How to Read Assay Results

An assay result is a grade measurement — a number expressing the concentration of a target metal in a rock sample — linked to a specific depth interval in a specific drill hole. Reading assay results means understanding that number in context: which unit it is expressed in, what interval it covers, how it was composited from individual sample submissions, whether the width reported is the true thickness of mineralisation, and whether the QAQC data confirms the numbers are trustworthy.

This article covers the full journey from the raw laboratory return file on your desk to a correctly interpreted drill intercept. If you have not yet read How Assays Work: Fire Assay, ICP, XRF & Screen Fire, start there — this article assumes you understand where the numbers come from before explaining how to work with them.

What does a laboratory return file actually look like?

The laboratory returns your assay data as a spreadsheet or CSV — sometimes called a certificate of analysis or a results file. Every row is one sample. The columns vary by laboratory and analytical package, but the core columns you will always see are:

The first task after receiving a results file is to match every sample number to the corresponding interval in your field sampling record, linking each assay back to its hole ID, from-depth, and to-depth. In a spreadsheet workflow this means a VLOOKUP or index-match. In a geological database it happens automatically. Without this linkage, the grade number is an orphan — it tells you nothing about where in the ground the mineralisation sits.

Understanding the units: g/t, ppm, ppb, and percent

Assay results are expressed in a small number of concentration units, and it is easy to mix them up or misread a result that changes units between elements or between reporting periods.

Parts per million (ppm) is the standard unit for gold in most exploration programs. One ppm means one gram of gold per one million grams of rock — which is equivalent to one gram per tonne (g/t). These two expressions mean exactly the same thing and are used interchangeably.

Parts per billion (ppb) is used where gold concentrations are very low — background soil samples, anomalous but sub-economic intercepts, or programs in low-sulphidation epithermal systems where grades in the range of 20–200 ppb can still be meaningful pathfinders. The conversion is straightforward: 1 ppm = 1,000 ppb, or 1 g/t = 1,000 ppb.

Percent (%) is the standard unit for base metals — copper, zinc, lead, nickel. One percent means ten kilograms of metal per tonne of rock, or 10,000 ppm. A copper result of 1.5% is the same as 15,000 ppm Cu. When you see base metal results reported in ppm it is usually because the concentration is low (say, an anomalous soil result of 200 ppm Cu, rather than 0.02%) or because the laboratory returned a multi-element ICP table in a single unit for readability.

A quick reference table:

If you are reviewing a multi-element table and the copper column reads 15,000, check whether the header says ppm or percent — the difference is a factor of 100 in the grade of the discovery.

Detection limits and overlimit results: what the < and > symbols mean

Below detection limit (<)

When a result is reported as ”< 0.001 ppm Au”, the laboratory is telling you the gold concentration in that sample is below 0.001 ppm — below the lowest concentration the method can reliably distinguish from noise. This does not mean zero gold. It means the gold is present at a level that is undetectable by the specific method used.

How you handle below-detection results matters in resource estimation. Substituting zero for all below-detection values systematically underestimates grade and can affect the shape of the grade distribution. Common approaches include substituting half the detection limit (0.5 × LDL) or the detection limit itself for below-detection values, documented in the resource’s analytical notes.

When reviewing your results for a drill program, a zone where many samples return < 0.001 ppm Au and then a cluster return 0.1–2.0 ppm is meaningful — the contrast itself is a targeting signal. A program where almost everything is at or near the detection limit may need a more sensitive analytical method.

Over detection limit (>)

When a result is reported as ”> 10,000 ppm Cu”, the sample has exceeded the upper calibration range of the instrument. The number reported is not the true grade — it is a flag. The standard protocol is for the laboratory to re-run the sample at a higher dilution using an appropriate method. Do not use an overlimit result in any grade calculation or resource estimate until the re-assay result is returned.

In a gold program, overlimit results on fire assay (typically > 100 g/t Au) trigger a re-run at higher charge weight or using a gravimetric finish. These results are often in or adjacent to high-grade ore zones, so the delay in receiving the re-assay is operationally important. Flag these samples in your database immediately.

From raw samples to a reported intercept: compositing explained

The laboratory return file contains one row per sample — typically one metre to two metres long for drill core. But the intercept reported in a press release or technical report — “12.4 m at 3.2 g/t Au from 85 m in hole XYZ-001” — is a composite of multiple consecutive samples. Understanding how the composite is calculated is essential to evaluating whether the reported intercept is real and fairly stated.

