Deep Learning For Seismic Data Enhancement And Representation
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Deep Learning For Seismic Data Enhancement And Representation
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Author : Shirui Wang
language : en
Publisher: Springer Nature
Release Date : 2024-12-18
Deep Learning For Seismic Data Enhancement And Representation written by Shirui Wang and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-18 with Science categories.
Seismic imaging is a key component of subsurface exploration, and it depends on a high-quality seismic data acquisition system with effective seismic processing algorithms. Seismic data quality concerns various factors such as acquisition design, environmental constraints, sampling resolution, and noises. The focus of this book is to investigate efficient seismic data representation and signal enhancement solutions by leveraging the powerful feature engineering capability of deep learning. The book delves into seismic data representation and enhancement issues, ranging from seismic acquisition design to subsequent quality improvement and compression technologies. Given the challenges of obtaining suitable labeled training datasets for seismic data processing problems, we concentrate on exploring deep learning approaches that eliminate the need for labels. We combined novel deep learning techniques with conventional seismic data processing methods, and construct networks and frameworks tailored for seismic data processing. The editors and authors of this book come from both academia and industry with hands-on experiences in seismic data processing and imaging.
Enhance Oil And Gas Exploration With Data Driven Geophysical And Petrophysical Models
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Author : Keith R. Holdaway
language : en
Publisher: John Wiley & Sons
Release Date : 2017-10-04
Enhance Oil And Gas Exploration With Data Driven Geophysical And Petrophysical Models written by Keith R. Holdaway and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-10-04 with Business & Economics categories.
Leverage Big Data analytics methodologies to add value to geophysical and petrophysical exploration data Enhance Oil & Gas Exploration with Data-Driven Geophysical and Petrophysical Models demonstrates a new approach to geophysics and petrophysics data analysis using the latest methods drawn from Big Data. Written by two geophysicists with a combined 30 years in the industry, this book shows you how to leverage continually maturing computational intelligence to gain deeper insight from specific exploration data. Case studies illustrate the value propositions of this alternative analytical workflow, and in-depth discussion addresses the many Big Data issues in geophysics and petrophysics. From data collection and context through real-world everyday applications, this book provides an essential resource for anyone involved in oil and gas exploration. Recent and continual advances in machine learning are driving a rapid increase in empirical modeling capabilities. This book shows you how these new tools and methodologies can enhance geophysical and petrophysical data analysis, increasing the value of your exploration data. Apply data-driven modeling concepts in a geophysical and petrophysical context Learn how to get more information out of models and simulations Add value to everyday tasks with the appropriate Big Data application Adjust methodology to suit diverse geophysical and petrophysical contexts Data-driven modeling focuses on analyzing the total data within a system, with the goal of uncovering connections between input and output without definitive knowledge of the system's physical behavior. This multi-faceted approach pushes the boundaries of conventional modeling, and brings diverse fields of study together to apply new information and technology in new and more valuable ways. Enhance Oil & Gas Exploration with Data-Driven Geophysical and Petrophysical Models takes you beyond traditional deterministic interpretation to the future of exploration data analysis.
Metaheuristics In Water Geotechnical And Transport Engineering
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Author : Xin-She Yang
language : en
Publisher: Newnes
Release Date : 2012-09
Metaheuristics In Water Geotechnical And Transport Engineering written by Xin-She Yang and has been published by Newnes this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-09 with Computers categories.
Due to an ever-decreasing supply in raw materials and stringent constraints on conventional energy sources, demand for lightweight, efficient and low cost structures has become crucially important in modern engineering design. This requires engineers to search for optimal and robust design options to address design problems that are often large in scale and highly nonlinear, making finding solutions challenging. In the past two decades, metaheuristic algorithms have shown promising power, efficiency and versatility in solving these difficult optimization problems. This book examines the latest developments of metaheuristics and their applications in water, geotechnical and transport engineering offering practical case studies as examples to demonstrate real world applications. Topics cover a range of areas within engineering, including reviews of optimization algorithms, artificial intelligence, cuckoo search, genetic programming, neural networks, multivariate adaptive regression, swarm intelligence, genetic algorithms, ant colony optimization, evolutionary multiobjective optimization with diverse applications in engineering such as behavior of materials, geotechnical design, flood control, water distribution and signal networks. This book can serve as a supplementary text for design courses and computation in engineering as well as a reference for researchers and engineers in metaheursitics, optimization in civil engineering and computational intelligence. Provides detailed descriptions of all major metaheuristic algorithms with a focus on practical implementation Develops new hybrid and advanced methods suitable for civil engineering problems at all levels Appropriate for researchers and advanced students to help to develop their work
Tensor Computation For Seismic Data Processing
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Author : Feng Qian
language : en
Publisher: Springer Nature
Release Date : 2025-04-26
Tensor Computation For Seismic Data Processing written by Feng Qian and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-26 with Science categories.
