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Author: Kalachand Sain
Publisher: John Wiley & Sons
ISBN: 1119482003
Category : Science
Languages : en
Pages : 292
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Book Description
Applying machine learning to the interpretation of seismic data Seismic data gathered on the surface can be used to generate numerous seismic attributes that enable better understanding of subsurface geological structures and stratigraphic features. With an ever-increasing volume of seismic data available, machine learning augments faster data processing and interpretation of complex subsurface geology. Meta-Attributes and Artificial Networking: A New Tool for Seismic Interpretation explores how artificial neural networks can be used for the automatic interpretation of 2D and 3D seismic data. Volume highlights include: Historic evolution of seismic attributes Overview of meta-attributes and how to design them Workflows for the computation of meta-attributes from seismic data Case studies demonstrating the application of meta-attributes Sets of exercises with solutions provided Sample data sets available for hands-on exercises The American Geophysical Union promotes discovery in Earth and space science for the benefit of humanity. Its publications disseminate scientific knowledge and provide resources for researchers, students, and professionals.
Author: Kalachand Sain
Publisher: John Wiley & Sons
ISBN: 1119482003
Category : Science
Languages : en
Pages : 292
Get Book Here
Book Description
Applying machine learning to the interpretation of seismic data Seismic data gathered on the surface can be used to generate numerous seismic attributes that enable better understanding of subsurface geological structures and stratigraphic features. With an ever-increasing volume of seismic data available, machine learning augments faster data processing and interpretation of complex subsurface geology. Meta-Attributes and Artificial Networking: A New Tool for Seismic Interpretation explores how artificial neural networks can be used for the automatic interpretation of 2D and 3D seismic data. Volume highlights include: Historic evolution of seismic attributes Overview of meta-attributes and how to design them Workflows for the computation of meta-attributes from seismic data Case studies demonstrating the application of meta-attributes Sets of exercises with solutions provided Sample data sets available for hands-on exercises The American Geophysical Union promotes discovery in Earth and space science for the benefit of humanity. Its publications disseminate scientific knowledge and provide resources for researchers, students, and professionals.
Author: Mohammadali Ahmadi
Publisher: Elsevier
ISBN: 0443240116
Category : Technology & Engineering
Languages : en
Pages : 517
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Book Description
Artificial Intelligence for a More Sustainable Oil and Gas Industry and the Energy Transition: Case Studies and Code Examples presents a package for academic researchers and industries working on water resources and carbon capture and storage. This book contains fundamental knowledge on artificial intelligence related to oil and gas sustainability and the industry's pivot to support the energy transition and provides practical applications through case studies and coding flowcharts, addressing gaps and questions raised by academic and industrial partners, including energy engineers, geologists, and environmental scientists. This timely publication provides fundamental and extensive information on advanced AI applications geared to support sustainability and the energy transition for the oil and gas industry. - Reviews the use and applications of AI in energy transition of the oil and gas sectors - Provides fundamental knowledge and academic background of artificial intelligence, including practical applications with real-world examples and coding flowcharts - Showcases the successful implementation of AI in the industry (including geothermal energy)
Author: Daniel S. Levine
Publisher: Psychology Press
ISBN: 1134786387
Category : Psychology
Languages : en
Pages : 525
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Book Description
This book is the third in a series based on conferences sponsored by the Metroplex Institute for Neural Dynamics, an interdisciplinary organization of neural network professionals in academia and industry. The topics selected are of broad interest to both those interested in designing machines to perform intelligent functions and those interested in studying how these functions are actually performed by living organisms and generate discussion of basic and controversial issues in the study of mind. The topic of optimality was chosen because it has provoked considerable discussion and controversy in many different academic fields. There are several aspects to the issue of optimality. First, is it true that actual behavior and cognitive functions of living animals, including humans, can be considered as optimal in some sense? Second, what is the utility function for biological organisms, if any, and can it be described mathematically? Rather than organize the chapters on a "biological versus artificial" basis or by what stance they took on optimality, it seemed more natural to organize them either by what level of questions they posed or by what intelligent functions they dealt with. The book begins with some general frameworks for discussing optimality, or the lack of it, in biological or artificial systems. The next set of chapters deals with some general mathematical and computational theories that help to clarify what the notion of optimality might entail in specific classes of networks. The final section deals with optimality in the context of many different high-level issues, including exploring one's environment, understanding mental illness, linguistic communication, and social organization. The diversity of topics covered in this book is designed to stimulate interdisciplinary thinking and speculation about deep problems in intelligent system organization.
