Sampling Quality Control Procedures

The Importance of QA/QC Samples in Geology for Accurate Results In geological work, a robust QA/QC system (Quality Assurance and Quality Control) is fundamental for obtaining accurate and reliable data. Various types of samples are utilized within the QA/QC framework to verify the quality of operations, prevent errors, and ensure the integrity of final results. Types of QA/QC Samples and Their Importance 🔹 Blanks: Used to confirm the absence of contamination during sampling or analysis. How? Inert materials that lack the target element are inserted among the sequence of samples. Purpose: To verify the cleanliness of tools and the surrounding environment. 🔹 Duplicates: Collected from the same source or analyzed from the original sample to assess precision. Types: Field Duplicates: Collected from the same location. Lab Duplicates: The same sample is analyzed twice. Split Duplicates: The original sample is divided and analyzed separately. Purpose: To measure reproducibility and consistency of results. 🔹 Certified Reference Materials (CRMs): Samples with known concentrations used as a reference during analysis. Purpose: To ensure the accuracy of laboratory instruments and procedures. 🔹 Control Samples: Periodically added to monitor quality consistency during operations. Purpose: To assess performance across different project stages. 🔹 Check Samples: Sent to alternative laboratories to verify the accuracy and comparability of results. Purpose: To benchmark the performance of the primary lab against others. 🔹 Spiked Samples: Known quantities of the target element are added to these samples to test analytical efficiency. Purpose: To check instrument sensitivity and analytical accuracy. Why QA/QC Matters 1. Accuracy Assurance: Reflects the geological reality with precision. 2. Error Detection: Identifies contamination or technical issues. 3. Enhanced Confidence: Enables decisions based on reliable data. Conclusion Implementing a strong QA/QC system is an investment in the accuracy of results and operational efficiency. Incorporating samples like Blanks, Duplicates, and CRMs enhances data quality and ensures sound decision-making. Have you implemented QA/QC samples in your projects? Share your experiences and insights! --- #QAQC #Geology #GeologicalExploration #DataAccuracy #MiningIndustry #QualityControl #GeochemicalAnalysis #CertifiedReferenceMaterials #GeologyWork #Sudan #ArabianNubianShield #SaudiArabia

The Critical Role of QAQC in Mineral Exploration and Mining: Ensuring Data Integrity and Project Success In the mineral exploration and mining industries, Quality Assurance and Quality Control (QAQC) are fundamental for ensuring reliable data, minimizing risks, and optimizing resource development. A robust QAQC system ensures standardized procedures throughout exploration—from sampling to analysis—enhancing decision-making and minimizing uncertainties. 1. Sample Collection & Handling Accurate exploration results depend on careful sampling protocols. Samples must be representative, collected properly, and preserved to avoid contamination. Chain-of-custody tracking ensures sample integrity from field collection to laboratory analysis. 2. Geological Logging Geological logging is essential for creating resource models. Accurate, consistent logging of lithology, mineralization, and alteration data is crucial for reliable resource estimation and modeling. 3. Laboratory Analysis Analytical methods must be precise and standardized. Laboratories should use accredited techniques (e.g., ICP, XRF, fire assays) and regularly calibrate equipment to ensure accurate assay results. 4. Certified Reference Materials (CRMs), Blanks, and Duplicates The use of CRMs, blanks, and duplicates in assay batches helps identify errors in the analysis, verify assay accuracy, detect contamination, and assess precision. 5. Geophysical & Geochemical Survey QAQC QAQC in geophysical and geochemical surveys ensures that instruments are calibrated correctly and consistent methods are used. Environmental corrections and quality control in geochemical sampling ensure the reliability of survey data. 6. Data Integrity and Management QAQC in data management is essential for maintaining the integrity of geological data. Proper validation checks allow for early detection of discrepancies, ensuring that only accurate, verifiable data is used in resource modeling. 7. Drill Core Sampling Drill core sampling protocols are key for obtaining representative samples. Duplicate sampling and assay validation help ensure that core results reflect the true characteristics of the deposit, supporting accurate resource estimation. 8. Statistical Analysis Geostatistical methods, like kriging and cross-validation, help evaluate assay data variability and optimize resource models by quantifying uncertainty and identifying anomalies. 9. Reporting Standards & Regulatory Compliance Adhering to international reporting standards such as JORC, NI 43-101, and SAMREC ensures transparency and consistency in resource reporting, providing confidence to stakeholders and investors. By embedding QAQC principles across all stages of exploration, companies can ensure more accurate resource estimations, reduce risks, and improve the efficiency and success of their mining operations. #QAQC #MineralExploration #Geology #GeochemicalAnalysis #GeologicalLogging #ResourceEstimation #GeologicalData