This book aims to provide a comprehensive understanding of tensor computation and its applications in seismic data analysis, exclusively catering to seasoned researchers, graduate students, and industrial engineers alike. Tensor emerges as a natural representation of multi-dimensional modern seismic data, and tensor computation can help prevent possible harm to the multi-dimensional geological structure of the subsurface that occurred in classical seismic data analysis. It delivers a wealth of theoretical, computational, technical, and experimental details, presenting an engineer's perspective on tensor computation and an extensive investigation of tensor-based seismic data analysis techniques. Embark on a transformative exploration of seismic data processing—unlock the potential of tensor computation and reshape your approach to high-dimensional geological structures. The discussion begins with foundational chapters, providing a solid background in both seismic data processing and tensor computation. The heart of the book lies in its seven chapters on tensor-based seismic data analysis methods. From structured low-tubal-rank tensor completion to cutting-edge techniques like tensor deep learning and tensor convolutional neural networks, each method is meticulously detailed. The superiority of tensor-based data analysis methods over traditional matrix-based data analysis approaches is substantiated through synthetic and real field examples, showcasing their prowess in handling high-dimensional modern seismic data. Notable chapters delve into seismic noise suppression, seismic data interpolation, and seismic data super-resolution using advanced tensor models. The final chapter provides a cohesive summary of the conclusion and future research directions, ensuring readers facilitate a thorough understanding of tensor computation applications in seismic data processing. The appendix includes a hatful of information on existing tensor computation software, enhancing the book's practical utility.
Seismic Data Analysis
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Author : Özdoğan Yilmaz
language : en
Publisher: SEG Books
Release Date : 2001
Seismic Data Analysis written by Özdoğan Yilmaz and has been published by SEG Books this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001 with Science categories.
Expanding the author's original work on processing to include inversion and interpretation, and including developments in all aspects of conventional processing, this two-volume set is a comprehensive and complete coverage of the modern trends in the seismic industry - from time to depth, from 3D to 4D, from 4D to 4C, and from isotropy to anisotropy.
Interpreting Subsurface Seismic Data
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Author : Rebecca Bell
language : en
Publisher: Elsevier
Release Date : 2022-05-27
Interpreting Subsurface Seismic Data written by Rebecca Bell and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-27 with Science categories.
Interpreting Subsurface Seismic Data presents recent advances in methodologies for seismic imaging and interpretation across multiple applications in geophysics including exploration, marine geology, and hazards. It provides foundational information for context, as well as focussing on recent advances and future challenges. It offers detailed methodologies for interpreting the increasingly vast quantity of data extracted from seismic volumes. Organized into three parts covering foundational context, case studies, and future considerations, Interpreting Subsurface Seismic Data offers a holistic view of seismic data interpretation to ensure understanding while also applying cutting-edge technologies. This view makes the book valuable to researchers and students in a variety of geoscience disciplines, including geophysics, hydrocarbon exploration, applied geology, and hazards. - Presents advanced seismic detection workflows utilized cutting-edge technologies - Integrates geophysics and geology for a variety of applications, using detailed examples - Provides an overview of recent advances in methodologies related to seismic imaging and interpretation
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.
Database And Expert Systems Applications
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Author : Christine Strauss
language : en
Publisher: Springer Nature
Release Date : 2022-07-28
Database And Expert Systems Applications written by Christine Strauss and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-07-28 with Computers categories.
This two-volume set, LNCS 13426 and 13427, constitutes the thoroughly refereed proceedings of the 33rd International Conference on Database and Expert Systems Applications, DEXA 2022, held in Vienna in August 2022. The 43 full papers presented together with 20 short papers in these volumes were carefully reviewed and selected from a total of 120 submissions. The papers are organized around the following topics: Big Data Management and Analytics, Consistency, Integrity, Quality of Data, Constraint Modelling and Processing, Database Federation and Integration, Interoperability, Multi-Databases, Data and Information Semantics, Data Integration, Metadata Management, and Interoperability, Data Structures and much more.
Advances And Applications Of Distributed Optical Fiber Sensing Dofs In Multi Scales Geoscience Problems
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Author : Yibo Wang
language : en
Publisher: Frontiers Media SA
Release Date : 2023-02-07
Advances And Applications Of Distributed Optical Fiber Sensing Dofs In Multi Scales Geoscience Problems written by Yibo Wang 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 2023-02-07 with Science categories.
Handbook Of Research On Data Science And Cybersecurity Innovations In Industry 4 0 Technologies
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Author : Murugan, Thangavel
language : en
Publisher: IGI Global
Release Date : 2023-09-21
Handbook Of Research On Data Science And Cybersecurity Innovations In Industry 4 0 Technologies written by Murugan, Thangavel and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-09-21 with Computers categories.
Disruptive innovations are now propelling Industry 4.0 (I4.0) and presenting new opportunities for value generation in all major industry segments. I4.0 technologies' innovations in cybersecurity and data science provide smart apps and services with accurate real-time monitoring and control. Through enhanced access to real-time information, it also aims to increase overall effectiveness, lower costs, and increase the efficiency of people, processes, and technology. The Handbook of Research on Data Science and Cybersecurity Innovations in Industry 4.0 Technologies discusses the technological foundations of cybersecurity and data science within the scope of the I4.0 landscape and details the existing cybersecurity and data science innovations with I4.0 applications, as well as state-of-the-art solutions with regard to both academic research and practical implementations. Covering key topics such as data science, blockchain, and artificial intelligence, this premier reference source is ideal for industry professionals, computer scientists, scholars, researchers, academicians, practitioners, instructors, and students.