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
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".