Implementation And Interpretation Of Machine And Deep Learning To Applied Subsurface Geological Problems
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Implementation And Interpretation Of Machine And Deep Learning To Applied Subsurface Geological Problems
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Author : David A. Wood
language : en
Publisher: Elsevier
Release Date : 2025-02-18
Implementation And Interpretation Of Machine And Deep Learning To Applied Subsurface Geological Problems written by David A. Wood and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-18 with Technology & Engineering categories.
Implementation and Interpretation of Machine and Deep Learning to Applied Subsurface Geological Problems: Prediction Models Exploiting Well-Log Information explores machine and deep learning models for subsurface geological prediction problems commonly encountered in applied resource evaluation and reservoir characterization tasks. The book provides insights into how the performance of ML/DL models can be optimized—and sparse datasets of input variables enhanced and/or rescaled—to improve prediction performances. A variety of topics are covered, including regression models to estimate total organic carbon from well-log data, predicting brittleness indexes in tight formation sequences, trapping mechanisms in potential sub-surface carbon storage reservoirs, and more.Each chapter includes its own introduction, summary, and nomenclature sections, along with one or more case studies focused on prediction model implementation related to its topic. - Addresses common applied geological problems focused on machine and deep learning implementation with case studies - Considers regression, classification, and clustering machine learning methods and how to optimize and assess their performance, considering suitable error and accuracy metric - Contrasts the pros and cons of multiple machine and deep learning methods - Includes techniques to improve the identification of geological carbon capture and storage reservoirs, a key part of many energy transition strategies
Machine Learning For Subsurface Characterization
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Author : Siddharth Misra
language : en
Publisher: Gulf Professional Publishing
Release Date : 2019-10-12
Machine Learning For Subsurface Characterization written by Siddharth Misra 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 2019-10-12 with Technology & Engineering categories.
Machine Learning for Subsurface Characterization develops and applies neural networks, random forests, deep learning, unsupervised learning, Bayesian frameworks, and clustering methods for subsurface characterization. Machine learning (ML) focusses on developing computational methods/algorithms that learn to recognize patterns and quantify functional relationships by processing large data sets, also referred to as the "big data." Deep learning (DL) is a subset of machine learning that processes "big data" to construct numerous layers of abstraction to accomplish the learning task. DL methods do not require the manual step of extracting/engineering features; however, it requires us to provide large amounts of data along with high-performance computing to obtain reliable results in a timely manner. This reference helps the engineers, geophysicists, and geoscientists get familiar with data science and analytics terminology relevant to subsurface characterization and demonstrates the use of data-driven methods for outlier detection, geomechanical/electromagnetic characterization, image analysis, fluid saturation estimation, and pore-scale characterization in the subsurface. - Learn from 13 practical case studies using field, laboratory, and simulation data - Become knowledgeable with data science and analytics terminology relevant to subsurface characterization - Learn frameworks, concepts, and methods important for the engineer's and geoscientist's toolbox needed to support
Advances In Subsurface Data Analytics
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Author : Shuvajit Bhattacharya
language : en
Publisher: Elsevier
Release Date : 2022-05-18
Advances In Subsurface Data Analytics written by Shuvajit Bhattacharya and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-18 with Science categories.
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
Machine Learning And Artificial Intelligence In Geosciences
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Author :
language : en
Publisher: Academic Press
Release Date : 2020-09-22
Machine Learning And Artificial Intelligence In Geosciences written by and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-09-22 with Science categories.
Advances in Geophysics, Volume 61 - Machine Learning and Artificial Intelligence in Geosciences, the latest release in this highly-respected publication in the field of geophysics, contains new chapters on a variety of topics, including a historical review on the development of machine learning, machine learning to investigate fault rupture on various scales, a review on machine learning techniques to describe fractured media, signal augmentation to improve the generalization of deep neural networks, deep generator priors for Bayesian seismic inversion, as well as a review on homogenization for seismology, and more. - Provides high-level reviews of the latest innovations in geophysics - Written by recognized experts in the field - Presents an essential publication for researchers in all fields of geophysics
Rock Physics Of Unconventional Reservoirs Volume Ii
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Author : Qiaomu Qi
language : en
Publisher: Frontiers Media SA
Release Date : 2024-10-07
Rock Physics Of Unconventional Reservoirs Volume Ii written by Qiaomu Qi and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-07 with Science categories.
