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.
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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 |
