“Thank you for reading. Follow me for fresh insights.”Quality Assurance and Quality Control (QAQC) are essential pillars in nickel exploration programs, underpinning the reliability of geological, geochemical, and assay data that drive resource estimation and project development. As the demand for nickel grows—especially for batteries and green technologies—robust QAQC protocols are more critical than ever to ensure that exploration results are accurate, reproducible, and trusted by stakeholders.
The Importance of QAQC in Nickel Exploration
QAQC in nickel exploration is designed to minimize errors, detect contamination, and ensure that all data collected—from drilling to laboratory analysis—meets international standards. Reliable data is the foundation for resource modeling, economic evaluation, and ultimately, investment decisions. Without rigorous QAQC, there is a risk of over- or underestimating resources, leading to costly mistakes in mine planning and development (McClenaghan et al., 2020; Bazania and Boisvert, 2025).
Core Components of QAQC
1. Quality Assurance (QA)
Quality Assurance is the proactive aspect of QAQC, focusing on the design and implementation of procedures that prevent errors before they occur. This includes:
- Developing standardized protocols for sampling, sample handling, and laboratory analysis.
- Training personnel in best practices.
- Selecting accredited laboratories and ensuring they follow recognized methods (McClenaghan et al., 2020).
2. Quality Control (QC)
Quality Control is the reactive component, involving the monitoring and verification of data quality throughout the exploration process. Key QC practices include:
- Inserting control samples (blanks, standards, duplicates) into the sample stream.
- Regularly reviewing assay results for accuracy and precision.
- Conducting external audits and inter-laboratory comparisons (McClenaghan et al., 2020; Bazania and Boisvert, 2025).
Best Practices in QAQC for Nickel Exploration
a. Control Samples
- Blanks: Used to detect contamination during sample preparation and analysis.
- Certified Reference Materials (CRMs): Monitor the accuracy of laboratory results.
- Duplicates: Assess the precision of sampling and analytical procedures.
A typical QAQC program will insert these control samples at regular intervals (often 1 in every 20–30 samples) to provide a continuous check on data quality (McClenaghan et al., 2020).
b. Data Validation and Management
- All data should be validated at multiple stages, from field collection to database entry.
- Use of digital data capture and management systems reduces transcription errors and enables efficient tracking of QAQC results (McClenaghan et al., 2020).
c. Laboratory Protocols
- Laboratories should participate in proficiency testing and round-robin programs to benchmark their performance.
- Results from primary and umpire (secondary) labs should be compared to identify any systematic biases (McClenaghan et al., 2020; Bazania and Boisvert, 2025).
d. Documentation and Transparency
- All QAQC procedures, results, and corrective actions must be thoroughly documented.
- Transparent reporting builds confidence among investors, regulators, and other stakeholders (McClenaghan et al., 2020).
Challenges and Technological Advances
Nickel exploration often occurs in remote or logistically challenging environments, increasing the risk of sample mix-ups, contamination, or data loss. Advances in automation, digital data capture, and real-time monitoring are helping to address these challenges by:
- Reducing human error in sample handling and data entry.
- Enabling rapid detection of QAQC failures, allowing for immediate corrective action (Galindo-Salcedo et al., 2021; Azamfirei, Psarommatis and Lagrosen, 2023).
Case Example: National Protocols and Industry Standards
The Geological Survey of Canada, for example, has developed comprehensive protocols for field sampling, laboratory analysis, and QAQC in mineral exploration. These protocols emphasize consistent sample media, diligent field notes, and rigorous QAQC procedures, enabling direct comparison of data across projects and regions (McClenaghan et al., 2020). Adopting such standardized approaches ensures that nickel exploration data is robust, comparable, and defensible.
Conclusion
QAQC is not just a regulatory requirement but a strategic investment in the credibility and success of nickel exploration programs. By implementing best practices in QAQC—ranging from careful sample handling to advanced data management—explorers can ensure that their resource estimates are accurate, their projects are economically viable, and their stakeholders are confident in the results (McClenaghan et al., 2020; Bazania and Boisvert, 2025; Galindo-Salcedo et al., 2021; Azamfirei, Psarommatis and Lagrosen, 2023).
Figure 1: Overview of QAQC principles and best practices in nickel exploration
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References
Galindo-Salcedo, M., Pertúz-Moreno, A., Guzmán-Castillo, S., Gómez-Charris, Y., & Romero-Conrado, A., 2021. Smart manufacturing applications for inspection and quality assurance processes. **, pp. 536-541. https://doi.org/10.1016/j.procs.2021.12.282
Bazania, J., & Boisvert, J., 2025. Current state of industry practice in mineral resource estimation and classification. CIM Journal. https://doi.org/10.1080/19236026.2025.2465091
Azamfirei, V., Psarommatis, F., & Lagrosen, Y., 2023. Application of automation for in-line quality inspection, a zero-defect manufacturing approach. Journal of Manufacturing Systems. https://doi.org/10.1016/j.jmsy.2022.12.010
McClenaghan, M., Spirito, W., Plouffe, A., McMartin, I., Campbell, J., Paulen, R., Garrett, R., Hall, G., Pelchat, P., & Gauthier, M., 2020. Geological Survey of Canada till-sampling and analytical protocols: from field to archive, 2020 update. **. https://doi.org/10.4095/326162
