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Orelysis Geosciences

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Orelysis Geosciences

We deliver independent high value geologic sample preparation services

We deliver independent high value geologic sample preparation services
Orelysis offers a range of geochemical sample preparation and testing services

11/08/2026

Resource Estimates Depend on Traceable Data: What JORC, NI 43-101 Reviewers Ask For.

Metrological traceability is a fundamental requirement of ISO/IEC 17025:2017, Clause 6.6. It mandates that every measurement result be demonstrably linked to a reference, ultimately to the International System of Units (SI), through an unbroken chain of calibrations, each supported by a stated measurement uncertainty.

In geochemical analysis, traceability is maintained through a structured calibration hierarchy:

- Primary Reference Standards: Certified by recognized Metrology bodies, such as NIST with concentrations directly traceable to the SI.
- Secondary Calibration Solutions: Prepared from primary standards by accredited producers, accompanied by documented uncertainty and a formal traceability certificate.
- Working Standards: Laboratory-prepared dilutions of secondary standards, with all dilution calculations and preparation records fully documented.
- Instrument Calibration: Performed for each analytical batch using working standards. Acceptance is contingent on all calibration points meeting the predefined linearity criteria.

Any disruption to this chain, including the procurement of standards from non-accredited suppliers, use of expired reference materials, or inadequate documentation of dilution procedures, constitutes a traceability gap. Under such circumstances, reported results cannot be considered metrologically traceable.

For exploration and mining companies, the traceability of analytical data supporting resource estimates is a critical component of due diligence. Third-party reviewers and Competent Persons operating under JORC or NI 43-101 frameworks increasingly require verifiable evidence of analytical traceability, beyond the certificate of analysis.

Orelysis provides technical due diligence support to exploration and mining laboratories to ensure compliance with traceability requirements.
Connect with our team of experts at www.orelysis.com

28/07/2026

A perfect Internal Audit is a warning sign.

Most labs treat internal audits as a compliance checkbox.
Top-performing labs treat them as risk-management tools.

Clause 8.7 of ISO/IEC 17025 requires planned internal audits at defined intervals to verify that the laboratory's management system and operations continue to meet requirements. "Planned" is key — it’s not reactive.

So, competent auditors and external assessors usually examine?

1. Technical Records.
Raw data, instrument outputs, calculation worksheets. Are they complete, traceable, and unaltered?

2. Equipment & Calibration.
Are intervals defined, documented, and followed? Are out-of-tolerance instruments properly documented and quarantined?

3. Personnel Competence.
Is there evidence of training, qualifications, and current authorisation for critical tasks?

4. Nonconformity Management.
Are NCs raised, root cause investigated, and corrective actions verified for effectiveness?

5. Method Currency.
Are procedures current? Are any unauthorised deviations happening?

6. Subcontracting.
If work is subcontracted, is the provider’s competence verified and documented?

Important note: Internal audits should produce findings.
A "perfect" audit history with zero NCs isn’t a win. To external assessors, it’s a risk signal. It usually means the audit was superficial.

At Orelysis, we help laboratories move from checkbox audits to audits that actually reduce risk and prepare for assessment.

For technical
questions or further discussions on geoscience applications, Orelysis' expert team at Orelysis.com is available for consultation.

21/07/2026

Method Validation vs Method Verification: A Critical Distinction
ISO/IEC 17025:2017 distinguishes between method validation and method verification, and the distinction determines how much experimental work a laboratory must do before using a method.

Method validation:
– Required when a laboratory develops a new method or significantly modifies a standard method.

– Full validation involves: establishing working range, linearity, detection limits, precision (repeatability + reproducibility), accuracy (bias vs CRM), matrix effects, and ruggedness.

– Result: a documented validation report with performance characteristics for defined matrices and concentration ranges.

Method verification:
– Required when a laboratory adopts an externally published standard method (ISO, ASTM, AOAC, etc.) without modification.

– Verifies that the laboratory can achieve the performance parameters claimed in the standard under its own conditions.

– Typically involves: CRM analysis to confirm accuracy, replicate analysis to confirm precision, and demonstration that DL meets the standard's specification.

– Scope is narrower than full validation — it confirms fitness for purpose, not full characterisation.

A common error is laboratories treating verification as optional when adopting a published method. ISO 17025 clause 7.2.2 is explicit — verification is mandatory. Accreditation bodies will audit for verification records.

Both processes must be documented, reviewed, and updated when conditions change — such as a new instrument, a new reagent lot, a new operator, or a new matrix type.

For technical
questions or further discussions on geoscience applications, Orelysis' expert team at Orelysis.com is available for consultation.

14/07/2026

A result without uncertainty is an incomplete result.

ISO/IEC 17025:2017 requires accredited laboratories to report measurement uncertainty for all analytical results. In geochemical practice, however, uncertainty is seldom included on Certificates of Analysis and is frequently not calculated.

A result reported without measurement uncertainty is considered technically incomplete and non- compliant under ISO/IEC 17025.

Measurement uncertainty expresses the range of values reasonably attributable to a result. It incorporates, but is not limited to, calibration uncertainty, method precision, matrix effects, CRM bias, and sample heterogeneity

For resource reporting, analytical uncertainty is a direct input to resource classification confidence. The absence of documented uncertainty introduces material risk to technical reporting and regulatory compliance.

30/06/2026

Are Your Geochemical Duplicates Masking QAQC Issues? Two Plots to Reveal Precision Problems

Average relative difference alone won’t tell you if your duplicate data are fit-for-purpose. For a structured assessment, use two complementary tools: the Thompson-Howarth plot and Half Absolute Relative Difference.

