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Record W3088011406 · doi:10.1785/0120200074

Static Ground Displacement for an Induced Earthquake Recorded on Broadband Seismometers

2020· article· en· W3088011406 on OpenAlexaffabout
Megan Zecevic, Thomas S. Eyre, David W. Eaton

Bibliographic record

VenueBulletin of the Seismological Society of America · 2020
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicSeismic Waves and Analysis
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsSeismometerGeologySeismologyBroadbandDeformation (meteorology)Geodetic datumGeodesyDisplacement (psychology)CodaSeismogramPassive seismicEngineeringTelecommunications

Abstract

fetched live from OpenAlex

ABSTRACT Using geodetic methods, significant static ground deformation has been observed for many large natural earthquakes. Some of the largest earthquakes induced by hydraulic-fracturing operations have been observed in the Western Canada Sedimentary Basin; however, because of the size and depths of these events, the associated static ground deformations have not yet been observed using traditional geodetic techniques. A seismic processing technique, developed for small volcano-seismic events, has the potential to resolve micrometer-scale static displacements using broadband seismic data. In this study, we test this processing method using vertical component broadband recordings of an Mw 4.1 event acquired at four nearby broadband seismometers. Estimated static displacements at the four stations are compared with the theoretical surface displacement field for a dislocation on a finite rectangular source within a homogeneous, elastic half-space. The theoretical displacements have the same polarities as the measured displacements across the seismic network and have similar amplitudes for three of the four stations. However, one station yielded unstable results, which shows that care must be taken when using this method. These results suggest that this processing method has potential for obtaining surface deformation for small to moderate-sized earthquakes using broadband data.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.369
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.044
GPT teacher head0.242
Teacher spread0.198 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2020
Admission routes2
Has abstractyes

Explore more

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