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Machine Learning for Subsurface Characterization, Misra, Siddharth


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Цена: 18528.00р.
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Автор: Misra, Siddharth
Название:  Machine Learning for Subsurface Characterization
Перевод названия: Сиддхарт Мисра: Машинное обучение для получения характеристик подземных пластов
ISBN: 9780128177365
Издательство: Elsevier Science
Классификация:



ISBN-10: 0128177365
Обложка/Формат: Paperback
Страницы: 230
Вес: 0.34 кг.
Дата издания: 01.06.2019
Язык: English
Размер: 229 x 153 x 22
Основная тема: Petroleum and petrochemical engineering
Ссылка на Издательство: Link
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Поставляется из: Европейский союз
Описание:

To continue to meet demand while keeping costs down, petroleum and reservoir engineers know it is critical to utilize their assets data through more complex modeling methods, and machine learning and data analytics is the known alternative approach to accurately represent the complexity of fluid-filled rocks. With a lack of training resources available, Machine Learning for Subsurface Characterization focuses on the development and application of neural networks, deep learning, unsupervised learning, reinforcement learning, and clustering methods for subsurface characterization under constraints. Such constraints are encountered during subsurface engineering operations due to financial, operational, regulatory, risk, technological, and environmental challenges.

This reference teaches how to do more with less. Used to develop tools and techniques of data-driven predictive modelling and machine learning for subsurface engineering and science, engineers will be introduced to methods of generating subsurface signals and analyzing the complex relationships within various subsurface signals using machine learning. Algorithmic procedures in MATLAB, R, PYTHON, and TENSORFLOW are displayed in text and through online instructional video to assist training and learning. Field cases are also presented to understand real-world applications, with a particular focus on examples involving shale reservoirs.

Explaining the concept of machine learning, advantages to the industry, and applications applied to complex subsurface rocks, Machine Learning for Subsurface Characterization delivers a missing piece to the reservoir engineers toolbox needed to support todays complex operations.

  • Focus on applying predictive modelling and machine learning from real case studies and Q&A sessions at the end of each chapter
  • Learn how to develop codes such as MATLAB, PYTHON, R, and TENSORFLOW with step-by-step guides included
  • Visually learn code development with video demonstrations included



Pattern Recognition and Machine Learning

Автор: Christopher M. Bishop
Название: Pattern Recognition and Machine Learning
ISBN: 0387310738 ISBN-13(EAN): 9780387310732
Издательство: Springer
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Цена: 11878.00 р.
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Описание: Familiarity with multivariate calculus and basic linear algebra is required, and some experience in the use of probabilities would be helpful though not essential as the book includes a self-contained introduction to basic probability theory.

Machine Learning

Автор: Kevin Murphy
Название: Machine Learning
ISBN: 0262018020 ISBN-13(EAN): 9780262018029
Издательство: MIT Press
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Цена: 18622.00 р.
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Описание:

A comprehensive introduction to machine learning that uses probabilistic models and inference as a unifying approach.

Today's Web-enabled deluge of electronic data calls for automated methods of data analysis. Machine learning provides these, developing methods that can automatically detect patterns in data and then use the uncovered patterns to predict future data. This textbook offers a comprehensive and self-contained introduction to the field of machine learning, based on a unified, probabilistic approach.

The coverage combines breadth and depth, offering necessary background material on such topics as probability, optimization, and linear algebra as well as discussion of recent developments in the field, including conditional random fields, L1 regularization, and deep learning. The book is written in an informal, accessible style, complete with pseudo-code for the most important algorithms. All topics are copiously illustrated with color images and worked examples drawn from such application domains as biology, text processing, computer vision, and robotics. Rather than providing a cookbook of different heuristic methods, the book stresses a principled model-based approach, often using the language of graphical models to specify models in a concise and intuitive way. Almost all the models described have been implemented in a MATLAB software package -- PMTK (probabilistic modeling toolkit) -- that is freely available online. The book is suitable for upper-level undergraduates with an introductory-level college math background and beginning graduate students.

Practical Machine Learning with H2O

Автор: Darren Cook
Название: Practical Machine Learning with H2O
ISBN: 149196460X ISBN-13(EAN): 9781491964606
Издательство: Wiley
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Цена: 6334.00 р.
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Описание: This hands-on guide teaches you how to use H20 with only minimal math and theory behind the learning algorithms.

