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: https://eos.org/editors-vox/quantifying-uncertainty-about-earths-resources