Data Science And Machine Learning Applications In Subsurface Engineering

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Data Science And Machine Learning Applications In Subsurface Engineering

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Author : Daniel Asante Otchere
language : en
Publisher: CRC Press
Release Date : 2024-02-06

Data Science And Machine Learning Applications In Subsurface Engineering written by Daniel Asante Otchere and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-02-06 with Science categories.

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.

Machine Learning Applications In Subsurface Energy Resource Management

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Author : Srikanta Mishra
language : en
Publisher: CRC Press
Release Date : 2022-12-27

Machine Learning Applications In Subsurface Energy Resource Management written by Srikanta Mishra and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-12-27 with Technology & Engineering categories.

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.

Machine Learning For Subsurface Characterization

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Author : Siddharth Misra
language : en
Publisher: Gulf Professional Publishing
Release Date : 2020

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 2020 with Big data categories.

Mastering Time Innovative Solutions To Complex Scheduling Problems

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Author : Ali Soofastaei
language : en
Publisher: BoD – Books on Demand
Release Date : 2025-05-07

Mastering Time Innovative Solutions To Complex Scheduling Problems written by Ali Soofastaei and has been published by BoD – Books on Demand this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-07 with Computers categories.

Time is one of our most valuable resources, yet managing it effectively is often one of the toughest challenges. Mastering Time - Innovative Solutions to Complex Scheduling Problems is a comprehensive guide introducing new methods and solutions to solve complex scheduling problems in professional contexts. By mastering these creative solutions, you can gain control over your time. This book presents practical strategies and tools to streamline workflows, optimize resource allocation, and tackle bottlenecks head-on. Whether you are managing multiple projects, balancing competing priorities, or simply seeking to organize your time better, the insights provided in this book will help you unlock new levels of productivity and efficiency. With real-world examples, cutting-edge technologies like artificial intelligence, and time-tested techniques, Mastering Time - Innovative Solutions to Complex Scheduling Problems equips readers with the knowledge and tools to transform even the most challenging schedules into manageable, efficient plans. Dive into the future of scheduling, where complexity is simplified and time is truly mastered.

Machine Intelligence And Data Science Applications

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Author : Amar Ramdane-Cherif
language : en
Publisher: Springer Nature
Release Date : 2023-09-01

Machine Intelligence And Data Science Applications written by Amar Ramdane-Cherif and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-09-01 with Technology & Engineering categories.

This book is a compilation of peer-reviewed papers presented at the International Conference on Machine Intelligence and Data Science Applications (MIDAS 2022), held on October 28 and 29, 2022, at the University of Versailles—Paris-Saclay, France. The book covers applications in various fields like data science, machine intelligence, image processing, natural language processing, computer vision, sentiment analysis, and speech and gesture analysis. It also includes interdisciplinary applications like legal, healthcare, smart society, cyber-physical system, and smart agriculture. The book is a good reference for computer science engineers, lecturers/researchers in the machine intelligence discipline, and engineering graduates.

Proceedings Of The Rocscience International Conference 2023 Ric2023

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Author : Reginald E. Hammah
language : en
Publisher: Springer Nature
Release Date : 2023-11-06

Proceedings Of The Rocscience International Conference 2023 Ric2023 written by Reginald E. Hammah and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-11-06 with Technology & Engineering categories.

This is an open access book. Rocscience is delighted to announce the Rocscience International Conference 2023 (RIC2023), an in-person gathering to be held from April 24–26, 2023, in Toronto, Canada. RIC2023's primary objective is to bring geotechnical professionals together to meet and exchange ideas on important issues and developments in geotechnical engineering, particularly combinations of emerging and mature technologies. The geotechnical industry is rapidly evolving. Engineers are more connected through technology, technology is becoming more integrated than ever, and methods combining these technologies are becoming more prevalent. This movement towards combining technologies led us to the conference theme, “Synergy in Geotechnical Engineering – Success Beyond Individual Technologies.” We believe the time is right to highlight how far the industry has come with various technologies and continues to develop. The conference aims to create an environment that fosters new perspectives and helps attendees delve deeper into innovative approaches. During RIC2023, Rocscience will award the 2023 Lifetime Achievement Medal to Dr. Norbert Morgenstern, an internationally recognized authority in the engineering community. As both a practitioner and educator, Dr. Morgenstern’s contributions to the geotechnical community continue to benefit engineers worldwide, and he will give an address on his career. In addition to keynotes by Dr. Morgernstern and four other distinguished speakers, there will be several technical and networking sessions.

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

Advanced Systems For Monitoring Carbon Sequestration

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Author : Pandey, Hari Mohan
language : en
Publisher: IGI Global
Release Date : 2025-04-17

Advanced Systems For Monitoring Carbon Sequestration written by Pandey, Hari Mohan and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-17 with Technology & Engineering categories.

