Advances In Subsurface Data Analytics

Author : Shuvajit Bhattacharya,Haibin Di
Publisher : Elsevier
Page : 378 pages
File Size : 55,8 Mb
Release : 2022-05-18
Category : Computers
ISBN : 9780128223086

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Advances in Subsurface Data Analytics by Shuvajit Bhattacharya,Haibin Di Pdf

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 : Springer Nature
Page : 172 pages
File Size : 40,7 Mb
Release : 2021-05-03
Category : Technology & Engineering
ISBN : 9783030717681

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A Primer on Machine Learning in Subsurface Geosciences by Shuvajit Bhattacharya Pdf

This book provides readers with a timely review and discussion of the success, promise, and perils of machine learning in geosciences. It explores the fundamentals of data science and machine learning, and how their advances have disrupted the traditional workflows used in the industry and academia, including geology, geophysics, petrophysics, geomechanics, and geochemistry. It then presents the real-world applications and explains that, while this disruption has affected the top-level executives, geoscientists as well as field operators in the industry and academia, machine learning will ultimately benefit these users. The book is written by a practitioner of machine learning and statistics, keeping geoscientists in mind. It highlights the need to go beyond concepts covered in STAT 101 courses and embrace new computational tools to solve complex problems in geosciences. It also offers practitioners, researchers, and academics insights into how to identify, develop, deploy, and recommend fit-for-purpose machine learning models to solve real-world problems in subsurface geosciences.

Author : Daniel Asante Otchere
Publisher : CRC Press
Page : 368 pages
File Size : 45,6 Mb
Release : 2024-02-06
Category : Science
ISBN : 9781003860228

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Data Science and Machine Learning Applications in Subsurface Engineering by Daniel Asante Otchere Pdf

This book covers unsupervised learning, supervised learning, clustering approaches, feature engineering, explainable AI and multioutput regression models for subsurface engineering problems. Processing voluminous and complex data sets are the primary focus of the field of machine learning (ML). ML aims to develop data-driven methods and computational algorithms that can learn to identify complex and non-linear patterns to understand and predict the relationships between variables by analysing extensive data. Although ML models provide the final output for predictions, several steps need to be performed to achieve accurate predictions. These steps, data pre-processing, feature selection, feature engineering and outlier removal, are all contained in this book. New models are also developed using existing ML architecture and learning theories to improve the performance of traditional ML models and handle small and big data without manual adjustments. This research-oriented book will help subsurface engineers, geophysicists, and geoscientists become familiar with data science and ML advances relevant to subsurface engineering. Additionally, it demonstrates the use of data-driven approaches for salt identification, seismic interpretation, estimating enhanced oil recovery factor, predicting pore fluid types, petrophysical property prediction, estimating pressure drop in pipelines, bubble point pressure prediction, enhancing drilling mud loss, smart well completion and synthetic well log predictions.

Author : Yoseph Bar-Cohen,Kris Zacny
Publisher : CRC Press
Page : 310 pages
File Size : 54,5 Mb
Release : 2020-12-21
Category : Technology & Engineering
ISBN : 9781000328424

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Advances in Terrestrial Drilling: by Yoseph Bar-Cohen,Kris Zacny Pdf

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 : Keith R. Holdaway
Publisher : John Wiley & Sons
Page : 389 pages
File Size : 44,8 Mb
Release : 2014-05-27
Category : Business & Economics
ISBN : 9781118779316

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Harness Oil and Gas Big Data with Analytics by Keith R. Holdaway Pdf

Use big data analytics to efficiently drive oil and gas exploration and production Harness Oil and Gas Big Data with Analytics provides a complete view of big data and analytics techniques as they are applied to the oil and gas industry. Including a compendium of specific case studies, the book underscores the acute need for optimization in the oil and gas exploration and production stages and shows how data analytics can provide such optimization. This spans exploration, development, production and rejuvenation of oil and gas assets. The book serves as a guide for fully leveraging data, statistical, and quantitative analysis, exploratory and predictive modeling, and fact-based management to drive decision making in oil and gas operations. This comprehensive resource delves into the three major issues that face the oil and gas industry during the exploration and production stages: Data management, including storing massive quantities of data in a manner conducive to analysis and effectively retrieving, backing up, and purging data Quantification of uncertainty, including a look at the statistical and data analytics methods for making predictions and determining the certainty of those predictions Risk assessment, including predictive analysis of the likelihood that known risks are realized and how to properly deal with unknown risks Covering the major issues facing the oil and gas industry in the exploration and production stages, Harness Big Data with Analytics reveals how to model big data to realize efficiencies and business benefits.

