Geometric and hydrodynamic modelling and fluid-structural relationships in the southeastern Athabasca Basin and significance for uranium mineralization
Bibliographic record
Abstract
Unconformity-type uranium deposits in the Athabasca Basin are spatially associated with reactivated basement faults intersecting the unconformity surface. However, questions such as what special factors focused fluid flow along and within fault zones, and why some faults are more fertile than others, are still unclear. This study aims to tackle these questions through examination of the southeastern Athabasca Basin. First, a basement structural map was compiled based on basement geophysical signatures, which shows three dominant sets of faults trending NE, NW, and NNW. A 3D model of the sub-Athabasca unconformity was constructed with GoCADR using publicly available geological and drill-hole data, revealing a number of dominantly NE-trending ridges and valleys. These unconformity topographic features are interpreted to be the products of the combined action of three main factors: 1) pre-Athabasca group ductile faulting and alteration; 2) differential weathering and erosion; and 3) post-Athabasca reactivation of pre-existing, graphite-rich ductile shear zones. The basin-scale numerical modelling of hydrodynamics indicates that fluid pressures in the Athabasca Basin were close to hydrostatic throughout its sedimentary history, and that thermal convection cells may have been well developed in the lower part of the basin, particularly below the Wolverine Point Formation aquitard. The modeling results also show that individual convection cells are less than 2 km, implying that individual mineralization centres, if controlled by thermal convection, may be spaced at just a few kilometers. Local-scale numerical modelling of fluid flow indicates that the location and spacing of basement faults influence thermally-driven fluid convection. In a model with an isolated fault, the fault coincides with an upwelling plume. In the case of two faults, the faults may coincide with upwelling flow or alternatively be centrally located below convection cells, depending on fault spacing. In the latter case, fluid may flow into and out of individual fault zones. Modelling of fluid-flow in response to mechanical compression suggests that fluid migrates up the fault during compression, and that the models with the most shallowly dipping fault and those with offset on the fault have slightly greater flow rates than the other models. The various relationships between fluid-flow and faults can explain why some faults are more favourable for fluid flow than others, which may be potentially used to evaluate whether a given structure has the potential to host mineralization.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".