Interpretation
Our analytical workflow solution-mode ICP-MS proved highly effective for evaluating trace-metal and REE distributions within Monterey Formation shale. Across the full dataset, calibration quality, internal standard performance, and replicate precision consistently demonstrated that the method produced high-quality, defensible geochemical results. The spider plots, bar charts, and trace-metal tables collectively show internally consistent patterns across wells and reveal meaningful geochemical signals relevant to our original research objective: determining whether Monterey shale holds distinct trace-metal or REE enrichments that could inform paleoenvironmental conditions or potential critical-mineral signatures.
Method Performance & Data Quality
Solution mode ICP-MS yielded stable signals, clean backgrounds, and robust internal-standard behavior, reflected by tight uncertainties and smooth downhole trends. Most analytes fell within the optimal dynamic range with minimal interference concerns following mode selection. Our QC materials and calibration checks remained within acceptable ±10% ranges.
The ICP-MS REE spider plots further confirm consistent normalization behavior, low noise, and reproducible REE patterns among samples. No major instrumental drift or charging issues were observed. Overall, the method produced high-quality, interpretable geochemical datasets.
What the Results Indicate Relative to the Research Problem
The spider charts normalized to PAAS reveal that the Monterey shale samples show mild LREE enrichment and relatively flat HREE patterns, consistent with typical marine shale signatures. Minor anomalies suggest subtle redox influences during deposition but no strong hydrothermal or diagenetic overprinting.
Trace-metal results show characteristic shale enrichments in Fe, V, Ni, and Ba, aligning with known Monterey depositional chemistry and organic-rich intervals. Some samples display elevated critical-element signals, but not at economically significant levels. Collectively, the results support the interpretation that Monterey shale preserves stable marine depositional chemistry, with REE patterns closely tracking PAAS-like compositions.
Possible Method Improvements
Although the dataset is strong, several refinements could enhance resolution:
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Additional internal standards would improve correction across mass ranges.
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Replicate digestions would better quantify digestion-based uncertainty.
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Including mineralogical data would allow better interpretation of REE carriers and metal-hosting phases.
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More time for method development could also improve sensitivity for low-abundance HREEs.
- More accurate sample calculations.
- Implementing geospatial data would help us put this information on a map to further analyze patterns.
- Sampling more of the Monetary Formation would help confirm if this REE trend is consistent with the entire layer and not just a spot in the area.
Budget Summary
Solution-Mode ICP-MS:
We counted each analysis from the first calibration standard to the last unknown.
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Total analyses ≈ 51
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Cost = 51 × $20/analysis = $1,020
Semiquantitative Runs :
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17 × $20/analysis = $340
Acid Digestions with Staci Loewy:
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Samples digested: 17
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Cost = 17 × $60/sample = $1,020
Grand Total
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Total cost = $2,380
Overall, our actual costs were slightly higher/lower than projected due to additional calibration checks and extended LA acquisition time required to optimize REE detection.
Summary
Our analytical method successfully produced high-quality geochemical data capable of addressing the research question posed in the project proposal. The trace-metal and REE patterns show consistent Monterey shale signatures with no evidence of instrumental or methodological failure. While several optional improvements could enhance future work, the overall method functioned well, produced meaningful geological insights, and it did end up going over budget expectations. This interpretation links directly back to the original project goals and demonstrates how ICP-MS workflows can generate reliable, publication-quality geochemical datasets for shale characterization.