Author : Srikanta Mishra
Publisher : CRC Press
Page : 379 pages
File Size : 47,7 Mb
Release : 2022-12-27
Category : Technology & Engineering
ISBN : 9781000823875

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Machine Learning Applications in Subsurface Energy Resource Management by Srikanta Mishra Pdf

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,Kris Zacny
Publisher : CRC Press
Page : 686 pages
File Size : 43,9 Mb
Release : 2021-08-26
Category : Technology & Engineering
ISBN : 9781000752878

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Advances in Terrestrial and Extraterrestrial Drilling: by Yoseph Bar-Cohen,Kris Zacny Pdf

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 : Fred Aminzadeh,Cenk Temizel,Yasin Hajizadeh
Publisher : John Wiley & Sons
Page : 613 pages
File Size : 40,5 Mb
Release : 2022-09-21
Category : Science
ISBN : 9781119879695

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Artificial Intelligence and Data Analytics for Energy Exploration and Production by Fred Aminzadeh,Cenk Temizel,Yasin Hajizadeh Pdf

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 : S.M. Agar,S. Geiger
Publisher : Geological Society of London
Page : 473 pages
File Size : 49,9 Mb
Release : 2015-02-02
Category : Science
ISBN : 9781862396593

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Fundamental Controls on Fluid Flow in Carbonates by S.M. Agar,S. Geiger Pdf

This volume highlights key challenges for fluid-flow prediction in carbonate reservoirs, the approaches currently employed to address these challenges and developments in fundamental science and technology. The papers span methods and case studies that highlight workflows and emerging technologies in the fields of geology, geophysics, petrophysics, reservoir modelling and computer science. Topics include: detailed pore-scale studies that explore fundamental processes and applications of imaging and flow modelling at the pore scale; case studies of diagenetic processes with complementary perspectives from reactive transport modelling; novel methods for rock typing; petrophysical studies that investigate the impact of diagenesis and fault-rock properties on acoustic signatures; mechanical modelling and seismic imaging of faults in carbonate rocks; modelling geological influences on seismic anisotropy; novel approaches to geological modelling; methods to represent key geological details in reservoir simulations and advances in computer visualization, analytics and interactions for geoscience and engineering.

Author : Seeram Ramakrishna
Publisher : Springer Nature
Page : 267 pages
File Size : 53,7 Mb
Release : 2024-05-19
Category : Electronic
ISBN : 9789819705894

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Handbook of Materials Circular Economy by Seeram Ramakrishna Pdf

Author : Y. Z. Ma
Publisher : Springer
Page : 640 pages
File Size : 50,9 Mb
Release : 2019-07-15
Category : Technology & Engineering
ISBN : 9783030178604

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Quantitative Geosciences: Data Analytics, Geostatistics, Reservoir Characterization and Modeling by Y. Z. Ma Pdf

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 : Kingshuk Srivastava,Thipendra P Singh,Manas Ranjan Pradhan,Vinit Kumar Gunjan
Publisher : CRC Press
Page : 187 pages
File Size : 48,5 Mb
Release : 2023-11-20
Category : Technology & Engineering
ISBN : 9781000995114

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Understanding Data Analytics and Predictive Modelling in the Oil and Gas Industry by Kingshuk Srivastava,Thipendra P Singh,Manas Ranjan Pradhan,Vinit Kumar Gunjan Pdf

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.

Author : National Academies of Sciences, Engineering, and Medicine,Division on Earth and Life Studies,Nuclear and Radiation Studies Board,Committee on Independent Assessment of Science and Technology for the Department of Energy's Defense Environmental Cleanup Program
Publisher : National Academies Press
Page : 123 pages
File Size : 47,9 Mb
Release : 2019-03-27
Category : Medical
ISBN : 9780309487788

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Independent Assessment of Science and Technology for the Department of Energy's Defense Environmental Cleanup Program by National Academies of Sciences, Engineering, and Medicine,Division on Earth and Life Studies,Nuclear and Radiation Studies Board,Committee on Independent Assessment of Science and Technology for the Department of Energy's Defense Environmental Cleanup Program Pdf

The National Defense Authorization Act for fiscal year 2017 contained a request for a National Academies of Sciences, Engineering, and Medicine review and assessment of science and technology development efforts within the Department of Energy's Office of Environmental Management (DOE-EM). This technical report is the result of the review and presents findings and recommendations.

Author : Deepak Garg,Kit Wong,Jagannathan Sarangapani,Suneet Kumar Gupta
Publisher : Springer Nature
Page : 507 pages
File Size : 48,7 Mb
Release : 2021-02-10
Category : Computers
ISBN : 9789811604010

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Advanced Computing by Deepak Garg,Kit Wong,Jagannathan Sarangapani,Suneet Kumar Gupta Pdf

This two-volume set (CCIS 1367-1368) constitutes reviewed and selected papers from the 10th International Advanced Computing Conference, IACC 2020, held in December 2020. The 65 full papers and 2 short papers presented in two volumes were thorougly reviewed and selected from 286 submissions. The papers are organized in the following topical sections: Application of Artificial Intelligence and Machine Learning in Healthcare; Using Natural Language Processing for Solving Text and Language related Applications; Using Different Neural Network Architectures for Interesting applications; ​Using AI for Plant and Animal related Applications.- Applications of Blockchain and IoT.- Use of Data Science for Building Intelligence Applications; Innovations in Advanced Network Systems; Advanced Algorithms for Miscellaneous Domains; New Approaches in Software Engineering.

Author : Siddharth Misra,Hao Li,Jiabo He
Publisher : Gulf Professional Publishing
Page : 442 pages
File Size : 40,9 Mb
Release : 2019-10-12
Category : Technology & Engineering
ISBN : 9780128177372

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Machine Learning for Subsurface Characterization by Siddharth Misra,Hao Li,Jiabo He Pdf

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