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    • Utah FORGE 6-3712: Probabilistic Estimation of Seismic Response Using Physics-Informed Recurrent Neural Networks - 2025 Workshop Presentation

    Metadata Updated: September 22, 2025

    This is a presentation on the Probabilistic Estimation of Seismic Response Using Physics-Informed Recurrent Neural Networks by GTC Analytics, presented by Dr. Jesse Williams. This video slide presentation discusses the development of machine learning-based predictive tools to estimate the magnitude-frequency response of stimulation-induced seismicity. This presentation was featured at the Utah FORGE R&D Annual Workshop on September 9, 2025. The workshop offered a valuable opportunity to review the progress of Research and Development projects funded under Solicitation 2022-2, which aim to improve our understanding of the key factors influencing Enhanced Geothermal System (EGS) reservoir and resource development.

    Access & Use Information

    Public: This dataset is intended for public access and use. License: Creative Commons Attribution

    Downloads & Resources

    Dates

    Metadata Created Date September 22, 2025
    Metadata Updated Date September 22, 2025

    Metadata Source

    Harvested from OpenEI data.json

    Other Data Resources

    Additional Metadata

    Resource Type Dataset
    Metadata Created Date September 22, 2025
    Metadata Updated Date September 22, 2025
    Publisher GTC Analytics
    Maintainer
    Identifier https://data.openei.org/submissions/8529
    Data First Published 2025-09-18T06:00:00Z
    Data Last Modified 2025-09-21T20:28:24Z
    Public Access Level public
    Bureau Code 019:20
    Metadata Context https://openei.org/data.json
    Metadata Catalog ID https://openei.org/data.json
    Schema Version https://project-open-data.cio.gov/v1.1/schema
    Catalog Describedby https://project-open-data.cio.gov/v1.1/schema/catalog.json
    Data Quality True
    Harvest Object Id 59b61569-f0ab-4b9b-97bd-ed047582319c
    Harvest Source Id 7cbf9085-0290-4e9f-bec1-91653baeddfd
    Harvest Source Title OpenEI data.json
    Homepage URL https://gdr.openei.org/submissions/1785
    License https://creativecommons.org/licenses/by/4.0/
    Old Spatial {"type":"Polygon","coordinates":-112.916367,38.483935,-112.879748,38.483935,-112.879748,38.5148,-112.916367,38.5148,-112.916367,38.483935}
    Program Code 019:006
    Projectlead Lauren Boyd
    Projectnumber EE0007080
    Projecttitle Utah FORGE
    Source Datajson Identifier True
    Source Hash 909725066648427bcfa641063abcb2663b8f008455d0df3d75c730587c45201f
    Source Schema Version 1.1
    Spatial {"type":"Polygon","coordinates":-112.916367,38.483935,-112.879748,38.483935,-112.879748,38.5148,-112.916367,38.5148,-112.916367,38.483935}

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