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Author: Shuvajit Bhattacharya
Publisher: Elsevier
ISBN: 0128223081
Category : Science
Languages : en
Pages : 378
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Book Description
Advances in Subsurface Data Analytics: Traditional and Physics-Based Approaches brings together the fundamentals of popular and emerging machine learning (ML) algorithms with their applications in subsurface analysis, including geology, geophysics, petrophysics, and reservoir engineering. The book is divided into four parts: traditional ML, deep learning, physics-based ML, and new directions, with an increasing level of diversity and complexity of topics. Each chapter focuses on one ML algorithm with a detailed workflow for a specific application in geosciences. Some chapters also compare the results from an algorithm with others to better equip the readers with different strategies to implement automated workflows for subsurface analysis. Advances in Subsurface Data Analytics: Traditional and Physics-Based Approaches will help researchers in academia and professional geoscientists working on the subsurface-related problems (oil and gas, geothermal, carbon sequestration, and seismology) at different scales to understand and appreciate current trends in ML approaches, their applications, advances and limitations, and future potential in geosciences by bringing together several contributions in a single volume. - Covers fundamentals of simple machine learning and deep learning algorithms, and physics-based approaches written by practitioners in academia and industry - Presents detailed case studies of individual machine learning algorithms and optimal strategies in subsurface characterization around the world - Offers an analysis of future trends in machine learning in geosciences
Author: Shuvajit Bhattacharya
Publisher: Elsevier
ISBN: 0128223081
Category : Science
Languages : en
Pages : 378
Get Book Here
Book Description
Advances in Subsurface Data Analytics: Traditional and Physics-Based Approaches brings together the fundamentals of popular and emerging machine learning (ML) algorithms with their applications in subsurface analysis, including geology, geophysics, petrophysics, and reservoir engineering. The book is divided into four parts: traditional ML, deep learning, physics-based ML, and new directions, with an increasing level of diversity and complexity of topics. Each chapter focuses on one ML algorithm with a detailed workflow for a specific application in geosciences. Some chapters also compare the results from an algorithm with others to better equip the readers with different strategies to implement automated workflows for subsurface analysis. Advances in Subsurface Data Analytics: Traditional and Physics-Based Approaches will help researchers in academia and professional geoscientists working on the subsurface-related problems (oil and gas, geothermal, carbon sequestration, and seismology) at different scales to understand and appreciate current trends in ML approaches, their applications, advances and limitations, and future potential in geosciences by bringing together several contributions in a single volume. - Covers fundamentals of simple machine learning and deep learning algorithms, and physics-based approaches written by practitioners in academia and industry - Presents detailed case studies of individual machine learning algorithms and optimal strategies in subsurface characterization around the world - Offers an analysis of future trends in machine learning in geosciences
Author: Mohammadali Ahmadi
Publisher: Elsevier
ISBN: 0443240116
Category : Technology & Engineering
Languages : en
Pages : 517
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Book Description
Artificial Intelligence for a More Sustainable Oil and Gas Industry and the Energy Transition: Case Studies and Code Examples presents a package for academic researchers and industries working on water resources and carbon capture and storage. This book contains fundamental knowledge on artificial intelligence related to oil and gas sustainability and the industry's pivot to support the energy transition and provides practical applications through case studies and coding flowcharts, addressing gaps and questions raised by academic and industrial partners, including energy engineers, geologists, and environmental scientists. This timely publication provides fundamental and extensive information on advanced AI applications geared to support sustainability and the energy transition for the oil and gas industry. - Reviews the use and applications of AI in energy transition of the oil and gas sectors - Provides fundamental knowledge and academic background of artificial intelligence, including practical applications with real-world examples and coding flowcharts - Showcases the successful implementation of AI in the industry (including geothermal energy)
Author: Yoseph Bar-Cohen
Publisher: CRC Press
ISBN: 1000328422
Category : Technology & Engineering
Languages : en
Pages : 310
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Book Description
Advances in Terrestrial Drilling: Ground, Ice, and Underwater includes the latest drilling and excavation principles and processes for terrestrial environments. The chapters cover the history of drilling and excavation, drill types, drilling techniques and their advantages and associated issues, rock coring including acquisition, damage control, caching and transport, and data interpretation, as well as unconsolidated soil drilling and borehole stability. This book includes a description of the basic science of the drilling process, associated processes of breaking and penetrating various media, the required hardware, and the process of excavation and analysis of the sampled media. Describes recent advances in terrestrial drilling. Discusses drilling in the broadest range of media including terrestrial surfaces, ice and underwater from shallow penetration to very deep. Provides an in-depth description of key drilling techniques and the unified approach to assessing the required tools for given drilling requirements. Discusses environmental effects on drilling, current challenges of drilling and excavation, and methods that are used to address these. Examines novel drilling and excavation approaches. Dr. Yoseph Bar-Cohen is the Supervisor of the Electroactive Technologies Group (http://ndeaa.jpl.nasa.gov/) and a Senior Research Scientist at the Jet Propulsion Lab/Caltech, Pasadena, CA. His research is focused on electro-mechanics including planetary sample handling mechanisms, novel actuators that are driven by such materials as piezoelectric and EAP (also known as artificial muscles), and biomimetics. Dr. Kris Zacny is a Senior Scientist and Vice President of Exploration Systems at Honeybee Robotics, Altadena, CA. His expertise includes space mining, sample handling, soil and rock mechanics, extraterrestrial drilling, and In Situ Resource Utilization (ISRU).
