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Hydraulic fracturing induced hybrid earthquakes in the Montney Basin, British Columbia, Canada may mark the transition from aseismic slip near the wellbore to seismic slip at greater distances

2020· article· en· W3094904988 on OpenAlexaffabout
R. M. Harrington, Hongyu Yu, Honn Kao, Yajing Liu, Bei Wang

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEarth and Planetary Sciences
Topicearthquake and tectonic studies
Canadian institutionsUniversity of VictoriaMcGill UniversityNatural Resources Canada
Fundersnot available
KeywordsInduced seismicitySeismologyGeologySeismic hazardMicroseismHydraulic fracturingSlip (aerodynamics)Structural basinGeotechnical engineeringEngineeringGeomorphology

Abstract

fetched live from OpenAlex

Seismicity related to fluid injection during unconventional oil and gas exploration has increased dramatically in North America in the last decade. The Western Canadian Sedimentary Basin experienced a significant increase in the number of M3+ earthquakes, including several M4+ associated with high-pressure stimulation during Hydraulic Fracturing (HF) activity. The vigorous seismic response to injection activity and low historical seismicity rates pose critical questions as to the triggering mechanism(s) and seismic hazard assessment in the affected areas. To monitor seismicity linked to injection, a dense local network of eight broadband seismic stations was installed in 2015 at distances of ~2 km around an active well pad with the purpose of monitoring seismicity prior to, and following, a HF well stimulation in the Montney Play in British Columbia, Canada. Here we present an earthquake source process study using observations from the local station network, and provide evidence for a slow-rupture seismic signal which may bridge the spectrum of fault slip rates from aseismic near the well bore, to typical seismic velocities at distances beyond ~1 km. Initial detection and relocation of seismicity between May 28 – October 15, 2015 yielded 350 well-constrained hypocenters of high-frequency events with a maximum magnitude of Mw 1.8 that resemble typical tectonically generated earthquakes. The detection procedure also yielded a total of 31 events with high-frequency (or broadband) onsets, that transition to protracted, low-frequency ringing relative to event magnitude, which we term hybrids. Both hybrid and high-frequency events occur at similar depths to the active well bore and at distances of ~1-2 km from injection stages, yet exhibit varying source characteristics in spite of their proximal source volumes. Hybrid waveforms are marked by broader P- and S-wave arrival pulse shapes, and spectral fitting suggests that the stress drop values are roughly an order of magnitude lower than high-frequency events, with average static stress drop values of 0.3 MPa and 4.9 MPa, respectively. We interpret wider phase arrival pulse widths and lower stress drop values as resulting from lower rupture velocities of hybrid events relative to high-frequency events. A dilatant strengthening effect would be expected in close proximity to the well bore, and near the hybrid sources, where material is weaker and pore pressures are elevated, which may result in slower rupture propagation when slip is initiated relative to further distances where material damage and pore pressure perturbation are both lower. Thus, hybrid earthquakes may mark regions where slip velocities transition from aseismic sliding directly next to the well bore, which has been observed in laboratory and meso-scale experiments, to typical seismic velocities at further distances. The size-duration scaling of the induced hybrids observed here also extends the scaling of slow earthquakes occurring in tectonic fault transition zones, and may provide the first observations to extend the scaling down to seismic moment values of ~1010.

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 score0.018
Threshold uncertainty score0.074

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.013
GPT teacher head0.177
Teacher spread0.164 · 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".

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Citations0
Published2020
Admission routes2
Has abstractyes

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