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Record W2323953236 · doi:10.1190/segam2012-1446.1

Multi-component investigation of fracturing in a potash mining region in Saskatchewan, Canada

2012· article· en· W2323953236 on OpenAlexaffabout
Andrew Nicol, Don C. Lawton

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicSeismic Imaging and Inversion Techniques
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsGeologyPotashDrillingEvaporiteBayGemologyBoreholeEconomic geologyIgneous petrologyAzimuthTerrainMining engineeringAnisotropyStructural basinSeismologyGeochemistryGeomorphologyEngineering geologyTectonicsMetamorphic petrologyVolcanismGeotechnical engineeringCartographyOceanographyPotassium

Abstract

fetched live from OpenAlex

Fractures in the subsurface are known to impact the quality of seismic imaging. This multi-component, time-lapse study focuses on the fracture-induced anisotropy within a potash mining region in the Williston Basin. The area of interest is the Dawson Bay Formation, a fractured carbonate overlying the Prairie Evaporite Formation which contains the potash ore deposits. PP and PS full azimuth volumes were divided into 4 sub-volumes consisting of a stack of source-receiver ray paths consisting of a 45 degree aperture for both a baseline and monitor surface. Through their interpretation and travel-time analysis, weak azimuthal velocity anisotropy was observed within the Dawson Bay Formation. Analysis of Vp/Vs indicates that there is a significant decrease in shear-wave velocity in the centre of the survey between the Birdbear and Winnipegosis formations, including the Dawson Bay Formation. These Vp/Vs results, along with travel time differences, confirm the presence of fracturing in the subsurface, and more specifically, within the Dawson Bay carbonates.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.082
Threshold uncertainty score0.164

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
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 head0.022
GPT teacher head0.206
Teacher spread0.183 · 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

Citations1
Published2012
Admission routes2
Has abstractyes

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