Articles tagged with: Resources

Grade-Tonnage Curves – Worthy of a Good Look

Date: July 16, 2023 Author: Ken Kuchling Comments: Leave a reply

Most of us have seen the typical “grade-tonnage” table or graph, showing ore tonnes and grade at varying cutoff grades. It is usually part of every 43-101 technical report in Section 14. We may glance at it quickly and then move on to more exciting chapters. Section 14 (Mineral Resources) can be a very complex chapter to read with statistics, geostatistics, and mathematical formulae. However the grade-tonnage curve aspect isn’t complicated at all.

The next time you see the grade-tonnage relationship, I suggest taking a few seconds to study it a bit further. There might be some interesting things in there.

Typical Grade-Tonnage Information

Typically, one will see grade-tonnage data in 43-101 Technical Reports towards the back of Section 14 "Mineral Resources". The information is normally presented in either of two ways; (i) a grade-tonnage table or (ii) a grade tonnage graph. Examples of each are shown below. The grade tonnage graph typically has the cutoff grade along the bottom x-axis and the two separate y-axes representing the ore tonnes above cutoff and the average ore grade above cutoff.

Rarely do you see both the table and curve in the report, although ideally one would want to see both. Given the option, I would prefer to see the graph more than the table of numbers. The trend of the grade-tonnage information is just as important as the values, maybe even a bit more important. Unfortunately, a data table by itself doesn’t illustrate trends very well.

Useful Grade-Tonnage Curve Information

When I am undertaking a due diligence review or working on a study, very early on I like to have a look at the grade-tonnage information. This could be for the entire deposit resource, within a resource constraining shell, or in the pit design.

The grade-tonnage information gives an understanding of how future economics or technical issues may impact on the mineable tonnage.

An example of a typical grade-tonnage curve is shown here.

The cutoff grade along the x-axis will be impacted by changes in metal price or operating cost. The cutoff grade will increase if metal prices decrease or if operating costs increase.

The question is how sensitive is the mineable tonnage to these economic factors. The slope of the tonnage and grade curves will help answer this question.

In the example shown, the tonnage curve (blue dots) is fairly linear, meaning the ore tonnage steadily decreases with increasing cut-off grade. That is expected and is reasonable.

However, if the tonnage curve profile resembled the light blue line in this image, with a concave shape, the ore tonnage is decreasing rapidly with increasing cutoff grade. This is generally not a favorable situation.

It indicates that a significant portion of the tonnage has a grade close to the cutoff grade. If that’s the situation, the calculation of the cutoff and the inputs used to generate it are important and worthy of scrutiny. Are they reasonable? Over the long term, is the cutoff grade more likely to increase or decrease?

The same logic can be used with the ore grade curve in the graph. As shown in this example, the ore grade increases steadily as the cutoff is raised. This is because lower grade ore is being shifted from ore to waste, and hence the remaining ore has better quality. If the cutoff is raised from 0.4 g/t to 0.5 g/t, then some material with a grade of about 0.45 g/t is moved from ore to waste.

I also like to compare the ratio of the average grade to the cutoff grade. Its nice to see a ratio of 4:1 to 5:1 to ensure the overall average grade isn’t close to the cutoff. In this example, the cutoff grade is 0.5 g/t and the average grade is 4.5 g/t, a ratio of 9:1.

The tonnage curve and grade curve provide information on the nature of the mineral resource. Study them both.

Reporting Waste Within a Shell

One complaint I have about reporting mineral resources inside a resource constraining shell is the lack of strip ratio information. This applies whether disclosing a single mineral resource estimate or variable grade-tonnage data.

In my view, the strip ratio is even more important to be aware of when looking at grade tonnage data.

The strip ratio within a shell will climb as an increasing cutoff grade results in a decreasing ore tonnage. Sometimes the strip ratio will increase exponentially. The corresponding amount of waste remaining in that pit shell increases, hence the ratio of the two (i.e. strip ratio) can escalate rapidly.

