As we wrap up our series on geochemistry laboratories, we want to take a moment to thank you for following along. Your interest in elevating the standard of geochemical data management inspires us to keep sharing insights that make a difference in exploration and mining.

For our final post, we’re focusing on the Quality Assurance (QA) side of QA/QC, ensuring that your data collection, preparation, and analysis are contamination-free, precise, and accurate.

Blanks: Keeping Contamination in Check

Blanks are essential for monitoring contamination at various stages of sampling and analysis. Here’s how to use them effectively:

• Coarse Blanks: Unmineralized material inserted before crushing, coarse blanks help identify contamination introduced during the crushing stage. Aim to insert coarse blanks at ~3% of your total samples.
• Chip Blanks: Introduced after crushing but before pulverizing, chip blanks target contamination during fine grinding. These should make up ~2% of your sample stream.

Blanks are particularly important when handling high-grade samples. Space them strategically before and after high-grade intervals, and request silica washes from the lab to reduce carryover contamination in preparation equipment.

Duplicates: Measuring Precision

Duplicates ensure consistency and reproducibility in your data. They should be used throughout the sampling and analysis pipeline:

• Field Duplicates: Taken at the same location during sampling, they detect variability in collection methods. Aim for ~1% of your total samples as field duplicates.
• Preparation Duplicates: Created by splitting a sample during preparation, they monitor contamination and errors in sample processing. These should account for ~2.5% of your samples.
• Pulp Duplicates: Taken from homogenized pulp before analysis, pulp duplicates measure analytical precision. Target ~2.5% for pulp duplicates.

Certified Reference Materials (CRMs): Testing Accuracy

CRMs are the cornerstone of laboratory validation, ensuring that your results are accurate across various sample grades.

• What is a Matrix-Matched CRM?
  A matrix-matched CRM (MM-CRM) is a standard with physical and chemical properties similar to your project’s samples. Using MM-CRMs are crucial because they reduce the risk of biases caused by differences in mineralogy or matrix effects between the CRM and your samples. For example, if your project is predominantly granite, your CRMs should have granite matrices.
• Do You Need a CRM for Every Matrix?
  No, it is not always necessary. For instance, if your project includes some diabase but the ore zone is exclusively hosted in granite, a diabase standard is not critical. Focus your CRM selection on the matrices where critical decision-making will occur.*
• Grades to Include:
  Use CRMs to cover a range of concentrations:
  • Low Grade: validate detection limits.
  • Medium Grade: represent typical sample concentrations.
  • High Grade: monitor accuracy at upper-grade ranges.

CRMs should make up ~4% of your total samples, alternating between grades for comprehensive testing; a high-grade CRM should be inserted in a high-grade zone; a medium-grade CRM in a medium-grade zone, and a low-grade CRM in a low-grade zone.

Umpire Labs and Round-Robin Programs

As your project advances, independent verification of your primary lab’s performance becomes increasingly important. This is where umpire labs and round-robin programs come into play.

• Umpire Labs:
  • An umpire lab is an independent laboratory used to verify the results of your primary lab. Sending ~5-10% of your pulps to an umpire lab is standard for advanced exploration and mining projects.
  • When to use umpire labs:
    • If you notice inconsistencies in QC performance from your primary lab.
    • During resource estimation phases, to validate the accuracy of critical datasets.
    • To establish confidence when preparing for feasibility studies or public reporting (e.g., NI 43-101 or JORC compliance).
• Round-Robin Programs:
  • Round-robin programs involve sending identical sample splits to multiple labs to evaluate inter-laboratory precision and accuracy.
  • When to conduct round robins:
    • To benchmark your primary lab against industry standards.
    • At the start of a program, especially if working in a new region or with a new lab.
    • As part of periodic checks during resource drilling programs to ensure ongoing reliability.

Both umpire labs and round-robin programs provide a higher level of assurance and are essential steps for high-value decision-making phases.

Routine QA Practices

Quality Assurance is not just about materials, but also about consistency in processes. Keep these best practices in mind:

• Documentation: Record the insertion order of QA/QC samples and regularly review lab performance.
• Lab Communication: Ensure labs are aware of high-grade samples and request additional cleaning protocols when necessary.
• Target QA Sample Rates: For a robust QA program, we recommend the above distribution of QA samples for a total of ~15%.

It is so important to emphasize that QA/QC programs are not about trying to “trick” the lab into failing, but rather it is about fostering collaboration to achieve the best possible results. By designing robust QA/QC protocols and maintaining open, continuous communication with your laboratory, we can ensure consistent data quality, reduce reanalysis, and save both the lab and your company valuable time and money. The ultimate goal is to generate reliable results efficiently, allowing you to confidently report to investors and stakeholders as quickly as possible. A strong partnership with your lab benefits everyone involved.

This concludes our series on geochemical laboratory essentials. We hope you have found it insightful and actionable for your projects. If you need further guidance or support in building or refining your QA/QC programs, feel free to reach out to us at LKI Consulting. We’re always here to help geoscientists make the most of their data.

Thank you for reading!