Exploring for copper–gold deposits with electromagnetic surveys at Opemiska, Canada
Notice bibliographique
Résumé
Finding and delineating new economic Cu-Au ore zones corresponding to poorly conductive disseminated mineralization and narrow massive chalcopyrite veins in the Chapais-Chibougamau mining district of Québec is a challenging exploration problem. The site of the former Opemiska underground mine was the location for conducting an experimental ground time-domain electromagnetics (EM) survey for mapping the conductivity, the anisotropy of the conductivity and the chargeability estimated from shape reversals. Measurements at fourteen different sites confirmed the variability of the EM response, and the difficulty of relying on a definite EM signature to locate the economic sulfides. The Cu-Au zones showed a variety of EM responses with a maximum conductance of 100 Siemens and 2 ms time constant. The trends, sizes, shapes and conductances of the relatively strong conductors were identified with success and modeled using thin plates in full space. The vein direction in the weakly conductive zones were quantified from the x-component data. In only one instance was a TDEM response associated with mineralization interpreted to be chargeable. Petrophysical measurements and microscopic observations suggest complex interrelations between the amount of ore, the fabric of the rock, texture, porosity, mineralogical associations and impurities. This explains a wide range of bulk conductivity values from ~0.01 S/m to 4000 S/m measured on rock samples, and suggests that chalcopyrite might be a semiconductor at some locations at Opemiska. The magnetic viscosity effects observed at time scales between 0.01 and 10 ms at Opemiska are associated with magnetic grains of variable size in rocks. Recent observations made during a ground time-domain electromagnetic (TDEM) survey at Opemiska are consistent with four aspects of the spatial and amplitude characteristics of a magnetic viscosity response: (1) the ∂Bz/∂𝑡𝑡 decay rate is roughly proportional to 1/𝑡𝑡1+ α, where -0.4 < α < 0.4; (2) the anomalies are mainly visible on the z-component when the EM receiver sensor is located inside or just outside the transmitter loop; (3) there is no obvious x- or y-component response; (4) the sites where magnetic viscosity effect are seen in the TDEM data are coincident with an airborne magnetic anomaly. Previous studies have demonstrated that the magnetic viscosity could be caused by (i) fine-grained particles of maghemite or magnetite in the overburden, regolith or soil that were formed through lateritic weathering processes; (ii) volcanic glass shards from tuff containing ~1% by weight magnetite, which occurs as grains ~0.002 to 0.01 μm in size precipitated in a spatially uniform way, or (iii) from Gallionella bacterium that precipitates ferrihydrite that oxidizes to nanocrystalline maghemite aggregates. The sites investigated at Opemiska are outcropping and well exposed with relatively little or no overburden, and are unfavorable to the formation of maghemite; hence, it is assumed that the source of magnetic viscosity seen at Opemiska cannot be the maghemite, or the other aforementioned causes. Hand samples were collected from Opemiska to identify the minerals present. Polished thin sections observed under an optical reflecting microscope identified the accessory minerals magnetite, ilmenite and pyrrhotite, all known for their relatively high magnetic susceptibility. The use of the scanning electron microscope confirmed fine grained magnetite grains as small as 0.667 μm. An electromagnetic induction spectrometer confirmed the viscous nature of the susceptibility of the Opemiska samples. This suggests that magnetic viscosity could originate not only from fine-grained magnetite and maghemite particles located in the weathered regolith, but also from other iron oxides and magnetic minerals embedded in the rock itself.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
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 | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,002 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| 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 ».