reservoir modeling, resource evaluation and uncertainty analysis using integrated geoscience, engineering and geostatistical methods. As the petroleum industry is heading towards operating oil fields digitally, a multidisciplinary skillset is a must for geoscientists who need to use data analytics to resolve inconsistencies in various sources of data, model reservoir properties, evaluate uncertainties, and quantify risk for decision making. This book intends to serve as a bridge for advancing the multidisciplinary integration for digital fields. The goal is to move beyond using quantitative methods individually to an integrated descriptive-quantitative analysis. In big data, everything tells us something, but nothing tells us everything. This book emphasizes the integrated, multidisciplinary solutions for practical problems in resource evaluation and field development.