Integrating petrophysical and geophysical data in forward and inversion modelling of Zone 5-8, Raglan Mine, Quebec, Canada
Bibliographic record
Abstract
Raglan Mine is located on the Ungava peninsula, Québec, Canada. It’s a Ni-Cu-PGE magmatic sulphide deposit undergoing brownfield exploration. Given the available data from Raglan Mine and the underutilization of geophysical data integration in mineral exploration, this thesis’ purpose is to investigate the utility of data integration. Specifically, four objectives are set to integrate petrophysical and geophysical data in forward and inversion modelling of Zone 5-8 at Raglan Mine. The first two objectives are met through forward modelling a 3D geological model. Magnetic and gravity forward models are compared to observed data. The major outcome establishes a macro-magnetic susceptibility maximum for the ultramafic of 0.31 SI. Vertical gravity modelling shows lows over sediments, and highs over basalts and an intermediate high over the ultramafic. Additionally, the resolvability of ore targets is investigated, showing that these targets are unresolvable using airborne and terrestrial magnetic and gravity methods. These results are incorporated in inversion modelling. Inversion modelling is an optimization problem, which is non-unique, meaning many solutions could fit. This issue is mitigated through constraints from input data and reference models (cooperative inversion). Objectives 3 and 4 are met by running single parameter and cooperative inversions. Outcomes of single parameter inversions show that magnetic inversions are effective in outlining the UM unit to a depth of ~1000-1250m with a cut off of 0.05 SI. Single parameter gravity gradient inversions outline lower density sediments and higher density basalts. The ultramafic is outlined to depths of ~560-910m (cut off 0-0.3 g/cm3) after which ambiguity exists due to density overlap with basalt. Gravity gradient inversions are enhanced through the cooperative magnetic isosurface reference model, which also balances out the impact of the surface geology constraint. The gravity gradient isosurface constraint on the cooperative magnetic inversion causes the ultramafic limbs to diverge. Overall, forward modelling is able to approximate observed data, and single parameter and cooperative inversion modelling are able to position the magnetic ultramafic and higher and lower density sediments and basalts in geologically and geophysically logical locations. This approach has promising applications in other zones.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".