Data Mining: Practical Machine Learning Tools and Techniques,

Автор: Ian H. Witten
Название: Data Mining: Practical Machine Learning Tools and Techniques,
ISBN: 0123748569 ISBN-13(EAN): 9780123748560
Издательство: Elsevier Science
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Цена: 8695.00 р.
Наличие на складе: Поставка под заказ.

Описание: Like the popular second edition, Data Mining: Practical Machine Learning Tools and Techniques offers a thorough grounding in machine learning concepts as well as practical advice on applying machine learning tools and techniques in real-world data mining situations. Inside, you'll learn all you need to know about preparing inputs, interpreting outputs, evaluating results, and the algorithmic methods at the heart of successful data mining?including both tried-and-true techniques of today as well as methods at the leading edge of contemporary research. <br><br>Complementing the book is a fully functional platform-independent open source Weka software for machine learning, available for free download. <br><br>The book is a major revision of the second edition that appeared in 2005. While the basic core remains the same, it has been updated to reflect the changes that have taken place over the last four or five years. The highlights for the updated new edition include completely revised technique sections; new chapter on Data Transformations, new chapter on Ensemble Learning, new chapter on Massive Data Sets, a new ?book release? version of the popular Weka machine learning open source software (developed by the authors and specific to the Third Edition); new material on ?multi-instance learning?; new information on ranking the classification, plus comprehensive updates and modernization throughout. All in all, approximately 100 pages of new material.<br> <br><br>* Thorough grounding in machine learning concepts as well as practical advice on applying the tools and techniques<br><br>* Algorithmic methods at the heart of successful data mining?including tired and true methods as well as leading edge methods<br><br>* Performance improvement techniques that work by transforming the input or output<br><br>* Downloadable Weka, a collection of machine learning algorithms for data mining tasks, including tools for data pre-processing, classification, regression, clustering, association rules, and visualization?in an updated, interactive interface. <br>

Machine Learning for Hackers

Автор: Conway Drew, White John Myles
Название: Machine Learning for Hackers
ISBN: 1449303714 ISBN-13(EAN): 9781449303716
Издательство: Wiley
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Цена: 6334.00 р.
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Описание: Now that storage and collection technologies are cheaper and more precise, methods for extracting relevant information from large datasets is within the reach any experienced programmer willing to crunch data.

Subsurface Upgrading of Heavy Crude Oils and Bitumen

Автор: Cesar Ovalles
Название: Subsurface Upgrading of Heavy Crude Oils and Bitumen
ISBN: 1138744441 ISBN-13(EAN): 9781138744448
Издательство: Taylor&Francis
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Цена: 26796.00 р.
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Описание:

Heavy crude oils and bitumen represent more than 50% of all hydrocarbons available on the planet. These feedstocks have a low amount of distillable material and high level of contaminants that make their production, transportation, and refining difficult and costly by conventional technologies. Subsurface Upgrading of Heavy Crude Oils and Bitumen is of interest to the petroleum industry mainly because of the advantages compared to aboveground counterparts.

The author presents an in-depth account and a critical review of the progress of industry and academia in underground or In-Situ upgrading of heavy, extra-heavy oils and bitumen, as reported in the patent and open literature. This work is aimed to be a standalone monograph, so three chapters are dedicated to the composition of petroleum and fundamentals of crude oil production and refining.

Key Features:

    • Offers a multidisciplinary scope that will appeal to chemists, geologists, biologists, chemical engineers, and petroleum engineers
    • Presents the advantages and disadvantages of the technologies considered
    • Discusses economic and environmental considerations for all the routes evaluated and offers perspectives from experts in the field working with highlighted technologies
Python machine learning -

Автор: Raschka, Sebastian Mirjalili, Vahid
Название: Python machine learning -
ISBN: 1787125939 ISBN-13(EAN): 9781787125933
Издательство: Неизвестно
Цена: 8091.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This second edition of Python Machine Learning by Sebastian Raschka is for developers and data scientists looking for a practical approach to machine learning and deep learning. In this updated edition, you`ll explore the machine learning process using Python and the latest open source technologies, including scikit-learn and TensorFlow 1.x.

