Decision-Making for Earth Resource Development
Quantifying Uncertainty
1st Edition
Will be published approx. on 16. September 2026
Book
Hardback
384 pages
978-1-394-30676-3 (ISBN)
Description
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.
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
Series
Language
English
Place of publication
United States
Publishing group
John Wiley & Sons Inc
Target group
Professional and scholarly
ISBN-13
978-1-394-30676-3 (9781394306763)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
Jef Caers | Céline Scheidt | Lewis Li
Decision-Making for Earth Resource Development
Quantifying Uncertainty
E-Book
06/2026
1st Edition
Wiley
€175.99
Available for download
Persons
Jef Caers, Stanford University, USA.
Celine Scheidt, Stanford University, USA.
Lewis Li, Chevron, USA.
Celine 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, Celine Scheidt, and Lewis Li
2 Decision-Making Under Uncertainty Using Artificial Intelligence 35
Jef Caers, Mansur Arief, Celine Scheidt, and Lewis Li
3 Data Science and Machine Learning for Uncertainty Quantification 83
Jef Caers, Celine Scheidt, and Lewis Li
4 Sensitivity Analysis 147
Jef Caers, Celine Scheidt, and Lewis Li
5 How to Think About Uncertainty: A Popper-Bayes Philosophy 173
Jef Caers, Celine Scheidt, and Lewis Li
6 Geological Priors and Inversion 199
Jef Caers, Celine Scheidt, and Lewis Li
7 A Popper-Bayes Protocol for Uncertainty Quantification in the Context of Decision-Making 265
Jef Caers, Celine 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, Celine Scheidt, and Lewis Li
9 Software Engineering and Implementation 345
Duncan Eddy
Index 359
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, Celine Scheidt, and Lewis Li
2 Decision-Making Under Uncertainty Using Artificial Intelligence 35
Jef Caers, Mansur Arief, Celine Scheidt, and Lewis Li
3 Data Science and Machine Learning for Uncertainty Quantification 83
Jef Caers, Celine Scheidt, and Lewis Li
4 Sensitivity Analysis 147
Jef Caers, Celine Scheidt, and Lewis Li
5 How to Think About Uncertainty: A Popper-Bayes Philosophy 173
Jef Caers, Celine Scheidt, and Lewis Li
6 Geological Priors and Inversion 199
Jef Caers, Celine Scheidt, and Lewis Li
7 A Popper-Bayes Protocol for Uncertainty Quantification in the Context of Decision-Making 265
Jef Caers, Celine 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, Celine Scheidt, and Lewis Li
9 Software Engineering and Implementation 345
Duncan Eddy
Index 359