Short Wavelength Infrared Spectral Characteristics of the HW Horizon: \nImplications for Exploration in the Myra Falls Volcanic-Hosted Massive Sulfide Camp, Vancouver Island, British Columbia, Canada
Notice bibliographique
Résumé
Short wavelength infrared (SWIR) spectrometry has been used to identify previously unmapped hydrothermal \nalteration zones around volcanic-hosted massive sulfide (VHMS) orebodies at Myra Falls, Vancouver Island, \nBritish Columbia. Hydrothermal alteration assemblages are uniformly dominated by fine-grained white \nmica, with poor development of mineralogical zonation. SWIR spectrometry is an ideal exploration tool for \ncharacterizing this fine-grained hydrothermal alteration. At Myra Falls, SWIR spectrometry has identified subtle \nshifts in the wavelengths of the AlOH absorption feature of white mica, corresponding to compositional \nchanges in altered rhyolite distal and proximal to ore. AlOH absorption occurs at shorter wavelengths (<2,198 \nnm) and corresponds to lower Fe, Fe + Mg, and Si/Al and higher Na/(Na + K) in strongly altered samples proximal \nto ore (slightly sodic muscovites). AlOH absorption occurs at longer wavelengths (>2,206 nm) and corresponds \nto higher Fe, Fe + Mg, and Si/Al and lower Na/(Na + K) in samples distal to ore (nonsodic slightly \nphengitic muscovites). White mica in siltstone within a meter of VHMS ore has higher Zn, V, Fe, and Mg contents \nthan white mica distal to these altered samples. Chlorite compositions, identified by SWIR, also show systematic \nchanges with intensity of alteration and distance from ore. The average wavelength of the FeOH absorption \nfeature for chlorite in rhyolitic samples proximal to ore is 2,241 nm (intermediate Mg chlorite), \nwhereas wavelengths in background samples average 2,247 nm (intermediate Fe chlorite). Similar changes are \nobserved in footwall and hanging-wall andesites, with samples near the Battle mine containing muscovite to \nphengitic muscovite (average wavelength of the AlOH absorption feature of 2,200 nm) and Mg-rich chlorite \n(average wavelength of the FeOH absorption feature of 2,245 nm) to regional andesite samples with phengitic \nmuscovite (average wavelengths of the AlOH absorption feature of 2,209 nm) and Fe-rich chlorite (average \nwavelength of the FeOH absorption feature of 2,249 nm). In weakly altered rocks white mica compositions also \nvary with host lithology. The AlOH absorption feature occurs at longer wavelengths in white mica in dacite and \nandesite compared to adjacent rhyolitic rocks, suggesting that higher Fe and Mg in the host lithology affects \nthe composition of white mica. \nTwo zones of intense hydrothermal alteration above the Battle and HW orebodies have distinctive SWIR \nspectral characteristics, with the AlOH and FeOH features occurring at shorter wavelengths (<2,197 and \n<2,240 nm, respectively). Small anomalous zones of alteration were also identified in the Thelwood Valley area, \nwhere minor mineralized zones are present. As broad zones of fine-grained white mica (sericite) alteration are \nubiquitous throughout the Myra Falls property, alteration proximal to ore cannot be identified simply by visual \nlogging of drill core. Alteration zonation may be determined by subtle shifts in white mica spectral characteristics. \nThis study indicates that SWIR analysis may be an effective field-based exploration tool for quantifying \nthe intensity of alteration associated with VHMS orebodies, and that trends in mineral compositions, even in \nvery fine grained rocks, can be used as mine-scale vectors to ore.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».