The Thompson-Howarth plot shows the mean vs. absolute difference for each pair, revealing the expected heteroscedastic pattern in geochemical data. Outliers above a 2× median HARD envelope flag problematic pairs, while a shift in scatter can indicate a detection limit or preparation heterogeneity issue. HARD, calculated as $|A - B| / (A + B) \times 100\%$, gives a robust, easy-to-interpret metric — a median

23/06/2026

The 3 Duplicate types every Geochemist must understand: Precision .

Duplicate analysis is the primary method for quantifying precision in geochemical programs. Precision, however, is not a single value. It comprises multiple components, each attributable to a distinct stage of the sampling and analytical sequence. Selecting the appropriate duplicate type is therefore essential for making technically sound, data-driven decisions.

Field Duplicate / Twin Sample
Independently collected from the same sampling interval or location.

Variance captured: Total variance, encompassing geological heterogeneity, sampling error, sample preparation error, and analytical error.

Key metric: Half Absolute Relative Difference (HARD%). Elevated variance at this stage typically indicates geological variability, deficiencies in sampling methodology, or both.

Preparation Duplicate / Coarse or Pulp Split

A subsample obtained from the same crushed or pulverised material before withdrawal of the final analytical aliquot.

Variance captured: Sample preparation error and analytical error only. Geological and sampling variance are excluded.

Application: Comparison with field duplicate results isolates and quantifies the combined geological and sampling error component.

Analytical Duplicate / Laboratory Pulp Replicate

A second subsample was weighed from the same pulp and subjected to independent digestion and measurement.

Variance captured: Analytical precision attributable to the instrument and method only.

Identifying which variance component is dominant is critical for targeted quality improvement. When field duplicate variance is high but analytical duplicate variance is low, imprecision originates in field sampling and sample preparation rather than in laboratory analysis.

16/06/2026

Preparation Blanks vs Reagent Blanks: They Are Not the Same.

Blank materials are essential QA/QC tools for detecting contamination. However, the type of blank used determines what contamination source it monitors — and using the wrong blank type leads to gaps in the contamination detection system.

Reagent blank (method blank):
– A blank solution carried through the full digestion and analysis procedure using only reagents (no sample matrix).
– Monitors: reagent purity, labware cleanliness, and airborne contamination during digestion.
– Does not capture: contamination introduced during physical sample preparation (crushing, milling).

Preparation blank (coarse blank or pulp blank):
– A low-grade or barren rock material physically processed through the full preparation sequence alongside the samples.
– Monitors: cross-contamination from equipment surfaces, carryover from previous high-grade samples, and dust contamination in the preparation environment.
– This is the critical blank type for geochemical sample preparation.

The classic carryover scenario: a high-grade gold sample is crushed and pulverised on a jaw crusher and ring mill. Residual gold particles remain on equipment surfaces. The next sample — even after cleaning — picks up trace contamination. A preparation blank inserted after the high-grade sample will detect this. A reagent blank will not.

Best practice: insert one preparation blank for every 20 samples, and always insert one immediately after any sample exceeding 10× the typical grade range for that project.

09/06/2026

Understanding Certified Reference Materials: Certification vs Characterisation

Not all reference materials carry the same analytical authority. The distinction between a certified reference material (CRM) and a characterised in-house standard is significant — and frequently misunderstood.

Certified Reference Material (CRM):

– Certified values are established through interlaboratory collaboration, typically involving 15–30+ independent laboratories.

– Uncertainty is expressed as a 95% confidence interval derived from statistical analysis of all participant results.

– Metrological traceability is documented — results are traceable to SI units through defined reference methods.

– Homogeneity and stability are tested and documented.

In-house control sample:

– Values are typically assigned by a single laboratory or a small set of laboratories.

– Uncertainty may not be formally quantified.

– Useful for monitoring internal consistency and precision — not for validating accuracy.

In a well-designed QA/QC program, both types are needed. CRMs anchor the accuracy of the system to an externally verified truth. In-house standards track precision and detect within-laboratory drift.

A CRM inserted at 1 per 20 samples provides ~5% coverage for accuracy monitoring. For high-value or high-risk campaigns, 1 per 10 is preferred — particularly where regulatory reporting depends on the data.

02/06/2026

Control Charts in Laboratory QA/QC: Reading the Signal Beyond the Limit

Control charts (Shewhart charts) are the standard tool for monitoring the analytical performance of certified reference materials (CRMs) over time. Most laboratories plot CRM results against the certified value and apply ±2σ warning limits and ±3σ action limits.

But passing a ±2σ threshold is not sufficient evidence of good performance. Control charts must also be interpreted for systematic patterns — the Western Electric Rules define several conditions that indicate process instability even when no individual point exceeds the action limit:

– Rule 1 (Spike): One point beyond ±3σ → investigate contamination or calibration failure.

– Rule 2 (Trend): Eight consecutive points on the same side of the mean → suggests systematic drift, reagent degradation, or instrument baseline shift.

– Rule 3 (Stratification): Fifteen consecutive points within ±1σ → may indicate data rounding or insensitive measurement.

– Rule 4 (Mixture): Eight consecutive points alternating above and below the mean → suggests two alternating analytical populations (e.g., instrument recalibrated mid-batch).

In geochemical QA/QC, drift patterns are particularly significant. A gradual upward trend in a CRM over months can indicate reagent contamination building in the preparation workflow — invisible to single-batch review but detectable in time-series charting.

Effective control chart use requires: long-term data retention, trend analysis beyond single batches, and investigation protocols triggered by pattern detection — not only limit violations.

Address

Nyang'omango
Misungwi
73

Opening Hours

Monday	08:00 - 17:00
Tuesday	08:00 - 17:00
Wednesday	08:00 - 17:00
Thursday	08:00 - 17:00
Friday	08:00 - 17:00
Saturday	09:00 - 16:30

Website

http://www.orelysis.com/

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