Tracking fluid mixing in epithermal deposits – Insights from in-situ δ18O and trace element composition of hydrothermal quartz from the giant Cerro de Pasco polymetallic deposit, Peru
Notice bibliographique
Résumé
Ore precipitation in mineral deposits formed in the upper parts of a porphyry system, at shallow crustal level (< 1.5 km), such as epithermal Au-Ag-(Cu)-(As) and polymetallic deposits is often triggered by fluid cooling and/or mixing between fluids from different sources. Commonly, in such deposits, two main fluid sources are identified a deeply sourced magmatic fluid and a shallow meteoric water stored in a surficial aquifer. Oxygen and hydrogen isotope compositions of gangue and alteration minerals using conventional bulk isotopic methods support the existence of mixing between these two fluid types. However, bulk isotope analysis provides only limited information on the exact mixing mechanisms and on the changing proportions of the involved fluids. Due to their high spatial resolution, SIMS in-situ oxygen isotope and LA-ICP-MS trace element analyses, in transects across growth zones of single crystals are adequate tools to trace the dynamics of this fluid mixing. In this study, in-situ SIMS oxygen isotope and LA-ICP-MS trace element analyses were performed on 10 selected quartz crystals from the giant Cerro de Pasco porphyry-related epithermal polymetallic deposit in central Peru. The results, combined with previous microthermometric and LA-ICP-MS fluid inclusion studies on the same or equivalent crystals, allow quantifying and documenting the mixing between different types of fluids that formed the large Cerro de Pasco epithermal polymetallic deposit. The δ18Oquartz values range between 4‰ and 20‰ and display variations up to 11.5‰ inside single crystals that cannot be only, nor mainly ascribed to fluid temperature changes. Rather, these variations record variable mixing proportions of a rising moderate-salinity magmatic fluid with a δ18OH2O around 10‰ and a low-salinity fluid with a δ18OH2O between 0 and 4‰, the latter stored below the paleo-water table. Each analyzed quartz crystals also display important variation of their trace element content, with Al (43 to 2098 ppm), Li (0.7 to 18 ppm), Ge (1.1 to 24ppm) and Ti (0.8 to 10 ppm). These variations do not systematically correlate with oxygen isotope compositions. This suggests that quartz trace element content is controlled by a complex interplay of fluid composition, temperature, pressure, and growth rate. Application of published Ti-in-quartz geothermometers on quartz grains from which the precipitation temperature is well constrained by fluid inclusion microthermometry, shows that it can lead to overestimation or underestimation of precipitation temperatures by more than 50 °C. The obtained δ18Oquartz patterns measured along profiles in the studied quartz crystals, and less clearly the in-situ trace element compositions, reveal abrupt changes and suggest that mixing between magmatic and surface-derived low-salinity fluids was not a continuous process. It rather took place through the influx of multiple short-lived pulses of magmatic fluid into the surface-derived low-salinity fluid surface aquifer.
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 | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».