Advanced systems, such as artificial intelligence (AI), blockchain, and Internet of Things (IoT), have transformative potential in creating intelligent and sustainable solutions for the sequestration management of carbon emissions. Carbon sequestration is important in fighting global warming, and the optimization of carbon shifts markets to a low-carbon economy. They also have real-world applications in areas like agriculture, healthcare, energy, supply chains, and conservation. These practical applications and future trends are critical for understanding and advancing the role of technology in sustainability for a greener and more equitable future. Advanced Systems for Monitoring Carbon Sequestration encourages the development of new tools, algorithms, and platforms for energy efficiency, resource optimization, and environmental conservation. It provides evidence-based recommendations and frameworks that organizations can use to create actionable strategies. Covering topics such as carbon flux modelling, big data platforms, and security protocols, this book is an excellent resource for environmentalists, engineers, computer scientists, business owners, policymakers, researchers, academicians and more.

Knowledge Guided Machine Learning

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Author : Anuj Karpatne
language : en
Publisher: CRC Press
Release Date : 2022-08-15

Knowledge Guided Machine Learning written by Anuj Karpatne and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-08-15 with Business & Economics categories.

Given their tremendous success in commercial applications, machine learning (ML) models are increasingly being considered as alternatives to science-based models in many disciplines. Yet, these "black-box" ML models have found limited success due to their inability to work well in the presence of limited training data and generalize to unseen scenarios. As a result, there is a growing interest in the scientific community on creating a new generation of methods that integrate scientific knowledge in ML frameworks. This emerging field, called scientific knowledge-guided ML (KGML), seeks a distinct departure from existing "data-only" or "scientific knowledge-only" methods to use knowledge and data at an equal footing. Indeed, KGML involves diverse scientific and ML communities, where researchers and practitioners from various backgrounds and application domains are continually adding richness to the problem formulations and research methods in this emerging field. Knowledge Guided Machine Learning: Accelerating Discovery using Scientific Knowledge and Data provides an introduction to this rapidly growing field by discussing some of the common themes of research in KGML using illustrative examples, case studies, and reviews from diverse application domains and research communities as book chapters by leading researchers. KEY FEATURES First-of-its-kind book in an emerging area of research that is gaining widespread attention in the scientific and data science fields Accessible to a broad audience in data science and scientific and engineering fields Provides a coherent organizational structure to the problem formulations and research methods in the emerging field of KGML using illustrative examples from diverse application domains Contains chapters by leading researchers, which illustrate the cutting-edge research trends, opportunities, and challenges in KGML research from multiple perspectives Enables cross-pollination of KGML problem formulations and research methods across disciplines Highlights critical gaps that require further investigation by the broader community of researchers and practitioners to realize the full potential of KGML

Applied Graph Data Science

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Author : Pethuru Raj
language : en
Publisher: Elsevier
Release Date : 2025-01-27

Applied Graph Data Science written by Pethuru Raj and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-27 with Computers categories.

Applied Graph Data Science: Graph Algorithms and Platforms, Knowledge Graphs, Neural Networks, and Applied Use Cases delineates how graph data science significantly empowers the application of data science. The book discusses the emerging paradigm of graph data science in detail along with its practical research and real-world applications. Readers will be enriched with the knowledge of graph data science, graph analytics, algorithms, databases, platforms, and use cases across a variety of research and topics and applications. This book also presents how graphs are used as a programming language, especially demonstrating how Sleptsov Net Computing can contribute as an entirely graphical concurrent processing language for supercomputers. Graph data science is emerging as an expressive and illustrative data structure for optimally representing a variety of data types and their insightful relationships. These data structures include graph query languages, databases, algorithms, and platforms. From here, powerful analytics methods and machine learning/deep learning (ML/DL) algorithms are quickly evolving to analyze and make sense out of graph data. As a result, ground-breaking use cases across scientific research topics and industry verticals are being developed using graph data representation and manipulation. A wide range of complex business and scientific research requirements are efficiently represented and solved through graph data analysis, and Applied Graph Data Science: Graph Algorithms and Platforms, Knowledge Graphs, Neural Networks, and Applied Graph Data Science gives readers both the conceptual foundations and technical methods for applying these powerful techniques. - Provides comprehensive coverage of the emerging paradigm of graph data science and its real-world applications - Gives readers practical guidance on how to approach and solve complex data analysis problems using graph data science, with an emphasis on deep analysis techniques including graph neural networks (GNNs), machine learning, algorithms, graph databases, and graph query languages - Covers extended graph models such as bipartite directed graphs of place-transition nets, graphs with dynamical processes defined on them - Petri and Sleptsov nets, and graphs as programming languages - Presents all the key tools and techniques as well as the foundations of graph theory, including mathematical concepts, research, and graph analytics