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Hydrogeological modelling applied to mineral exploration

2020· article· en· W3104558819 on OpenAlexaffabout
Valérie Plagnes, David Quirt, Antonio Benedicto, Patrick Ledru

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological Modeling and Analysis
Canadian institutionsiNano Medical (Canada)
Fundersnot available
KeywordsGroundwaterUnconformityGeologyMineralization (soil science)UraniumStructural basinHydrogeologyGeochemistryWater wellBedrockMineral explorationUranium oreAquiferHydrology (agriculture)GeomorphologySoil science

Abstract

fetched live from OpenAlex

A multidisciplinary approach combining a groundwater hydrogeochemical survey and a 3D groundwater flow model was applied to unconformity-type U mineralization in the Athabasca Basin (Canada), as a new supplementary guide for uranium exploration. This approach was developed at the McClean Lake Operation site (eastern part of the basin), where several uranium deposits have already been mined and others are not yet mined. The goal of ongoing exploration in this area is to find new deposits in the vicinity of known deposits to facilitate possible future mining. Groundwater levels were measured in 60 wells and groundwater sampling was carried out in 31 of these wells, some of these wells are screened in bedrock below the unconformity and others in sandstones above the unconformity. Among these wells, we included 4 wells located near a known ore body (SABRE sector) to better evaluate the potential of our approach to identify the presence of U mineralization. The results show that in this study area, the U concentration and saturation index maps are not good indicators of U mineralization as U concentrations are very low for all samples due to the strong reducing conditions. However, 5 of the wells show remarkable geochemical composition: the highest total dissolved solids, high Cl concentration and strong relationships between Cl and concentrations of Na, K, Mg, Ca, Fe as well as Sr and Ba, suggesting that these ions may have come from a common source. Four of these five samples belong to the deposit of the SABRE sector, but the fifth well is located upstream of this region, far from a known ore body. A 3-D groundwater model was developed for the entire basin and the flow path ending at this well screen was traced to its source by reverse particle tracking. In the structure of the groundwater model, graphite-rich fault zones are considered the main geological structures controlling groundwater flows. The up-gradient geochemical plume deciphered from the backflows allows the identification of new exploration targets. This approach appears to be an appropriate method for prioritizing locations for future exploration drilling.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.039
Threshold uncertainty score0.079

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0100.002

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 head0.084
GPT teacher head0.211
Teacher spread0.127 · 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 designSimulation or modeling
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

Citations2
Published2020
Admission routes2
Has abstractyes

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