The weighted average

The grade of a composite intercept is the length-weighted average of the individual sample grades that fall within it. If three consecutive samples in a hole return the following:

The composite grade for the 85.0–90.0 m interval (5.0 m total) is:

[(1.5 × 1.4) + (2.0 × 5.2) + (1.5 × 2.8)] ÷ 5.0 = [2.1 + 10.4 + 4.2] ÷ 5.0 = 16.7 ÷ 5.0 = 3.34 g/t Au

The 5.0 m interval at 3.3 g/t is a length-weighted average that correctly gives more weight to the two-metre sample (which had the highest grade) than to the flanking 1.5 m samples.

Cut-off grade

Before you can define where the composite starts and ends, you need a cut-off grade — a minimum grade below which material is treated as waste for the purposes of the intercept calculation. The cut-off grade is typically an economic threshold: the minimum grade at which the ore could theoretically be mined profitably under assumed metal prices and cost structures. For a gold project it might be 0.3 g/t; for a copper project it might be 0.2% Cu.

Applying a cut-off of 0.3 g/t Au to a downhole assay table means that any sample returning below 0.3 g/t is excluded from a mineralized interval, unless it is within an otherwise continuous zone where including it still keeps the composite grade above the cut-off. This is the basis for the “maximum internal waste” or “dilution” rules that exploration companies define in their compositing protocols.

A compositing approach that allows up to 2 m of sub-cut-off material to be included within an intercept (to avoid breaking a continuous zone into fragments) is reasonable and common. A compositing approach that allows 10 m of sub-cut-off material to be included across a 12 m intercept is grade-smearing — the reported grade and width bear little relationship to the zone that would actually be mined.

What to check when reading a reported intercept

Before accepting a drill intercept at face value, confirm:

1. Is the cut-off grade stated? An intercept without a stated cut-off cannot be evaluated.
2. Is the maximum internal dilution stated? Without this you cannot tell if the intercept is a continuous mineralised zone or a series of narrow zones bridged by waste.
3. Are the individual sample assays available? Technical reports (JORC, NI 43-101) must include the underlying sample data; press releases often don’t. Request the drill collar and assay tables if they are not included.

Downhole width versus true width: the most misread number in drill results

The interval reported in a drill intercept — the 12.4 m in “12.4 m at 3.2 g/t Au” — is the downhole length: the distance measured along the drill hole trajectory from the start to the end of the mineralised zone. This is not the same as the true thickness (also called true width) of the mineralised zone, which is its actual perpendicular thickness in the earth.

Why they differ

A drill hole enters the ground at an angle — say, 60° below horizontal, in a direction chosen to intersect the target. The mineralised zone has its own orientation: it might be steeply dipping, sub-horizontal, or anything in between. Unless the drill hole intersects the mineralised zone exactly perpendicular to its contact surfaces, the measured downhole interval overstates the true thickness.

The geometry is simple trigonometry. If a drill hole intersects a vertical vein at a shallow angle, it traverses a long distance through the vein even though the vein is thin. The same vein, intersected at 90°, gives a downhole length equal to the true thickness.

As a rough guide:

A 30-metre downhole intercept in a hole that intersects a steeply dipping vein at 30° represents approximately 15 metres of true vein thickness. The same result in a hole perpendicular to the vein represents 30 metres. These are vastly different discoveries.

How true width is calculated

The precise calculation requires knowing the orientation of the drill hole (azimuth and dip) and the orientation of the mineralised zone (strike and dip). When those are known, the true width can be calculated geometrically. Companies following JORC (2012) or NI 43-101 reporting standards are required to state whether widths are downhole or true widths, and to provide the information needed to estimate true width where it has not been calculated directly.

If a company reports a wide intercept without specifying whether it is downhole or true width, and without providing drill hole orientation data, that is a significant omission. Treat the result as uninformative on thickness until the orientation data is available.

Metal equivalents: what AuEq and CuEq mean, and when to be sceptical

In polymetallic deposits — porphyry copper-gold systems, zinc-lead-silver deposits, nickel-cobalt deposits — the reported grade often combines multiple metals into a single “equivalent” grade expressed in terms of one reference metal. The most common forms are gold equivalent (AuEq, in g/t) and copper equivalent (CuEq, in %).

