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DOE OSTI · 2441446

Utah FORGE 6-3712: Probabilistic Estimation of Seismic Response Using Physics-Informed Recurrent Neural Networks - 2024 Annual Workshop Presentation

Williams, Jesse
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Abstract

This is a presentation on the Probabilistic Estimation of Seismic Response Using Physics-Informed Recurrent Neural Networks by GTC Analytics, presented by 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 in the Utah FORGE R&D Annual Workshop on August 15, 2024.

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15 GEOTHERMAL ENERGYdeep learningDLEGSenergygeothermalmachine learningmagnitude-frequency distributionmulti frequencypredictive systemspresentationseismicseismicityseismicity predictorstimulationstimulation-induced seismicityUtah FORGEvideo

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Williams, Jesse. 2024-09-17. Utah FORGE 6-3712: Probabilistic Estimation of Seismic Response Using Physics-Informed Recurrent Neural Networks - 2024 Annual Workshop Presentation. https://doi.org/10.15121/2441446

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