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    • Utah FORGE 2-2439v2: Report on Predicting Far-Field Stresses Using Finite Element Modeling and Near-Wellbore Machine Learning for Well 16A(78)-32

    Metadata Updated: January 20, 2025

    This report presents the far-field stress predictions at two locations along the vertical section of Utah FORGE Well 16A (78)-32 using a physics-based thermo-poro-mechanical model. Three principal stresses in far-field were obtained by solving an inverse problem based on the near-wellbore stress estimates generated by the Machine Learning (ML) predictive model presented in a previous report, which is linked below as "Machine Learning for Well 16A(78)-32 Stress Predictions". Combined ML and physics-based Finite Element model was applied to translate the near-field stresses to stresses away from the wellbore/cooling-influenced zone. The thermo-poro-mechanical effect by pre-cooling circulation prior to well logging in an enhanced geothermal system (EGS) well was accounted for in the stress predictions at Well 16A (78)-32.

    Access & Use Information

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

    Downloads & Resources

    Dates

    Metadata Created Date January 11, 2025
    Metadata Updated Date January 20, 2025

    Metadata Source

    Harvested from OpenEI data.json

    Other Data Resources

    Additional Metadata

    Resource Type Dataset
    Metadata Created Date January 11, 2025
    Metadata Updated Date January 20, 2025
    Publisher University of Pittsburgh
    Maintainer
    Identifier https://data.openei.org/submissions/7711
    Data First Published 2024-08-30T06:00:00Z
    Data Last Modified 2024-09-05T15:37:53Z
    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
    Datagov Dedupe Retained 20250120155001
    Harvest Object Id d0310b40-2bc3-4714-a611-ebec8bc42ec8
    Harvest Source Id 7cbf9085-0290-4e9f-bec1-91653baeddfd
    Harvest Source Title OpenEI data.json
    Homepage URL https://gdr.openei.org/submissions/1641
    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 bde0dc2963405ef85443e05b6518dfea292d7905656eb4f81b3baa15bfcc14e2
    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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