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Record W4407471205 · doi:10.32389/jeeg23-014

Detection of a Permeable Aquifer Geohazard Above Potash Mines using In-mine Time-domain Electromagnetics

2024· article· en· W4407471205 on OpenAlexaffabout
Todd John LeBlanc, S. L. Butler

Bibliographic record

VenueJournal of Environmental and Engineering Geophysics · 2024
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeophysical and Geoelectrical Methods
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsGeologyGeohazardPotashAquiferElectromagneticsMining engineeringHydrogeologyGroundwaterGeotechnical engineeringLandslideEngineeringEngineering physicsPotassium

Abstract

fetched live from OpenAlex

ABSTRACT Inflows pose a serious concern to potash mining operations and often increase operating costs and production slow-downs. The mapping and understanding of water-bearing geohazards is vital in the potash mining industry. Critical to this effort is the development of geophysical tools to quantify the type and magnitude of these geohazards. In this paper, we propose using in-mine time-domain electromagnetics (TDEM) as a viable tool for investigating porous, water-bearing anomalies in geological layers more distant than has been done with electrical methods in the past. This work includes a TDEM survey to better delineate and quantify the properties of a suspected geohazard near a potash mine in southern Saskatchewan. Our investigations had two objectives: one was to confirm and define the extent of the conductive brine in the overlying lithology. The second was to determine the effectiveness of deploying TDEM in-mine where full-space effects and nearby machinery pose significant noise challenges to operation. Our results found a strong conductive EM signature to the suspected anomaly, suggesting there is high value in deploying TDEM underground. In addition, full-space EM computer modeling was performed in COMSOL Multiphysics using 2D-axisymmetric geometry to account for lithological changes both above and below our survey. We invert the survey data using a pair of different strategies. The results of which demonstrate that the anomalous EM response is caused by a conductive high in the Dawson Bay carbonate layers above the mine workings.

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 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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.933
Threshold uncertainty score0.412

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)0.0000.000

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 head0.004
GPT teacher head0.172
Teacher spread0.168 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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
Published2024
Admission routes2
Has abstractyes

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