How the calculation works

The formula converts each co-product metal into an equivalent quantity of the reference metal using the ratio of their metal prices. A simplified example for a copper-gold system:

AuEq (g/t) = Au (g/t) + [Cu (%) × Cu price per tonne ÷ Au price per troy oz × conversion factor × recovery ratio]

More specifically: if gold is US$3,000/oz and copper is US$9,000/tonne, and gold recovery is 90% and copper recovery is 85%, a sample with 1.5 g/t Au and 0.3% Cu would have an AuEq calculated from the economic value each metal contributes relative to gold.

The exact formula varies by company and must be disclosed. Any technical report or press release that uses a metal equivalent is required to state the metal prices, recovery rates, and payability assumptions used in the calculation.

Why to be sceptical of equivalents

Metal equivalent grades can legitimately simplify the description of a polymetallic deposit by summarising the combined value in a single number. They can also be used to inflate apparent grade by including metals that are present but may not be recoverable or economic. Key questions to ask:

• Are the metal prices current? If gold was US$1,800/oz when the equivalent was calculated and is now US$3,000/oz, all the gold-equivalent grades are understated — or vice versa.
• Are the recoveries realistic? Using 100% recovery for a metal that realistically recovers at 60% significantly overstates the equivalent grade.
• Is each co-product actually extractable from this ore type? Some deposit geometries concentrate metals in separate domains; a “gold equivalent” that assumes co-recovery of silver, copper, and gold from a single circuit may not reflect what the process plant can actually do.

As a general rule: if a deposit is being described primarily through a metal equivalent rather than its individual metal grades, ask for the underlying data to evaluate the contribution of each metal separately.

Reading your QAQC data: what blanks, standards, and duplicates are telling you

Every batch of samples you submit to the laboratory includes a set of quality control samples inserted into the submission sequence. When the assay certificate comes back, the QAQC results are included alongside the geological samples. Reading them tells you whether the analytical data from that batch is trustworthy.

Standards (certified reference materials, CRMs)

A standard is a sample of known composition — certified by a geochemical laboratory or a standards supplier. Your standard should return a result within an acceptable range of its certified value, typically ± 2 standard deviations (SD) of the certified mean for acceptance, and flagged as a failure at > 3 SD.

A standard that consistently returns below its certified value suggests the laboratory is under-digesting or under-recovering the metal — your sample grades may be systematically underestimated. One that consistently returns above its certified value suggests contamination in the prep or analytical step.

Use two CRMs at different grade levels: one near background and one near expected ore grade. A CRM that passes near-background but fails at ore grade (or vice versa) points to a matrix or grade-dependent issue rather than a random error.

Blanks

A blank is a sample known to contain negligible concentrations of the elements of interest — typically a clean quartz sand or a commercially sourced low-grade rock with certified near-zero metal content. Blanks check for carry-over contamination: if the sample ahead of the blank in the prep sequence was high-grade, and the blank returns elevated values, the laboratory’s crushing and pulverising equipment is not being cleaned adequately between samples.

The acceptable failure threshold for blanks is typically: no more than 10% of blanks exceeding 5 times the lower detection limit, or alternatively, no blank exceeding 3 SD above the blank’s certified background value. A batch where multiple blanks fail after high-grade samples is a serious red flag — the assay data from that batch may need to be re-submitted.

Duplicates

Field duplicates are collected by splitting the same core interval into two portions and submitting both independently. They measure the combined variability of sampling and laboratory analysis.

The standard measure of precision for duplicates is the coefficient of variation (CV): the standard deviation of the pair divided by the mean, expressed as a percentage. Acceptable precision in most exploration programs is a CV below 15–20% for mineralised intervals. High CVs in mineralised zones (> 30%) indicate that the gold or metal of interest is unevenly distributed within the sample — a nugget effect problem that may require protocol changes (larger sample mass, screen fire assay) rather than just a laboratory re-run.

A quick summary of what each QAQC sample type catches:

Putting it all together: reading a drill intercept announcement

When you see an intercept like “HOLE XYZ-007: 18.0 m at 4.1 g/t Au from 112 m, including 4.0 m at 12.5 g/t Au from 122 m”, here is what a rigorous reading looks like:

1. Is the 18.0 m downhole or true width? Check the note at the bottom of the table. If true width is not stated, check whether the drill orientation and zone orientation data allow you to estimate it. A narrow steeply-dipping vein drilled at a shallow angle could turn a 18 m downhole intercept into 6–7 m true width.

