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Record W4281642889 · doi:10.1029/2022gl098062

A Small CO<sub>2</sub> Leakage May Induce Seismicity on a Sub‐Seismic Fault in a Good‐Porosity Clastic Saline Aquifer

2022· article· en· W4281642889 on OpenAlexaff
Stanislav Glubokovskikh, Erdinc Saygin, S. A. Shapiro, Boris Gurevich, Roman Isaenkov, David Lumley, Rie Nakata, Julian Drew, Roman Pevzner

Bibliographic record

VenueGeophysical Research Letters · 2022
Typearticle
Languageen
FieldEarth and Planetary Sciences
Topicearthquake and tectonic studies
Canadian institutionsCentennial College
Fundersnot available
KeywordsInduced seismicityPlumeGeologyAquiferSeismologyFault (geology)OverpressurePore water pressureOverburdenPetrologyGeotechnical engineeringGroundwater

Abstract

fetched live from OpenAlex

Abstract Despite public concerns, only a few CO 2 injections into saline aquifers have reported microseismicity. We analyze passive seismic monitoring of a small (15,000 tonnes and 0.15 MPa pressure) injection of supercritical CO 2 ‐rich mixture for Stage 2C of the CO2CRC Otway Project (Victoria, Australia), which induced 19 detectable events with maximum moment magnitude M W ‐0.5. The locations and dynamic parameters of the triggered events indicate a reactivation of a small fault patch where CO 2 flowed through the fault. Time‐lapse seismic images of the plume and reservoir simulations show that the reactivation occurred when the CO 2 plume reached this fault. This might be indicative of a fault weakening by the plume that enabled subsequent reactivation by pressure variations. Our observations suggest that a leakage from a commercial‐scale storage may trigger felt seismicity in the overburden without strong overpressure, thus, the de‐risking workflows should involve a detailed study of small faults.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.052
GPT teacher head0.279
Teacher spread0.227 · 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

Citations45
Published2022
Admission routes1
Has abstractyes

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