Regarding mineral resources, one should be required to disclose the waste tonnage and strip ratio when reporting resources inside a constraining shell. The constraining shell and cutoff grade are both based on defined economic factors such as unit mining costs, processing cost, process recoveries, and metal prices. With respect to the mining cost component, the strip ratio is a key aspect of the total mining cost, yet it normally isn’t disclosed.

Its common to see mention that the mining cost is (say) $2.50/t, but if the strip ratio is 10:1, that equates to an effective mining cost of $27.50 per tonne of ore. That’s an important cost to know, especially if one is pushing a pit shell deep to maximum the mineral resource tonnage.

Each mineral deposit resource model can behave differently. Hence, in my view, the waste tonnage should be included when reporting mineral resource tonnages (or presenting grade-tonnage data) within a constraining shell. This waste tonnage or strip ratio can be in the footnotes to the mineral resource summary table.

Spider Diagram Downsides

In 43-101 technical reports, the financial Chapter 22 normally presents the project sensitivities expressed in a spider diagram or a table format.

In a previous blog post I had discussed the flaws in the spider diagram approach. That article link is at “Cashflow Sensitivity Analyses – Be Careful”. The grade-tonnage curve helps explain why that is.

In the spider diagrams, we typically see sensitivities related to +/- 20% on metal prices and operating costs. If either of these factors change, then in reality the cutoff grade would change.

If the metal price decreases by -20%, or the operating cost climbs by +20%, the cutoff grade must increase. This adjustment is normally not made in the sensitivity analysis because it requires a lot of re-work.

Elevating the cutoff grade would shift the pit ore tonnage towards the right on the grade-tonnage curve, showing a decrease in mineable tonnes. However, in the spider diagram logic, the assumption is that production schedule in the cashflow model is unchanged and simply the metal prices or operating costs are adjusted. Therefore, the spider diagram can be a misleading representation of the downside risk, showing a more positive situation than in reality.

Conclusion

The grade-tonnage information is always presented in technical reports. It examines the sensitivity of the orebody size to changes in cutoff grade. The next time you see grade-tonnage data, don’t skip over it. Take a minute to study it further to see what can be learned.

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Polymetallic Drill Results – Interesting or Not?

Date: June 30, 2023 Author: Ken Kuchling Comments: Leave a reply

A while ago I posted an article about how one can evaluate the economic potential of a gold deposit using early-stage exploration intercepts. That article can be found at this link. Doing the same evaluation for a polymetallic deposit is a bit more challenging. There will be different metals of interest, with variable grades, prices, and process recoveries.

When disclosing polymetallic drill results, many companies will convert the multiple metal grades into a single equivalent grade. I am not a big proponent of that approach.

I prefer using the rock value, whether calculated as a recoverable “NSR dollar value per tonne” or as an “insitu value per tonne”. Either rock value is fine for my purposes.

Interestingly NI 43-101 prohibits the disclosure of insitu rock value but allows the use of metal-equivalents. In my view this is a bit counter-intuitive since the equivalent grade can be more misleading than rock value.

What can drill intercepts show

The three aspects that interest me the most when looking at early-stage drill results are:

The economic value of the rock (in $/t tonne). This can either be “insitu value” (assuming 100% recovery, 100% payable) or the “NSR value” incorporating recovery and payable factors (if available). Personally, the 100% insitu value is simpler to calculate and assess.
The depth to the top of the economic zone, which indicates if this deposit would be a lower cost open pit mine or must be a higher cost underground mine.
The length of the economic intervals, which indicates whether bulk mining approaches are viable versus the need to selectively mine narrow ore zones. The economic interval lengths also give a sense for the potential tonnage size (i.e. is it a big deposit or a small one).

There are two types of early-stage exploration data that can be examined with respect to the three items of interest described above. They are (i) the drill hole assay data and (ii) the drill hole "intercepts of interest". I will show an example of each in this post using sample data from an actual exploration program.

One can examine individual drill hole assays to calculate the rock value profile along each drill hole. One can also examine the rock values for the major and minor intervals of interest reported in company news releases.

