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Record W2063931499 · doi:10.3997/2214-4609.20142156

Filling in the Gap: Capturing the Full Scaling Relationships of Hydraulic Fracturing

2014· article· en· W2063931499 on OpenAlexaff
A. M. Baig, T. Urbancic, Katie Bosman

Bibliographic record

VenueProceedings · 2014
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicSeismic Imaging and Inversion Techniques
Canadian institutionsCanadian Apheresis Group
Fundersnot available
KeywordsGeophoneMagnitude (astronomy)Hydraulic fracturingInduced seismicityGeologyScalingRange (aeronautics)Fracture (geology)Scale (ratio)SeismologyGeotechnical engineeringMaterials sciencePhysicsGeometry

Abstract

fetched live from OpenAlex

Summary Seismicity associated with hydraulic fracturing can range in magnitude up to and beyond +M3, large enough in many cases to be felt on surface. These higher magnitude events are in contrast to the smaller magnitude events that are normally used to characterize the efficacy of fracture treatments, as they can represent the activation of structures on the scale lengths of hundreds of meters, whereas the microseismicity (below M0) in the reservoir is associated with the activation of structures up to the scale of 10s of m. To accurately characterize events activating structures of intermediary lengths, i.e. between 10 m and 100 m, deploying instruments at or near the reservoir level, and low-frequency instruments at shallower depths and on the surface will help determine accurate source parameters for events not only one the surface, but also for events not necessarily strong enough to propagate clearly to the surface but high enough magnitude to saturate typical 15 Hz downhole geophones.

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)0.005
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 score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0000.001
Research integrity0.0000.001
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 head0.029
GPT teacher head0.213
Teacher spread0.184 · 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

Citations0
Published2014
Admission routes1
Has abstractyes

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