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Earthquake source parameter analysis shows hydraulic fracturing induced events are consistent with fault reactivation under regional stress in northeastern British Columbia, Canada

2020· article· en· W3096505003 on OpenAlexaffabout
Marco Pascal Roth, Alessandro Verdecchia, Kilian B. Kemna, John Onwuemeka, R. M. Harrington, Yajing Liu

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEarth and Planetary Sciences
Topicearthquake and tectonic studies
Canadian institutionsMcGill University
Fundersnot available
KeywordsSeismologyGeologyStructural basinFault (geology)Geomorphology

Abstract

fetched live from OpenAlex

An increasing number of M3+ earthquakes have been associated with Hydraulic Fracturing (HF) injection activity in low-permeable tight shale formations in the Western Canada Sedimentary Basin (WCSB) in the last decade. These include a Mw 4.6 on 08/17/2015 near Ft. St. John, a ML 4.5 on 11/30/2018, and two ML 3.2 on 10/05/2019, 10/08/2019 near Dawson Creek, British Columbia. Increased seismic activity in the Dawson-Septimus area prompted a temporary deployment of seismic stations in a joint effort between McGill University and the Ruhr University Bochum in order to perform higher-resolution monitoring relative to the regional seismic station coverage. Here, we use waveform data from that deployment of 22 (dominantly broadband) stations in close proximity to numerous HF wells in an area of roughly 60 x 70 km2, between July 2017 and August 2019, as well as records from 6 additional seismic stations northwest of the study area. In total, we detect 6222 local earthquakes, of which 5325 surpass a quality control criterion of having a horizontal location error ≤ 3 km. An investigation of the spatial and temporal correlation between injection and earthquake initiation using a cross-correlation based event similarity analysis during seismically active time periods reveals a high degree of event similarity within various clusters and a strong correlation with individual injection episodes at specific HF wells. In addition, event clusters also exhibit similar patterns in daily cumulative seismic moment, independent of differences in waveform characteristics. As individual clusters may represent the activation of specific geological structures, we perform double-difference relative relocation of seismicity to identify fault orientations. In addition, we invert for focal mechanism solutions per event cluster to check consistency with structures inferred with relocated hypocenters, and perform spectral fitting for source parameter analysis. Event relocations are performed on individual families, where the total catalog is divided into subsets corresponding to 24 seismic active time periods where 43 event families are active. Relocating each earthquake family separately allows us to successfully relocate 4571 out of the total 5325 events. The relative relocations align in two dominant orientations, with one roughly perpendicular to the maximum horizontal regional stress orientation, and the other at low angles to the maximum regional stress orientation on a regional scale around individual HF wells. Focal mechanism estimates for events with M > 2.0 result in two primary groups of faulting mechanisms: strike-slip deformation on faults implied by lineations striking at low angles to SH, and thrust-faulting deformation on faults implied by lineations perpendicular to SH. Seismic moment and corner frequency estimates from single spectrum and spectral ratio fitting as well as scaling relations will be presented.

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)0.001
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 score0.013
Threshold uncertainty score0.091

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0070.001

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 head0.025
GPT teacher head0.195
Teacher spread0.170 · 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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