Multiscale Hydrogeologic-Biogeochemical Process Monitoring and Prediction Framework

In the 21st century society will need to address and resolve a large number of subsurface challenges related to energy and environmental issues. These challenges include contaminant cleanup and long term site management at contaminated sites, long term storage of nuclear fuel, carbon cycling and sequestration, production of unconventional resources (oil shales and tight gas) and water resource management. All of these require a fundamental understanding of coupled physical, chemical and biological processes as well as the ability to predict such processes. A predictive assimilation framework (PAF) for subsurface sites will be developed and validated which can provide actionable information to stakeholders. This framework will be constructed such that it is broadly applicable to a range of different sites and problems, and can be rapidly set up, configured and deployed. The open source framework will use open source codes developed by DOE, NSF, USGS as well as academic institutions. It will couple observational data, data storage and information access tools, inversion and prediction methods, numerical forward models and petrophysical models. The framework will be enabled through the use of standardized software interfaces and workflows. Commercial Applications and Other Benefits: The framework will provide a predictive understanding of the behavior of diverse subsurface sites. The framework will be directly applicable on federally owned contaminated sites, but also on vulnerable aquifers, sites used for CO2 sequestration and sites used for unconventional energy production. By leveraging codes developed by US national laboratories and academia PAF will provide taxpayers a return on investment in these codes, as well as create numerous commercial opportunities around implementing, supporting and enhancing the framework.