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Coupling poroelastic stress change and rate-state fault slip models to simulate fluid injection induced seismic and aseismic slip

2020· article· en· W3089501435 on OpenAlexaff
Yajing Liu, Alessandro Verdecchia, Kai Deng, R. M. Harrington

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEarth and Planetary Sciences
Topicearthquake and tectonic studies
Canadian institutionsMcGill University
Fundersnot available
KeywordsPoromechanicsInduced seismicityGeologyHydraulic fracturingPore water pressureSeismologySlip (aerodynamics)Seismic hazardFluid pressureFault (geology)Fluid dynamicsGeotechnical engineeringMicroseismStress (linguistics)Shear stressMechanicsPorosityEngineeringPorous medium

Abstract

fetched live from OpenAlex

Fluid injection in unconventional hydrocarbon resource exploration can introduce poroelastic stress and pore pressure changes, which in some cases may lead to aseismic slip on pre-existing fractures or faults. All three processes have been proposed as candidates for inducing earthquakes up to 10s of kilometers from injection wells. In this study, we examine their relative roles in triggering fault slip under both wastewater disposal and hydraulic fracturing scenarios. We first present modeling results of poroelastic stress changes on a previously unmapped fault near Cushing, Oklahoma, due to injection at multiple wastewater disposal wells within ~ 10 km of distance, where over 100 small to moderate earthquakes were reported between 2015/09 to 2016/11 including a Mw5.0 event at the end of the sequence. Despite the much larger amplitude of pore pressure change, we find that earthquake hypocenters are well correlated with positive shear stress change, which dominates the regimes of positive Coulomb stress change encouraging failure. Depending on the relative location of the disposal well to the recipient fault and its sense of motion, fluid injection can introduce either positive or negative Coulomb stress changes, therefore promoting or inhibiting seismicity. Our results suggest that interaction between multiple injection wells needs to be considered in induced seismicity hazard assessment, particularly for areas of dense well distributions. Next, we plan to apply the model to simulate poroelastic stress changes due to multi-stage hydraulic fracturing wells near Dawson Creek, British Columbia, where a dense local broadband seismic array has been in operation since 2016. We will investigate the relative amplitudes, time scales, and spatial ranges of pore pressure versus solid matrix stress changes in influencing local seismicity. Finally, we have developed a rate-state friction framework for calculating slip on a pre-existing fault under stress perturbations for both the disposal and hydraulic fracturing cases. Preliminary fault slip simulation results suggest that fault response (aseismic versus seismic) highly depends on 1) the relative timing in the intrinsic earthquake cycle (under tectonic loading) when the stress perturbation is introduced, 2) the amplitude of the perturbation relative to the background fault stress state, and 3) the duration of the perturbation relative to the “memory” timescale governed by the rate-state properties of the fault. Our modeling results suggest the design of injection parameters could be critical for preventing the onset of seismic slip.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.085
Threshold uncertainty score0.169

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.070
GPT teacher head0.234
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 designSimulation or modeling
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

Citations0
Published2020
Admission routes1
Has abstractyes

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