Blend and Content Uniformity Decision by Stratified Sampling This flowchart outlines a systematic process using stratified sampling to evaluate blend uniformity (BU) and content uniformity (CU), ensuring compliance with USP <905>. 1. Blend Sampling Objective: Verify uniformity of the blend before further processing. Procedure: Collect 3 replicate samples from at least 10 locations in the blender or drum. Assay 1 sample per location initially. 2. Blend Uniformity – Stage 1 Acceptance Criteria: SD ≤ 3.0%: Blend uniformity is acceptable. SD > 3.0%: Proceed to Stage 2 for further sampling and testing. 3. Blend Uniformity – Stage 2 Further Testing: Assay additional replicates from each location. Acceptance Ranges: SD ≤ 3.0%: Acceptable. 3.1% ≤ SD ≤ 5.0%: Acceptable with caution. SD > 5.0%: Uniformity fails; conduct a root cause analysis (RCA). 4. Dosage Unit Sampling Procedure: Collect 3 samples from at least 40 locations across the batch. Assay 3 dosage units from at least 20 locations. 5. Content Uniformity – Stage 1 Acceptance Criteria: Individual values within 75.0–125.0% of target potency. Passes statistical tests per USP <905>. Pass: Acceptable uniformity. Fail: Proceed to Stage 2. 6. Content Uniformity – Stage 2 Further Sampling: Assay units from the remaining 20 locations. Acceptance Criteria: Same as Stage 1. Pass: Batch passes. Fail: Batch is non-uniform. Final Decision 1. Acceptable Uniformity: If all criteria are met. 2. Non-Uniformity: If any criteria fail, the batch is rejected, and RCA is required. Purpose and Benefits Ensures representative sampling and accurate evaluation of BU and CU. Identifies variability and ensures compliance with regulatory standards for product quality and safety.

Quality Assurance (QA) and Quality Control (QC) are critical components of any mineral exploration project to ensure the reliability and accuracy of the data collected, which ultimately affects the interpretation and decision-making processes. Here's a breakdown of how QA and QC are typically applied in mineral exploration: #Quality #Assurance (QA) QA is the overarching process that ensures that all procedures and practices in the exploration project are carried out systematically and meet predetermined standards. It includes: 1. #Standard #Operating #Procedures (SOPs): Establishing and following SOPs for sampling, sample handling, logging, and assaying to minimize errors and biases. 2. #Training: Ensuring all team members are properly trained and competent in their roles to maintain consistency in data collection and processing. 3. #Documentation: Keeping detailed records of procedures, equipment calibration, and maintenance logs to ensure traceability and transparency. 4. #Sample #Security: Implementing measures to protect the integrity of samples, such as proper labeling, secure storage, and chain-of-custody protocols. 5. #Audits: Regular internal and external audits to verify that QA protocols are being followed and to identify areas for improvement. #Quality #Control (QC) QC involves the specific measures taken to monitor and verify the accuracy and precision of data collected during the exploration process. It includes: 1. #Blanks: Using blank samples to detect contamination during sample preparation and analysis. This is something you're already familiar with and use to quickly identify contamination issues. 2. #Standards (Certified Reference Materials): Inserting standards into the sample stream to assess the accuracy of the analytical methods and to detect any systematic errors. 3. #Duplicates: Analyzing duplicate samples to check the precision of sampling and analytical processes. This can include field duplicates, coarse duplicates, and pulp duplicates. 4. #Control #Charts: Plotting results of standards and blanks on control charts to visually monitor data quality over time and quickly identify any deviations or trends. 5. #Data #Verification: Regularly reviewing and verifying data for any inconsistencies, outliers, or errors. This can include re-assaying or re-sampling in case of suspicious results. 6. #Cross-Lab #Checks: Sending a subset of samples to a secondary laboratory to verify the results from the primary lab, ensuring that the data is consistent and reliable. #Application #in #Exploration** - #Geochemical #Sampling: Implementing QC procedures in soil, rock, and stream sediment sampling to ensure representativeness and reliability of the geochemical data. - #Drilling #Programs: Incorporating QA/QC in core logging, sample splitting, and assaying to maintain the integrity of the geological data. - #Resource #Estimation: Using variograms and other geostatistical tools to evaluate the spatial variability. https://t.me/OreZone