Quantifying Uncertainty in Subsurface Systems (Geophysical Monograph Series, Band 236) - Hardcover

Hardcover

ISBN 10: 1119325838 ISBN 13: 9781119325833

Verlag: American Geophysical Union, 2018

Inhaltsangabe

Under the Earth's surface is a rich array of geological resources, many with potential use to humankind. However, extracting and harnessing them comes with enormous uncertainties, high costs, and considerable risks. The valuation of subsurface resources involves assessing discordant factors to produce a decision model that is functional and sustainable. This volume provides real-world examples relating to oilfields, geothermal systems, contaminated sites, and aquifer recharge.

Volume highlights include:

• A multi-disciplinary treatment of uncertainty quantification
• Case studies with actual data that will appeal to methodology developers
• A Bayesian evidential learning framework that reduces computation and modeling time

Quantifying Uncertainty in Subsurface Systems is a multidisciplinary volume that brings together five major fields: information science, decision science, geosciences, data science and computer science. It will appeal to both students and practitioners, and be a valuable resource for geoscientists, engineers and applied mathematicians.

Read the Editors' Vox: eos.org/editors-vox/quantifying-uncertainty-about-earths-resources

Über diesen Titel

Über die Autorin bzw. den Autor

Céline Scheidt is senior research engineer at Stanford University with 10 years of experience in this field. She is known for her work on uncertainty quantification using machine learning methods and has published several impactful papers in that area. She will be the keynote speaker of the next international Geostatistics congress.

Lewis Li is 3rd year PhD student at Stanford University. He has published three papers, with three more in the pipeline. With an Electrical Engineering degree from Stanford University, he has considerable expertise in software engineering and in addressing computational challenges.

Jef Caers is a world-leading expert in quantifying uncertainty in the subsurface, has closely worked on 100+ projects with a variety of industries in this area and has been leading the Stanford Center for Reservoir Forecasting for 15 years, he has been Professor at Stanford University for 19 years.

Von der hinteren Coverseite

Quantifying Uncertainty in Subsurface Systems

Under the Earth's surface is a rich array of geological resources, many with potential use to humankind. However, extracting and harnessing them comes with enormous uncertainties, high costs, and considerable risks. The valuation of subsurface resources involves assessing discordant factors to produce a decision model that is functional and sustainable. Quantifying Uncertainty in Subsurface Systems provides real-world examples relating to oilfields, geothermal systems, contaminated sites, and aquifer recharge.

Volume highlights include:

• A multidisciplinary treatment of uncertainty quantification
• Case studies with actual data that will appeal to methodology developers
• A Bayesian evidential learning framework that reduces computation and modeling time

Quantifying Uncertainty in Subsurface Systems is a multidisciplinary volume that brings together five major fields: information science, decision science, geosciences, data science, and computer science. It will appeal to both students and practitioners, and be a valuable resource for geoscientists, engineers, and applied mathematicians.

Aus dem Klappentext

Quantifying Uncertainty in Subsurface Systems

Under the Earth's surface is a rich array of geological resources, many with potential use to humankind. However, extracting and harnessing them comes with enormous uncertainties, high costs, and considerable risks. The valuation of subsurface resources involves assessing discordant factors to produce a decision model that is functional and sustainable. Quantifying Uncertainty in Subsurface Systems provides real-world examples relating to oilfields, geothermal systems, contaminated sites, and aquifer recharge.

Volume highlights include:

• A multidisciplinary treatment of uncertainty quantification
• Case studies with actual data that will appeal to methodology developers
• A Bayesian evidential learning framework that reduces computation and modeling time

Quantifying Uncertainty in Subsurface Systems is a multidisciplinary volume that brings together five major fields: information science, decision science, geosciences, data science, and computer science. It will appeal to both students and practitioners, and be a valuable resource for geoscientists, engineers, and applied mathematicians.

Details zur Ausgabe

• Verlag: American Geophysical Union
• Erscheinungsdatum: 2018
• Sprache: Englisch
• ISBN 10: 1119325838
• ISBN 13: 9781119325833
• Einband: Gebundene Ausgabe
• Auflage: 1
• Anzahl der Seiten: 304
• Herausgeber: Scheidt Céline, Li Lewis, Caers Jef
• Kontakt zum Hersteller: Wiley-VCH GmbH; product_safety@wiley.com; ; Boschstrasse 12; Weinheim; 69469; Deutschland