Author: Fei Yu
Publisher: Frontiers Media SA
ISBN: 2832545599
Category : Science
Languages : en
Pages : 131
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Book Description
Author: Ana Fred
Publisher: Springer
ISBN: 3642184723
Category : Computers
Languages : en
Pages : 413
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Book Description
This book constitutes the thoroughly refereed post-conference proceedings of the Third International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2010, held in Valencia, Spain, in January 2010. The 30 revised full papers presented together with 1 invited lecture were carefully reviewed and selected from a total of 410 submissions in two rounds of reviewing and improvement. The papers cover a wide range of topics and are organized in four general topical sections on healthinf, biodevices, biosignals, and bioinformatics.
Author: Fred Aminzadeh
Publisher: John Wiley & Sons
ISBN: 1119879876
Category : Science
Languages : en
Pages : 613
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Book Description
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: Sabu M. Thampi
Publisher: Springer Nature
ISBN: 9811543011
Category : Computers
Languages : en
Pages : 276
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Book Description
This book constitutes the refereed proceedings of the First Symposium on Machine Learning and Metaheuristics Algorithms, and Applications, SoMMA 2019, held in Trivandrum, India, in December 2019. The 17 full papers and 6 short papers presented in this volume were thoroughly reviewed and selected from 53 qualified submissions. The papers cover such topics as machine learning, artificial intelligence, Internet of Things, modeling and simulation, disctibuted computing methodologies, computer graphics, etc.
Author: Amalendu Sinha
Publisher: Springer Nature
ISBN: 3031469666
Category : Science
Languages : en
Pages : 492
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Book Description
Rising concern about climate change and strong societal expectations with increasing complexities of mineral deposits being mined, call for more innovative exploration and exploitation technologies with higher productivity and recovery including eco-friendly strategies and policies in place for long term sustainability of the mineral Industry. It is now ardently necessary to identify and define the best mining practices addressing societal needs. In view of these, The Mining, Geological and Metallurgical Institute of India (MGMI), established way back on 16th January 1906, and one of the oldest institutions of this kind in the world, is organizing the 10th Asian Mining Congress (AMC) during November 06-09, 2023 in Kolkata, India with the Theme, “Roadmap for Best Mining Practices vis-à-vis Global Transformation”. The AMC and International Mining Exhibition (IME), held concurrently, are flagship international events organized by MGMI biennially since its centenary year. This series have provided ample opportunities to all stakeholders including practicing engineers, machinery manufacturers, planners, regulators, academicians, scientists and policy makers, for sharing their knowledge, experience and expertise and exhibit their products that can benefit the mining and mineral industries not only in the Asian region but also globally. This proceeding of 10th AMC contains the articles written by eminent persons and stalwarts in their respective domains. It is a collection of contemporary articles narrating recent advancements in mining sector.
Author: Vera Kůrková
Publisher: Springer Science & Business Media
ISBN: 3540875352
Category : Computers
Languages : en
Pages : 1053
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Book Description
This two volume set LNCS 5163 and LNCS 5164 constitutes the refereed proceedings of the 18th International Conference on Artificial Neural Networks, ICANN 2008, held in Prague Czech Republic, in September 2008. The 200 revised full papers presented were carefully reviewed and selected from more than 300 submissions. The first volume contains papers on mathematical theory of neurocomputing, learning algorithms, kernel methods, statistical learning and ensemble techniques, support vector machines, reinforcement learning, evolutionary computing, hybrid systems, self-organization, control and robotics, signal and time series processing and image processing.
Author: Joaquim Marques de Sá
Publisher: Springer
ISBN: 3540746900
Category : Computers
Languages : en
Pages : 999
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Book Description
This book is the first of a two-volume set that constitutes the refereed proceedings of the 17th International Conference on Artificial Neural Networks, ICANN 2007, held in Porto, Portugal, September 2007. Coverage includes advances in neural network learning methods, advances in neural network architectures, neural dynamics and complex systems, data analysis, evolutionary computing, agents learning, as well as temporal synchronization and nonlinear dynamics in neural networks.