2. What cut-off grade was used? A 0.3 g/t cut-off and a 1.0 g/t cut-off on the same hole can produce significantly different reported intervals. Confirm the cut-off is stated and consistent with the deposit’s expected economics.

3. What is the “including” telling you? The 4.0 m at 12.5 g/t sub-interval means most of the grade in the 18 m intercept is concentrated in a 4 m window. The outer 14 m averages approximately 1.0 g/t (back-calculated). That context matters for understanding the mineralisation style.

4. What depth is the intercept at? 112 m vertical depth is open-pittable at many projects; 500 m is underground territory. Depth profoundly affects project economics even if the grade-width numbers look identical.

5. Did the QAQC pass? If the announcement does not mention QAQC, check the NI 43-101 or JORC technical report that should accompany any material drill result. Passing QAQC is not optional — it is the evidence that the grade number is real.

6. Is there a metal equivalent in the headline number? If the 4.1 g/t is AuEq rather than Au, read the footnote for the metal prices, recoveries, and constituent metals used to derive it.

FAQ

What is the difference between downhole length and true width, and which one matters more?

Downhole length is the distance along the drill hole trajectory that the mineralised zone was intersected. True width is the actual perpendicular thickness of the mineralised zone as it exists in the ground. True width is what matters for economic assessment — it determines how much rock will be moved per unit of deposit thickness in any mining scenario. Downhole lengths are reported because they are what is actually measured; true width requires knowing the orientation of both the hole and the zone. Always look for the true width disclosure when evaluating an intercept.

What does it mean when an assay returns a detection limit result below a high-grade zone?

A below-detection result immediately above or below a high-grade intercept is normal and expected — grade usually transitions from background into anomaly over some distance. What to watch for is a zone where drill-hole-to-drill-hole correlation shows consistently below-detection samples in areas where you expect mineralisation based on the geology. That can indicate a lateral or vertical change in the system, or it can indicate a sampling or analytical issue. Compare the assay data against the geological log for that interval.

How many standard and blank samples should I include per batch?

Industry standard is one CRM (standard), one blank, and one field duplicate per 20–40 samples submitted, giving a QAQC sample insertion rate of 5–15%. For high-grade zones or programs close to a resource estimate, increase the frequency to one-in-20. Insert blanks immediately after any sample from a visually mineralised interval to catch carry-over contamination at the points of highest risk.

Can I calculate true width myself from the press release data?

Sometimes. If the company discloses the drill hole dip (e.g., -60°), the azimuth, and the estimated dip and strike of the mineralised zone, you can calculate an approximate true width using the appropriate geometric formula. Many exploration software packages (and some online calculators) can perform this calculation. If the company does not disclose the drill orientation data, you cannot calculate true width — and the absence of that disclosure is itself informative.

Why do some intercepts show very different grades when reported by different analysts?

Different cut-off grades and different dilution allowances applied to the same raw data will produce different composited intercepts. A 0.5 g/t cut-off will narrow and raise the apparent grade of an intercept relative to a 0.1 g/t cut-off on the same hole. Neither is necessarily wrong — the choice of cut-off should reflect the deposit economics — but inconsistency between companies or between reporting periods for the same project makes comparison difficult. Always compare intercepts at the same cut-off.

How Blue Butterfly connects raw assay data to drill intercepts

In most exploration programs, the journey from laboratory return file to a composited, QAQC-checked drill intercept involves multiple spreadsheets, manual copy-paste, and VLOOKUP chains across separate tabs. Each step is a potential source of error: a transposed sample number, an over-copied formula, a QAQC failure that is missed because no one is systematically checking the standard results column.

Blue Butterfly imports the laboratory return file — CSV, Excel, or direct lab API — and automatically links each result to the sampling interval already recorded in the database, matched by hole ID, from-depth, to-depth, and sample number. QAQC samples (standards, blanks, duplicates) are flagged automatically against their expected values the moment the file arrives, so failures are visible before the data enters any intercept calculation or geological interpretation.

The chain from geological log → sampling record → laboratory dispatch → validated assay result is intact and auditable in a single system — no intermediate spreadsheets, no manual matching step, no version confusion.

