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Subsurface Data Assimilation◆日本地質学会 第133年学術大会 特別価格！：2026年10月23日(金)ご注文分まで
※上記表示の販売価格は割引適用後の価格です 未刊 ご予約承ります。 Title: Subsurface Data Assimilation Subtitle: Theory and Applications Author: Luo, Xiaodong (Norwegian Research Centre (NORCE), Norway) / Leeuwenburgh, Olwijn (Netherlands Organisation for Applied Scientific Research (TNO), The Netherlands) / Emerick, Alexandre Anoze (Senior Advisor, Petrobras Research Center, Rio de Janeiro, Brazi Publisher: Elsevier USA ISBN: 9780443415432 Cover: PAPERBACK Date: 2026年10月 DESCRIPTION Subsurface Data Assimilation: Theory and Applications provides a comprehensive exploration of data assimilation algorithms applied to subsurface characterization and monitoring. The book begins with data assimilation methods, including multilevel data assimilation, coupled data assimilation with machine learning, and generative neural networks for geological parameterization. It also introduces Latent-Space Data Assimilation (LSDA), leveraging deep learning for feature-based analysis and forecasting, and geostatistical seismic inversion techniques. The second part of the book looks into the practical applications of data assimilation in various subsurface problems. Chapters explore CO2 monitoring, geologic CO2 sequestration, and the use of data assimilation for earthquake or CO2 storage scenarios. Hierarchical data assimilation procedures for carbon storage with uncertain geological scenarios are discussed, along with applications of data assimilation in geothermal energy contexts. The book also addresses practical uncertainty management practices and challenges related to CO2 storage and geothermal energy projects. TABLE OF CONTENTS Part I: Theoretical Foundations of Data Assimilation Algorithms 1. Recent Progresses of Data Assimilation Methods Applied to Subsurface Characterization and Monitoring Problems 2. Multilevel Data Assimilation 3. Coupled Data Assimilation and Machine Learning 4. Generative Neural Networks for Geological Parameterization 5. Latent-Space Data Assimilation (LSDA): Leveraging Deep Learning for Feature-Based Analysis and Forecasting 6. Geostatistical Seismic Inversion Part II: Applications to Various Subsurface Problems 7. CO2 Monitoring 8. Geologic CO2 Sequestration 9. Earthquake or CO2 Storage 10. Hierarchical Data Assimilation Procedures for Carbon Storage with Uncertain Geological Scenario 11. Geothermal Energy 12. Practical Uncertainty Management, Practices, and Challenges in CO2 Storage/Geothermal Energy 最近チェックした商品
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