3D joint inversion of magnetotelluric and airborne tipper data: a case study from the Morrison porphyry Cu–Au–Mo deposit, British Columbia, Canada
Bibliographic record
Abstract
ABSTRACT Z‐axis tipper electromagnetic and broadband magnetotelluric data were used to determine three‐dimensional electrical resistivity models of the Morrison porphyry Cu–Au–Mo deposit in British Columbia. Z‐axis tipper electromagnetic data are collected with a helicopter, thus allowing rapid surveys with uniform spatial sampling. Ground‐based magnetotelluric surveys can achieve a greater exploration depth than Z‐axis tipper electromagnetic surveys, but data collection is slower and can be limited by difficult terrain. The airborne Z‐axis tipper electromagnetic tipper data and the ground magnetotelluric tipper data show good agreement at the Morrison deposit despite differences in the data collection method, spatial sampling, and collection date. Resistivity models derived from individual inversions of the Z‐axis tipper electromagnetic tipper data and magnetotelluric impedance data contain some similar features, but the Z‐axis tipper electromagnetic model appears to lack resolution below a depth of 1 km, and the magnetotelluric model suffers from non‐uniform and relatively sparse spatial sampling. The joint Z‐axis tipper electromagnetic inversion solves these issues by combining the dense spatial sampling of the airborne Z‐axis tipper electromagnetic technique and the deeper penetration of the lower frequency magnetotelluric data. The resulting joint resistivity model correlates well with the known geology and distribution of alteration at the Morrison deposit. Higher resistivity is associated with the potassic alteration zone and volcanic country rocks, whereas areas of lower resistivity agree with known faults and sedimentary units. The pyrite halo and ≥0.3% Cu zone have the moderate resistivity that is expected of disseminated sulphides. The joint Z‐axis tipper electromagnetic inversion provides an improved resistivity model by enhancing the lateral and depth resolution of resistivity features compared with the individual Z‐axis tipper electromagnetic and magnetotelluric inversions. This case study shows that a joint Z‐axis tipper electromagnetic–magnetotelluric approach effectively images the interpreted mineralised zone at the Morrison deposit and could be beneficial in exploration for disseminated sulphides at other porphyry deposits.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".