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Record W2518496520 · doi:10.1002/2016gl070421

Poroelastic stress triggering of the December 2013 Crooked Lake, Alberta, induced seismicity sequence

2016· article· en· W2518496520 on OpenAlexaffabout
Kai Deng, Yajing Liu, R. M. Harrington

Bibliographic record

VenueGeophysical Research Letters · 2016
Typearticle
Languageen
FieldEarth and Planetary Sciences
Topicearthquake and tectonic studies
Canadian institutionsMcGill University
Fundersnot available
KeywordsInduced seismicityPoromechanicsGeologyPore water pressureHydraulic fracturingCoulombSeismologyStress (linguistics)Sequence (biology)Geotechnical engineeringPhysicsPorous medium

Abstract

fetched live from OpenAlex

Abstract The Crooked Lake area in Central Alberta, Canada, became seismically active in December 2013 with a sequence of earthquakes M w 2.0 and higher. The earthquakes are suspected to be induced by hydraulic fracturing in nearby horizontal wells due to their strong spatiotemporal correlation. To investigate the physical mechanism of the induced seismicity near Crooked Lake, we calculate stress and pore pressure perturbations resulting from high‐rate multistage fluid injection in the framework of linear poroelasticity. The calculated perturbations are used for seismic risk analysis based on the Coulomb failure criterion. Results show that most seismicity is within a positive Coulomb stress change regime, indicating that failure is promoted by injection of fluid. By comparing Coulomb stress results for different parameter settings, we show that elastic response of the solid matrix, instead of fluid diffusion, is more likely the dominant factor for the induced earthquakes shortly after fluid injection.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.134
Threshold uncertainty score0.269

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
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 head0.054
GPT teacher head0.286
Teacher spread0.232 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations177
Published2016
Admission routes2
Has abstractyes

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