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Utah FORGE: Focal Mechanism Catalog from Stage 3 of the April 2022 Stimulation Test
This submission includes focal-mechanism solutions derived from the Utah FORGE April 2022 Stage-3 stimulation. Waveforms were extracted around each event (short windows bracketing origin times) from the downhole three-component arrays in wells 58-32, 78-32, and 56-32 and the surface station UU.FORK; an initial Stage-3 catalog of several thousand located events was narrowed to ~1,200 preselected events and processed to produce a final high-quality set of 717 focal mechanisms.
Methods combined automated phase picking with a noise-resistant deep-learning polarity classifier, simple amplitude-ratio measurements around arrivals, and Bayesian moment-tensor inversion using MTfit. Polarities and amplitude ratios were weighted by per-measurement confidence, posterior ensembles were sampled to quantify uncertainty, and solutions with low angular uncertainty (Kagan angle < 20 degrees) form the distributed high-quality catalog.
Complete Metadata
| @type | dcat:Dataset |
|---|---|
| accessLevel | public |
| bureauCode |
[
"019:20"
]
|
| contactPoint |
{
"fn": "Ahmad Mohammadi",
"@type": "vcard:Contact",
"hasEmail": "mailto:ahmadmohamadi.gh@gmail.com"
}
|
| dataQuality |
true
|
| description | This submission includes focal-mechanism solutions derived from the Utah FORGE April 2022 Stage-3 stimulation. Waveforms were extracted around each event (short windows bracketing origin times) from the downhole three-component arrays in wells 58-32, 78-32, and 56-32 and the surface station UU.FORK; an initial Stage-3 catalog of several thousand located events was narrowed to ~1,200 preselected events and processed to produce a final high-quality set of 717 focal mechanisms. Methods combined automated phase picking with a noise-resistant deep-learning polarity classifier, simple amplitude-ratio measurements around arrivals, and Bayesian moment-tensor inversion using MTfit. Polarities and amplitude ratios were weighted by per-measurement confidence, posterior ensembles were sampled to quantify uncertainty, and solutions with low angular uncertainty (Kagan angle < 20 degrees) form the distributed high-quality catalog. |
| distribution |
[
{
"@type": "dcat:Distribution",
"title": "Focal Mechanisms.csv",
"format": "csv",
"accessURL": "https://gdr.openei.org/files/1773/focals.csv",
"mediaType": "text/csv",
"description": "This catalogs the focal-mechanism solutions for events recorded during Stage 3 of the April 2022 stimulation at Utah FORGE. Data includes event magnitude, location, strike, dip, rake, and average Kagan angle."
}
]
|
| identifier | https://data.openei.org/submissions/8518 |
| issued | 2025-09-15T06:00:00Z |
| keyword |
[
"Bayesian inversion",
"EGS",
"FORGE",
"Kagan angle",
"MTfit",
"Milford",
"Utah",
"Utah FORGE",
"amplitude ratios",
"deep-learning",
"dip",
"energy",
"event catalog",
"focal-mechanisms",
"geophysical inversion",
"geophysics",
"geothermal",
"hydraulic stimulation",
"magnitude",
"moment-tensor inversion",
"stage 3",
"strike"
]
|
| landingPage | https://gdr.openei.org/submissions/1773 |
| license | https://creativecommons.org/licenses/by/4.0/ |
| modified | 2025-09-16T14:27:32Z |
| programCode |
[
"019:006"
]
|
| projectLead | Lauren Boyd |
| projectNumber | EE0007080 |
| projectTitle | Utah FORGE |
| publisher |
{
"name": "Texas A and M University",
"@type": "org:Organization"
}
|
| spatial |
"{"type":"Polygon","coordinates":[[[-112.916367,38.483935],[-112.879748,38.483935],[-112.879748,38.5148],[-112.916367,38.5148],[-112.916367,38.483935]]]}"
|
| title | Utah FORGE: Focal Mechanism Catalog from Stage 3 of the April 2022 Stimulation Test |
