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Record W2188723710

Statistics of microseismic events: implications for geomechanics

2012· article· en· W2188723710 on OpenAlex
Mélanie Grob, Mirko van der Baan

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicEarthquake Detection and Analysis
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMicroseismHydraulic fracturingGeothermal gradientGeologyGeomechanicsSeismologyFractal dimensionInduced seismicityTectonicsPermeability (electromagnetism)FractalGeotechnical engineeringGeophysicsMathematics
DOInot available

Abstract

fetched live from OpenAlex

Summary Processes like cyclic steam injection, hydraulic fracturing... are used to increase the permeability of oil and gas reservoirs or geothermal fields. Microseismic events are created during these processes at the injection point due to the local stress changes induced by fluid pressure. The location of events can reveal pre-existing structures whose shape was determined by surrounding tectonic stresses, and weak planes within rocks. The spatial distribution of events is quantified by the D-value, a statistical coefficient which reflects the clustering of events. Source properties of microseismic events can be retrieved through the fractal dimension which describes the frequency-magnitude distribution of the events, also known as b-value. A combined statistical study of these two dimensions can help infer the variations of local stresses in a reservoir.

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.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.872
Threshold uncertainty score0.999

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)0.0020.000

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 head0.021
GPT teacher head0.250
Teacher spread0.229 · 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

Quick stats

Citations3
Published2012
Admission routes1
Has abstractyes

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