See how Blue Butterfly manages assay data import and QAQC →

Sources

• Next Investors — How to Read Assays and Drilling Results for Beginners (key components: grade, width, hole ID; cut-off grade; grade-thickness metric; depth context): https://nextinvestors.com/learn-to-invest/mining/how-to-read-assays-and-drilling-results-for-beginners/
• Discovery Alert — Decoding Drill Results: A Guide to Mineral Exploration Analysis (true width vs. apparent width; angle distortion at 45°, 30°, 10°; how to evaluate drill results): https://discoveryalert.com.au/mineral-exploration-drill-results-interpretation-2025/
• Small Cap Investor — How to Read and Interpret Drill Results (downhole vs. true width; reporting red flags; intercept evaluation checklist): https://smallcapinvestor.ca/the-truth-machine-how-to-read-and-interpret-drill-results/
• Mining Maven — A Beginner’s Guide to Understanding Assay Results (cut-off grade definition; compositing explained; grade averaging): https://miningmaven.com/blog/777-a-beginner-s-guide-to-understanding-assay-results-by-david-price-ceo-of-rockfire-resources-2
• Mining.com.au — How drill results are reported and interpreted (reporting conventions; intercept structure; JORC context): https://mining.com.au/how-drill-results-are-reported-and-interpreted/
• Resource World Magazine — Making the grade: understanding exploration results (grade-thickness calculation; unit explanations; depth significance): https://resourceworld.com/making-grade-understanding-exploration-results/
• American Eagle Gold — Copper Equivalent Calculation (CuEq formula; metal prices and recovery rates in equivalent calculation): https://americaneaglegold.ca/projects/nak-property-1/copper-equivalent-calculation/
• Geology for Investors — Metal Equivalent Calculator (AuEq and CuEq concepts; formula structure; limitations of equivalents): https://www.geologyforinvestors.com/simple-metal-equivalent-calculator-for-mining-results/
• CSA Global / Gerry Fahey — The Use and Abuse of Metal Equivalents (sceptical framework for reading equivalents; recovery and price assumptions): https://www.csaglobal.com/wp-content/uploads/2019/11/The-Use-and-Abuse-of-Metal-Equivalents_Gerry-Fahey_November_2019.pdf
• Seequent (Leapfrog) — Compositing numeric and assay data in Leapfrog Geo (length-weighted average compositing; composite interval definition; Leapfrog compositing workflow): https://www.seequent.com/compositing-numeric-and-assay-data-in-leapfrog-geo/
• Datamine Software Docs — Create a Drillhole Composite by Cut-off Grade (cut-off grade compositing; dilution rules; waste inclusion parameters): https://docs.dataminesoftware.com/Discover/ArcGISPro/Latest/Drillhole-Data-Management/Create-a-Drillhole-Composite-by-Cut-off-Grade.htm
• Merit Laboratories — A Closer Look at the QA/QC Samples That Ensure Data Quality (QAQC sample types; blank and standard acceptance criteria; duplicate precision targets): https://www.meritlabs.com/blog/2025/11/6/a-closer-look-at-the-qaqc-samples-that-ensure-data-quality
• LinkedIn / Owen Greenberger — Basic Introduction to QAQC (insertion rates; standards, blanks, duplicates explained; CV calculation): https://www.linkedin.com/pulse/basic-introduction-qaqc-owen-greenberger
• USGS Open-File Report 2011-1187 — Quality Assurance and Quality Control of Geochemical Data (detection limits; below-detection handling; QAQC procedures for exploration geochemistry): https://pubs.usgs.gov/of/2011/1187/pdf/ofr2011-1187.pdf
• Lyell Collection / Geochemistry: Exploration, Environment, Analysis — Practical applications of QAQC in mineral exploration, resource estimation and mining programmes (comprehensive review of international QAQC best practices; standard deviation thresholds; precision and accuracy monitoring): https://www.lyellcollection.org/doi/full/10.1144/geochem2023-046
• ResearchGate — Quality Control of Assay Data: A Review of Procedures for Measuring and Monitoring Precision and Accuracy (CV thresholds; duplicate variability; failure criteria for CRMs and blanks): https://www.researchgate.net/publication/250084048_Quality_Control_of_Assay_Data_A_Review_of_Procedures_for_Measuring_and_Monitoring_Precision_and_Accuracy