DOI · DOI-0039 · record R2709

Geothermal Energy Assessments

Department of the Interior · USGS

Overview

Development stage: In development or acquisitionSource: a) Pre-deployment – The use case is in a development or acquisition status.
High-impact designation: Not high-impactSource: c) Not high-impact
Impact justification: Not reported
Start date: Not reported
Withheld from public reporting: NoSource: a) No

Mission

Topic area: Energy and the Environment
Operational functions: No function tag matched Derived by keyword rules; see methodology

Problem the AI is intended to solve

Executive Order 14156 – Declaring a National Energy Emergency, directs federal agencies to identify and develop our Nations energy resources.

Expected benefits

New methodology developed by the USGS leverages AI and advanced machine learning (ML) techniques to accelerate how we assess geothermal energy potential and brings new speed and precision to our science to unleash American energy.

System outputs

The USGS is developing data-driven machine learning strategies (a form of artificial intelligence) to produce new maps of hydrothermal resource favorability for the Great Basin in the western US as part of our geothermal resource estimation efforts and to map geologic features and transitions using EarthMRI datasets in support of energy and minerals resource assessments.

Technology

AI classification: Classical / predictive MLSource: Classical/Predictive Machine Learning: Models trained on data to make predictions or classifications based on identified patterns or relatio…
System name(s): Not reported
Custom-developed code: No
Public source code: Not reported

Sourcing

How it was built: Not reported
Vendor (as reported): Not reported
Vendors (standardized): None on the standard list

A vendor is the supplier named by the agency. It does not identify the underlying model or AI technology.

Data and privacy

Involves PII: No
Privacy Impact Assessment: Not reported
Authorization to Operate: No
Demographic features: Not reported
Training and evaluation data: Not reported
Federal Data Catalog: Not reported

Governance

0 of 8 minimum-practice questions answered. A blank answer means the agency reported nothing; it does not mean the practice is absent.

Pre-deployment testingNo answer reported

AI impact assessmentNo answer reported

Independent reviewNo answer reported

Ongoing monitoringNo answer reported

Operator trainingNo answer reported

Fail-safeNo answer reported

Appeal processNo answer reported

User and public consultationNo answer reported

Potential impacts and how they were identified

Not reported