RFI:Technology Advancements for Subsurface Exploration for Renewable Energy Resources or Carbon Storage
RFI: Technology Advancements for Subsurface Exploration for Renewable Energy Resources or Carbon Storage This is a Request for Information (RFI) only. This RFI is not soliciting application for financial assistance. The purpose of this RFI is solely to solicit input for ARPA-E consideration to inform the possible formulation of future programs. The purpose of this RFI is to solicit input for a potential future ARPA-E research program focused on technologies that enable high-resolution, wide-area subsurface mapping in order to identify opportunities for renewable energy technologies and the future low-carbon economy. Examples where advances in subsurface imaging will be critical include, but are not limited to, locating reservoirs for carbon capture and storage (CCS), identifying new geothermal sites, mapping natural accumulations of energy-relevant minerals, and assessing potential resources of geologic hydrogen. The goal is to better understand how subsurface imaging technologies today may need to expand, adapt, or improve beyond technologies which have been optimized for oil and gas exploration. ARPA-E is seeking information at this time regarding the state of the art in subsurface imaging technologies and transformative and implementable technologies that could: 1. Reduce frontier exploration costs for renewable energy or carbon storage projects by an order of magnitude or more, leveraging advancements in subsurface imaging, data collection, and data processing. For new renewable technologies or CCS projects, identifying potential geologic sites with the requisite properties requires honing in on sites from a much larger region, often in areas that have not been traditionally explored by oil and gas interests and where there is little prior high-quality imaging data. Isolating regions of interest could mean developing new, cost-effective wide-area subsurface exploration technologies, using a combination of imaging techniques paired with multi-physics models, using data processing or novel geostatistical methods to upgrade or augment existing datasets, and/or developing machine learning algorithms which can fill in data gaps. 2. Advance data processing to accommodate larger amounts of data and reduce processing time by orders of magnitude for wide-area and/or nationwide subsurface imaging surveys. 3. Dramatically improve project success rates. Successful technologies would result in outcomes such as reduced incidence of dry wells in geothermal energy projects or identification of new energy-relevant mineral deposits. These outcomes can be facilitated by acquiring higher-quality and/or more comprehensive data in order to discern sites with high probability factors. 4. Monitor dynamic changes in the subsurface over time (4D mapping) with more sensitive surveys techniques, more comprehensive models, and/or algorithms. ARPA-E expects that subsurface changes of interest to renewable energy or CCS projects (e.g. changes in rock morphology, active water-rock chemical reactions, fluid migration, fracture network development, biological processes) may be different than those typically modelled for the oil and gas industry and that current models may need to be expanded to include these processes. 5. Reveal opportunities for interdisciplinary collaboration, combining the expertise of groups that traditionally do not interact, in order to gain a more comprehensive understanding of dynamic geologic processes. To view the RFI in its entirety, please visit https://arpa-e-foa.energy.gov. The information you provide may be used by ARPA-E in support of program planning. THIS IS A REQUEST FOR INFORMATION ONLY. THIS NOTICE DOES NOT CONSTITUTE A FUNDING OPPORTUNITY ANNOUNCEMENT (FOA). NO FOA EXISTS AT THIS TIME.