1887

Abstract

Summary

Seismicity induced by human activities poses a significant threat to public safety, emphasizing the need for accurate and timely hypocenter localization. This study leverages the Fourier Neural Operator (FNO) framework for localization of microseismic events in the Enhanced Geothermal Systems (EGS) setting at the Utah FORGE site. By applying FNO to actual microseismic data from the EGS operational well, the research demonstrates the model’s ability to accurately predict hypocenter locations. We use first arrival traveltimes that were picked for the four selected microseismic events recorded during EGS activities at the Utah FORGE on April 24–28, 2019, including a perforation shot. The velocity model used in this study was approximated using sonic log data from well 58–32. Through this work, we not only establish FNO’s efficacy in source localization under realistic conditions, considering challenges like partial data coverage, but also underscore its potential as a valuable tool for microseismic monitoring. Our method opens a pathway to real-time microseismic monitoring as the trained FNO model can be evaluated instantly to yield the source location. This may enable real-time decision-making to ensure safe and effective development of subsurface operations.

© EAGE Publications BV
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/content/papers/10.3997/2214-4609.2024101189
2024-06-10
2026-03-16

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/content/papers/10.3997/2214-4609.2024101189
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Application of Fourier Neural Operator-Based Microseismic Source Localization at the FORGE Geothermal Underground Laboratory
Conference Proceedings 2024, 1 (2024); https://doi.org/10.3997/2214-4609.2024101189
/content/papers/10.3997/2214-4609.2024101189
/content/papers/10.3997/2214-4609.2024101189
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