
Characterizing Low-Yield Mining Blasts with Distributed Acoustic Sensing (DAS)
Distributed Acoustic Sensing (DAS) has shown to be a reliable method in the detection of various seismic sources from megathrust earthquakes to small-magnitude explosive sources. Lior et al. (2023) showed, DAS can potentially be used for real-time magnitude estimation and ground motion prediction. Here we report the DAS recordings of mining blast events from the Six Mile and Shawville mines approximately 25 kilometers northwest of Philipsburg, Pennsylvania, and 50 kilometers northwest of the FORESEE DAS array using telecommunication fiber-optic cables beneath the Pennsylvania State University campus in the city of State College, Pennsylvania. Our DAS array detected 126 of 269 recorded blasts, 96 of which lay outside our monitoring period between 2019-2021, for a 72% detection rate and observed 99 more events than The Pennsylvania State Seismic Network (PASEIS). Observed explosive tonnage of blasts range from 6,156 to 57,780lbs (lowest to highest yield source observed) at 19 and 70-foot hole depths respectively. Using pre-detected events, we use template matching to search for hidden blast events. Our final goal is to assign magnitude estimates to the observed blasts by using the methods described in Yin et al. (2023). If this approach proves to estimate earthquake magnitude of low-yield explosive sources reliably and rapidly, we propose incorporating this method into geohazard early warning on the seismically vulnerable east coast of the United States.
Files
Metadata
Work Title | Characterizing Low-Yield Mining Blasts with Distributed Acoustic Sensing (DAS) |
---|---|
Access | |
Creators |
|
Keyword |
|
License | In Copyright (Rights Reserved) |
Work Type | Research Paper |
Acknowledgments |
|
Publication Date | December 16, 2023 |
Subject |
|
Language |
|
Geographic Area |
|
Deposited | January 19, 2024 |
Versions
Analytics
Collections
This resource is currently not in any collection.