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Record W3132228739 · doi:10.1785/0120200251

A Study on the Largest Hydraulic Fracturing Induced Earthquake in Canada: Numerical Modeling and Triggering Mechanism

2021· article· en· W3132228739 on OpenAlexaffabout
Bei Wang, Alessandro Verdecchia, Honn Kao, R. M. Harrington, Yajing Liu, Hongyu Yu

Bibliographic record

VenueBulletin of the Seismological Society of America · 2021
Typearticle
Languageen
FieldEarth and Planetary Sciences
Topicearthquake and tectonic studies
Canadian institutionsMcGill UniversityUniversity of VictoriaGeological Survey of Canada
Fundersnot available
KeywordsPoromechanicsInduced seismicityHydraulic fracturingGeologyFluid pressurePore water pressureSeismologyStress fieldPermeability (electromagnetism)Geotechnical engineeringStress (linguistics)Finite element methodMechanicsPorosityStructural engineeringEngineeringPorous medium

Abstract

fetched live from OpenAlex

ABSTRACT The Mw 4.6 earthquake that occurred on 17 August 2015 northwest of Fort St. John, British Columbia, is considered the largest hydraulic-fracturing-induced event in Canada, based on its spatiotemporal relationship with respect to nearby injection operations. There is a ∼5 day delay of this Mw 4.6 mainshock from the onset of fluid injection at the closest well pad (W1). In contrast, other two nearby injection wells (W2 and W3) have almost instantaneous seismic responses. In this study, we first take a forward numerical approach to investigate the causative mechanisms for the Mw 4.6 event. Specifically, three finite-element 3D poroelastic models of various permeability structures and presence or absence of hydraulic conduits are constructed, to calculate the coupled evolution of elastic stress and pore pressure caused by multistage fluid injections. Our simulation results suggest that pore pressure increase associated with the migration of injected fluid is required to accumulate sufficient stress perturbations to trigger this Mw 4.6 earthquake. In contrast, the elastic stress perturbation caused by rock matrix deformation alone is not the main cause. Furthermore, injection and seismicity at W1 may have altered the local stress field and brought local faults closer to failure at sites W2 and W3. This process could probably shorten the seismic response time and, thus, explain the observed simultaneous appearance of injection and induced seismicity at W2 and W3.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.675
Threshold uncertainty score0.753

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)0.0000.000

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 head0.029
GPT teacher head0.211
Teacher spread0.181 · 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.

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

Citations35
Published2021
Admission routes2
Has abstractyes

Explore more

Same venueBulletin of the Seismological Society of AmericaSame topicearthquake and tectonic studiesFrench-language works237,207