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The integration of subsurface systems involves weighing the enormous uncertainties of harnessing the Earth's geological resources with high costs and considerable risks. Such valuation involves assessing discordant factors to produce a decision model that is functional and sustainable. Quantifying Uncertainty in Subsurface Systems will provide a multi-disciplinary treatment of uncertainty quantification towards practical engineering applications and decision making. Volume highlights include: Five substantial case studies on decision making under uncertainty for subsurface systems Forecasting total volume and future revenue stream in giant oilfields Designing heat pumps for heating buildings in shallow geothermal systems Optimizing data acquisition for uranium contaminated sites Managing aquifer recharge in the groundwater system Characterizing the risk of misclassification of mining blocks in function of drill-hole quality and spacing Quantifying Uncertainty in Subsurface Systems is a multidisciplinary volume that brings together five major fields of science to tackle real-world problems covering information science, decision science, geosciences, data science and computer science. The volume presents actual field cases with actual data that will appeal to methodology developers e.g. doctoral students, as well as practitioners e.g. industry professionals, and will also be a valuable resource for geoscientists, engineers and applied mathematicians.
