Opportunity ID: 304786

General Information

Document Type: Grants Notice
Funding Opportunity Number: DE-FOA-0001920
Funding Opportunity Title: Request for Information (RFI)- Machine Learning for Geothermal Energy and the Geosciences
Opportunity Category: Discretionary
Opportunity Category Explanation:
Funding Instrument Type: Other
Category of Funding Activity: Energy
Category Explanation:
Expected Number of Awards: 1
Assistance Listings: 81.087 — Renewable Energy Research and Development
Cost Sharing or Matching Requirement: No
Version: Synopsis 1
Posted Date: May 07, 2018
Last Updated Date:
Original Closing Date for Applications: Jun 06, 2018 All responses to this RFI must be provided as an attachment (in
Microsoft Word format) to an e-mail message addressed to
machinelearninggeo@ee.doe.gov.
Current Closing Date for Applications: Jun 06, 2018 All responses to this RFI must be provided as an attachment (in
Microsoft Word format) to an e-mail message addressed to
machinelearninggeo@ee.doe.gov.
Archive Date: Aug 07, 2018
Estimated Total Program Funding: $1
Award Ceiling: $2
Award Floor: $1

Eligibility

Eligible Applicants: Unrestricted (i.e., open to any type of entity above), subject to any clarification in text field entitled “Additional Information on Eligibility”
Additional Information on Eligibility:

Additional Information

Agency Name: Golden Field Office
Description: Department of Energy’s (DOE) Office of Energy Efficiency and
Renewable Energy (EERE), invites input from the public
regarding opportunities associated with applying machine
learning techniques toward challenges in the geosciences that are relevant to geothermal energy. With the overall goals of establishing the practice of machine learning (ML) in the geothermal industry and maximizing the value of the rich datasets utilized in the geosciences, GTO is seeking input in three areas: Identifying the most promising
applications of machine learning in subsurface R&D, building open community datasets capable of supporting the most advanced ML techniques, and leveraging crowd-sourced R&D through alternative funding mechanisms. As ML is already well- established in some industries, GTO is also very interested in feedback from outside of the geothermal community. The information requested is intended to advance GTO goals in geothermal development, though there are likely crosscutting applications with other industries operating in the subsurface. Opportunities for partnerships with other industries are also of interest. The purpose of this Request for Information (RFI) is to gather feedback from stakeholders prior to DOE potentially issuing a Funding Opportunity Announcement (FOA).

This RFI is not a FOA: therefore, DOE is not accepting
applications at this time. All responses to this RFI must be provided as an attachment (in Microsoft Word format) to an e-mail message addressed to machinelearninggeo@ee.doe.gov. Responses must be received no later than 5:00 PM EDT on June 6, 2018. The full content of the announcement can be found on the EERE Exchange website at https://eere-exchange.energy.gov.

Link to Additional Information: https://eere-exchange.energy.gov
Grantor Contact Information: If you have difficulty accessing the full announcement electronically, please contact:

Michael J. Weathers
machinelearninggeo@ee.doe.gov

Email:machinelearninggeo@ee.doe.gov

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