Subsurface porous media systems host an abundance of multiphysical, multiscale processes involving reactive transport, multiphase flows, thermo-hydro-mechanical-chemical (THMC) couplings, and biogeochemical reactions. While coupled processes are often better understood at fine scales, predictive models at coarser scales---from laboratory to reservoir scales---are needed for engineering applications involving porous media systems. However, developing models that reliably predict multiphysical behaviors across spatiotemporal scales remains challenging, as the relevant range of scales can span many orders of magnitude. This session invites recent contributions on physics- and data-based approaches related to multiscale modeling and uncertainty quantification for subsurface porous media systems. This includes---but is not limited to---analytical, numerical, symbolic-computational, and data-driven approaches to upscaling, reduced-order modeling, and scientific machine learning for better prediction of system behaviors in carbon dioxide sequestration, methane and hydrogen storage, environmental remediation, and geothermal applications. Approaches connecting continuum descriptions with atomistic and quantum simulations are also encouraged.

• B - Biogeosciences
• EP - Earth and Planetary Surface Processes
• MR - Mineral and Rock Physics
• NG - Nonlinear Geophysics