Understanding Machine Learning

Автор: Shalev-Shwartz
Название: Understanding Machine Learning
ISBN: 1107057132 ISBN-13(EAN): 9781107057135
Издательство: Cambridge Academ
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Цена: 11194.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: Machine learning is one of the fastest growing areas of computer science, with far-reaching applications. This book explains the principles behind the automated learning approach and the considerations underlying its usage. The authors explain the `hows` and `whys` of machine-learning algorithms, making the field accessible to both students and practitioners.

Learning machine translation

Название: Learning machine translation
ISBN: 0262072971 ISBN-13(EAN): 9780262072977
Издательство: MIT Press
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Цена: 1709.00 р.
Наличие на складе: Нет в наличии.

Описание: The Internet gives us access to a wealth of information in languages we don`t understand. The investigation of automated or semi-automated approaches to translation has become a thriving research field with enormous commercial potential. This title investigates how Machine Learning techniques can improve Statistical Machine Translation.

Petrophysical Characterization and Fluids Transport in Unconventional Reservoirs

Автор: Jianchao Cai and Xiangyun Hu
Название: Petrophysical Characterization and Fluids Transport in Unconventional Reservoirs
ISBN: 0128166983 ISBN-13(EAN): 9780128166987
Издательство: Elsevier Science
Рейтинг:
Цена: 21391.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: Petrophysical Characterization and Fluids Transport in Unconventional Reservoirs presents a comprehensive look at these new methods and technologies for the petrophysical characterization of unconventional reservoirs, including recent theoretical advances and modeling on fluids transport in unconventional reservoirs. The book is a valuable tool for geoscientists and engineers working in academia and industry. Many novel technologies and approaches, including petrophysics, multi-scale modelling, rock reconstruction and upscaling approaches are discussed, along with the challenge of the development of unconventional reservoirs and the mechanism of multi-phase/multi-scale flow and transport in these structures.

Stratigraphic Reservoir Characterization for Petroleum Geologists

Автор: Roger M. Slatt
Название: Stratigraphic Reservoir Characterization for Petroleum Geologists
ISBN: 0444563652 ISBN-13(EAN): 9780444563651
Издательство: Elsevier Science
Рейтинг:
Цена: 20380.00 р.
Наличие на складе: Поставка под заказ.

Описание: A reservoir characterization as a discipline grew out of the recognition that more oil and gas could be extracted from reservoirs if the geology of the reservoir was understood. This title describes different types of sandstone and shale reservoirs and applications of standard, new, and emerging technologies.

Fuel Property Estimation and Combustion Process Characterization

Автор: Kiang, Yen-Hsiung
Название: Fuel Property Estimation and Combustion Process Characterization
ISBN: 0128134739 ISBN-13(EAN): 9780128134733
Издательство: Elsevier Science
Рейтинг:
Цена: 21391.00 р.
Наличие на складе: Поставка под заказ.

Описание:

Fuel Property Estimation and Combustion Process Characterization is a thorough tool book, which provides readers with the most up-to-date, valuable methodologies to efficiently and cost-effectively attain useful properties of all types of fuels and achieve combustion process characterizations for more efficient design and better operation. Through extensive experience in fuels and combustion, Kiang has developed equations and methodologies that can readily obtain reasonable properties for all types of fuels (including wastes and biomass), which enable him to provide guidance for designers and operators in the combustion field, in order to ensure the design, operation, and diagnostics of all types of combustion systems are of the highest quality and run at optimum efficiency.

Written for professionals and researchers in the renewable energy, combustion, chemical, and mechanical engineering fields, the information in this book will equip readers with detailed guidance on how to reliably obtain properties of fuels quickly for the design, operation and diagnostics of combustion systems to achieve highly efficient combustion processes.

  • Presents models for quick estimation of fuel properties without going through elaborate, costly and time consuming sampling and laboratory testing
  • Offers methodologies to determine combustion process characteristics for designing and deploying combustion systems
  • Examines the fundamentals of combustion applied to energy systems, including thermodynamics of traditional and alternative fuels combustion
  • Presents a fuel property database for over 1400 fuels
  • Includes descriptive application of big data technology, using dual properties analysis as an example
  • Provides specific technical solutions for combustion, fuels and waste processing

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