Unconventional resources with commercial interest in the world mainly include heavy oils, shales, coalbed methane, and tight gas sands. The production and development of these resources has changed the global energy supply pattern. Quantitative interpretation of geophysical data in the exploration, well-logging, and engineering development of unconventional resources requires a comprehensive understanding of physical properties of rocks and their relationships. The research of rock physics provides an interdisciplinary treatment of physical properties, whether related to geological, geophysical, or geomechanical methodologies. The development of new rock physics methods is essential when integrating core, well-log, seismic data to improve the accuracy of formation evaluation and reservoir characterization. The composition, internal structure, and thermodynamic environment of reservoir rocks are complex and vary with different regions. This becomes particularly evident for unconventional reservoirs with strong macro- and micro-scopic heterogeneities. The diversity of exploration targets and complexity of reservoir characteristics pose great challenges to the applicability of existing rock physics experiments and theories. There are potential risks in directly using existing empirical relations and physical models to guide geophysical interpretation since spurious results may occur. Therefore, it is imperative to explore more applicable rock physics methods according to the petrophysical nature of actual reservoirs.
Applications Of Machine Learning In Volcanology
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Author : Bellina Di Lieto
language : en
Publisher: Frontiers Media SA
Release Date : 2025-04-29
Applications Of Machine Learning In Volcanology written by Bellina Di Lieto and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-29 with Science categories.
The characterization of volcano state is not a simple task due the complexity of physics processes underway. Understanding their evolution prior to and during eruptions is a critical point for identifying transitions in volcanic state. Permanent monitoring networks are developed for such a purpose. With the increase of the number of monitoring sites, the amount of available continuous data coming from different sources (infrasonic, seismic, GPS, geochemical, etc.) has increased exponentially and extracting the huge amount of information this data brings, represents a non-trivial task for researchers, who are always more often looking at the potentiality of computer algorithms to find correlations among them. Recent developments in the field of Machine Learning (ML) have proven to be very useful and efficient for automatic discrimination, decision, prediction, clustering and information extraction in many fields, including volcanology. In recent times, Deep Learning has seen rapid growth in its popularity along with other supervised strategies, such as Support Vectors Machines and Recurrent neural networks (RNN), which have consistently been applied with success to broader and broader sets of applications and fields. However, supervised machine learning requires labels for training, and obtaining these labels for large volumes of seismic and volcanic data is a very demanding and challenging task. Therefore, semi-supervised and unsupervised methods, such as Self-organized Maps, have been applied with success, to extract relevant information from huge amounts of unlabelled data. In seismic and deformative data processing, these techniques are used for waveform inversion, automatic picking of first arrivals, and interpretation of peculiar characteristics of transients. ML is helpful in the discrimination of magmatic complexes, in distinguishing tectonic settings of volcanic rocks, in the evaluation of correlations between volcanic signals and the chemico-physical composition of erupted materials. Other applications of ML in volcanology include the analysis and classification of geological, geochemical and petrological “static” data to infer for example, the possible source and mechanism of observed deposits, the analysis of satellite imagery to quickly classify vast regions difficult to investigate on the ground or, again, to detect changes that could indicate an unrest. The results obtained with the help of these algorithms would otherwise represent for researchers’ tasks hard to be solved with the usual standard methodologies.
Cybercartography
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Author : D.R. Fraser Taylor
language : en
Publisher: Elsevier
Release Date : 2006-01-12
Cybercartography written by D.R. Fraser Taylor and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-01-12 with Science categories.
