
Decision-Making for Earth Resource Development
Description
Alles über E-Books | Antworten auf Fragen rund um E-Books, Kopierschutz und Dateiformate finden Sie in unserem Info- & Hilfebereich.
Earth's subsurface offers many vital resources-such as minerals, geothermal energy, and clean water-but decisions regarding exploration and extraction must balance resource value against environmental impact. This can only be addressed by accepting uncertainty as an integral part of most decisions.
Decision-Making for Earth Resource Development presents uncertainty quantification strategies tested on real cases using a Bayesian methodology that can be applied to a wide variety of decision problems.
Volume highlights include:
- Six substantial case studies, covering mineral exploration, geothermal heat feasibility, groundwater management, and more
- Popper-Bayes protocol for formulating and solving uncertainty quantification problems
- Machine learning approaches for Bayesian inversion
- Decision-making with AI and high-performance computing
- Investigation models using global sensitivity analysis in the geosciences
- Software development for large-scale practical implementation
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.
More details
Other editions
Additional editions

Persons
Jef Caers, Stanford University, USA.
Céline Scheidt, Stanford University, USA.
Lewis Li, Chevron, USA.
Content
List of Contributors vii
Preface ix
Acknowledgments xi
1 Real-World Decision-Making Cases 1
Jef Caers, John Mern, Jihoon Park, Troels Vilhelmsen, Torsten Clemens, Markus Zechner, Anthony Corso, Maria-Magdalena Chiotoroiu, LukaTas, Thomas Hermans, Luk Peeters, Cameron Huddlestone-Holmes, Kate Holland, Rebecca Doble, Céline Scheidt, and Lewis Li
2 Decision-Making Under Uncertainty Using Artificial Intelligence 35
Jef Caers, Mansur Arief, Céline Scheidt, and Lewis Li
3 Data Science and Machine Learning for Uncertainty Quantification 83
Jef Caers, Céline Scheidt, and Lewis Li
4 Sensitivity Analysis 147
Jef Caers, Céline Scheidt, and Lewis Li
5 How to Think About Uncertainty: A Popper-Bayes Philosophy 173
Jef Caers, Céline Scheidt, and Lewis Li
6 Geological Priors and Inversion 199
Jef Caers, Céline Scheidt, and Lewis Li
7 A Popper-Bayes Protocol for Uncertainty Quantification in the Context of Decision-Making 265
Jef Caers, Céline Scheidt, and Lewis Li
8 Decision-Making in Developing Earth Resources 287
Jef Caers, John Mern, Jihoon Park, Troels Vilhelmsen, Torsten Clemens, Markus Zechner, Anthony Corso, Maria-Magdalena Chiotoroiu, Luka Tas, Thomas Hermans, Luk Peeters, Cameron Huddlestone-Holmes, Kate Holland, Rebecca Doble, Céline Scheidt, and Lewis Li
9 Software Engineering and Implementation 345
Duncan Eddy
Index 359
System requirements
File format: PDF
Copy-Protection: Adobe-DRM (Digital Rights Management)
System requirements:
- Computer (Windows; MacOS X; Linux): Install the free reader Adobe Digital Editions prior to download (see eBook Help).
- Tablet/smartphone (Android; iOS): Install the free app Adobe Digital Editions or the app PocketBook before downloading (see eBook Help).
- E-reader: Bookeen, Kobo, Pocketbook, Sony, Tolino and many more (only limited: Kindle).
The file format PDF always displays a book page identically on any hardware. This makes PDF suitable for complex layouts such as those used in textbooks and reference books (images, tables, columns, footnotes). Unfortunately, on the small screens of e-readers or smartphones, PDFs are rather annoying, requiring too much scrolling.
This eBook uses Adobe-DRM, a „hard” copy protection. If the necessary requirements are not met, unfortunately you will not be able to open the eBook. You will therefore need to prepare your reading hardware before downloading.
Please note: We strongly recommend that you authorise using your personal Adobe ID after installation of any reading software.
For more information, see our eBook Help page.