Author: Srikanta Mishra
Publisher: CRC Press
ISBN: 1000823873
Category : Technology & Engineering
Languages : en
Pages : 379
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Book Description
The utilization of machine learning (ML) techniques to understand hidden patterns and build data-driven predictive models from complex multivariate datasets is rapidly increasing in many applied science and engineering disciplines, including geo-energy. Motivated by these developments, Machine Learning Applications in Subsurface Energy Resource Management presents a current snapshot of the state of the art and future outlook for ML applications to manage subsurface energy resources (e.g., oil and gas, geologic carbon sequestration, and geothermal energy). Covers ML applications across multiple application domains (reservoir characterization, drilling, production, reservoir modeling, and predictive maintenance) Offers a variety of perspectives from authors representing operating companies, universities, and research organizations Provides an array of case studies illustrating the latest applications of several ML techniques Includes a literature review and future outlook for each application domain This book is targeted at practicing petroleum engineers or geoscientists interested in developing a broad understanding of ML applications across several subsurface domains. It is also aimed as a supplementary reading for graduate-level courses and will also appeal to professionals and researchers working with hydrogeology and nuclear waste disposal.
Author: Yoseph Bar-Cohen
Publisher: CRC Press
ISBN: 1000752879
Category : Technology & Engineering
Languages : en
Pages : 686
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Book Description
Covers both the most recent advances in terrestrial and extraterrestrial drilling. Discusses drilling in the broadest range of media including ground, ice, underwater and planetary surfaces from shallow to very deep. Provides a comprehensive description of key drilling techniques and the efforts to develop unified approach to assessing the required tools for given drilling requirements. Discusses how environment affects drilling and approaches to addressing the effects and current challenges of drilling and excavation on other planets. Examines novel drilling and excavation approaches.
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: Y. Z. Ma
Publisher: Springer
ISBN: 3030178609
Category : Technology & Engineering
Languages : en
Pages : 646
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Book Description
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.
Author: Fred Aminzadeh
Publisher: John Wiley & Sons
ISBN: 1119879698
Category : Science
Languages : en
Pages : 613
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Book Description
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.
Author: Buddhima Indraratna
Publisher: Springer Nature
ISBN: 9819782457
Category :
Languages : en
Pages : 242
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Book Description
Author: Jonathan W-C Wong
Publisher: Elsevier
ISBN: 0444636757
Category : Science
Languages : en
Pages : 532
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Book Description
Current Developments in Biotechnology and Bioengineering: Solid Waste Management provides extensive coverage of new developments, state-of-the-art technologies, and potential future trends, reviewing the latest innovative developments in environmental biotechnology and bioengineering as they pertain to solid wastes, also revealing current research priority areas in solid waste treatment and management. The fate of solid wastes can be divided into three major areas, recycling, energy recovery, and safe disposal. From this foundation, the book covers such key areas as biotechnological production of value added products from solid waste, bioenergy production from various organic solid wastes, and biotechnological solutions for safe, environmentally-friendly treatment and disposal. The state of the art situation, potential advantages, and limitations are discussed, along with proposed strategies on how to overcome limitations. - Reviews available bioprocesses for the production of bioproducts from solid waste - Outlines processes for the production of energy from solid waste using biochemical conversion processes - Lists various environmentally friendly treatments of solid waste and its safe disposal