For generations, the map has been central to how societies function all over the world. Cybercartography is a new paradigm for maps and mapping in the information era. Defined as "the organization, presentation, analysis and communication of spatially referenced information on a wide variety of topics of interest to society, cybercartography is presented in an interactive, dynamic, multisensory format with the use of multimedia and multimodal interfaces. Cybercartography: Theory and Practice examines the major elements of cybercartography and emphasizes the importance of interaction between theory and practice in developing a paradigm which moves beyond the concept of Geographic Information Systems and Geographical Information Science. It argues for the centrality of the map as part of an integrated information, communication, and analytical package.This volume is a result of a multidisciplinary team effort and has benefited from the input of partners from government, industry and other organizations. The international team reports on major original cybercartographic research and practice from a variety of disciplinary perspectives, including the humanities, social sciences including human factors psychology, cybernetics, English literature, cultural mediation, cartography, and geography. This new synthesis has intrinsic value for industries, the general public, and the relationships between mapping and the development of user-centered multimedia interfaces.* Discusses the centrality of the map and its importance in the information era * Provides an interdisciplinary approach with contributions from psychology, music, and language and literature * Describes qualitative and quantitative aspects of cybercartography and the importance of societal context in the interaction between theory and practice* Contains an interactive CD-Rom containing color images, links to websites, plus other important information to capture the dynamic and interactive elements of cybercartography
Advanced Reservoir Engineering
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Author : Tarek Ahmed
language : en
Publisher: Elsevier
Release Date : 2011-03-15
Advanced Reservoir Engineering written by Tarek Ahmed and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-03-15 with Technology & Engineering categories.
Advanced Reservoir Engineering offers the practicing engineer and engineering student a full description, with worked examples, of all of the kinds of reservoir engineering topics that the engineer will use in day-to-day activities. In an industry where there is often a lack of information, this timely volume gives a comprehensive account of the physics of reservoir engineering, a thorough knowledge of which is essential in the petroleum industry for the efficient recovery of hydrocarbons.Chapter one deals exclusively with the theory and practice of transient flow analysis and offers a brief but thorough hands-on guide to gas and oil well testing. Chapter two documents water influx models and their practical applications in conducting comprehensive field studies, widely used throughout the industry. Later chapters include unconventional gas reservoirs and the classical adaptations of the material balance equation.* An essential tool for the petroleum and reservoir engineer, offering information not available anywhere else* Introduces the reader to cutting-edge new developments in Type-Curve Analysis, unconventional gas reservoirs, and gas hydrates * Written by two of the industry's best-known and respected reservoir engineers
Piping And Pipelines Assessment Guide
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Author : Keith Escoe
language : en
Publisher: Elsevier
Release Date : 2006-04-10
Piping And Pipelines Assessment Guide written by Keith Escoe and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-04-10 with Technology & Engineering categories.
Whether it's called "fixed equipment (at ExxonMobil), "stationary equipment (at Shell), or "static equipment (in Europe), this type of equipment is the bread and butter of any process plant. Used in the petrochemical industry, pharmaceutical industry, food processing industry, paper industry, and the manufacturing process industries, stationary equipment must be kept operational and reliable for companies to maintain production and for employees to be safe from accidents. This series, the most comprehensive of its kind, uses real-life examples and time-tested rules of thumb to guide the mechanical engineer through issues of reliability and fitness-for-service. This volume on piping and pipeline assessment is the only handbook that the mechanical or pipeline engineer needs to assess pipes and pipelines for reliability and fitness-for-service.* Provides essential insight to make informed decisions on when to run, alter, repair, monitor, or replace equipment* How to perform these type of assessments and calculations on pipelines is a 'hot' issue in the petrochemical industry at this time* There is very little information on the market right now for pipers and pipeliners with regard to pipe and pipeline fitness-for-service
Handbook Of Industrial Hydrocarbon Processes
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Author : James G. Speight
language : en
Publisher: Gulf Professional Publishing
Release Date : 2010-12-24
Handbook Of Industrial Hydrocarbon Processes written by James G. Speight 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 2010-12-24 with Technology & Engineering categories.
Written by an author with over 38 years of experience in the chemical and petrochemical process industry, this handbook will present an analysis of the process steps used to produce industrial hydrocarbons from various raw materials. It is the first book to offer a thorough analysis of external factors effecting production such as: cost, availability and environmental legislation. An A-Z list of raw materials and their properties are presented along with a commentary regarding their cost and availability. Specific processing operations described in the book include: distillation, thermal cracking and coking, catalytic methods, hydroprocesses, thermal and catalytic reforming, isomerization, alkylation processes, polymerization processes, solvent processes, water removal, fractionation and acid gas removal. - Flow diagrams and descriptions of more than 250 leading-edge process technologies - An analysis of chemical reactions and process steps that are required to produce chemicals from various raw materials - Properties, availability and environmental impact of various raw materials used in hydrocarbon processing