I normally like to examine both, but the intervals of interest data is publicly disclosed and more readily available. Drill hole assays are often a bit harder, if not impossible, to track down.

Economic Parameters

In a polymetallic deposit, the insitu rock value is simply the summation of value of the individual metal, based on their respective assay grades. An NSR rock value would apply an adjustment for metal recoveries and smelter payables, thereby lowering the insitu rock value somewhat. However the insitu value is fine if there is no metallurgical or process data to rely upon.

Next one must determine what insitu rock value is deemed potentially economic, i.e. the breakeven cutoff.

One can estimate a processing cost and G&A cost. In an open pit scenario, one doesn’t include the mining cost since the goal is to decide whether to send a truck to the waste dump or to the crusher. Only the processing and G&A cost musts be recovered by the ore value. In an underground mining scenario, one would include the mining cost in the cutoff calculation.

In our example, lets assume a unit processing cost of $12/t and a G&A cost of $$2/t, for a combined cost of $14/t. If we envision a metal recovery range of 75%-95%, we can assume 85% for now.

If we envision a smelter payable range of 75% to 95%, we will assume 85% for that also.

The “NSR factor” would now be 85% x 85% or 75%. Therefore, if the breakeven cost is $14/t, then one should target to mine rock with an insitu value greater than $20/tonne (i.e. $14 / 0.75). This would be the approximate ore vs waste cutoff. It is still only ballpark estimate at this early stage, but good enough for this type of review.

Normally it would be nice to see the average head grade (or rock value) at 3 to 4 times greater than the cutoff grade. This is not a necessity but it is a positive factor.

For example, in a gold deposit with a 0.3 g/t cutoff, one would like to see average head grades at least 0.9 to 1.2 g/t or more. If the average head grade is close to the cutoff grade, then possibly the orebody tonnage may be very sensitive to changes in cutoff. This may not be a good thing.

In our example, with a breakeven cutoff rock value of $20/t, one would like to see some ore zones with insitu values 3-4x higher, or above $60 - $80/t. We can target >$70/t rock as a "nice to have" with $20/t as the cutoff.

So far, its all pretty simple. Let’s look at some actual exploration data to see how to apply this approach.

Our example will be a polymetallic deposit containing four metals of interest; copper, gold, cobalt, and iron. One can examine a few drill holes as well as the intervals of interest.

Metal prices used in this example are Cu = $4/lb, Au = $1980/oz, Co = $15.50/lb, Fe concentrate = $100/tonne, assuming 100% recovery and 100% payable for everything.

Drill Hole Assays Examples

The following three graphs show down hole profiles for Drill Holes A, B, C. For each hole there are two plots. One plot shows the insitu rock values down the hole. The second plot is the same, except the x-axis minimum has been set to the breakeven cutoff value of $20/t. This is done simply to highlight the potentially economic zones.

Normally I would not spend a lot of time examining holes with little to no grade. Some may consider this as a biased view. However, every orebody has its limits, and what is occurring along the edges isn’t that critical in my view.

My objective is to understand what is happening in the core of the orebody, since that is what will dictate the overall economics. Is the core of the orebody marginal value, or does it consist of high value rock? Ultimately it will be the exploration company's task to keep drilling to define if there is sufficient tonnage of this higher value rock to justify a mine. However this shows that at least the grades are there.

Intervals of Interest Example

The next series of plots examines the insitu rock values over drill intervals typically published in a company news releases. The intervals of interest will composite the individual assays over larger widths based on the company’s technical judgement.

It is interesting to see whether the larger intervals have good economic potential. The following charts combine both major intervals with minor zones, often referred to as “including” in news releases. Both major and minor intervals can provide useful information.

Insitu Rock Value vs Depth:

This chart shows the rock values for multiple report intervals versus their depth (top) along the hole.

One can see multiple intervals at open pit depths (<250 m) with insitu values above the $20/t cutoff and above the $70/t threshold.

Within the upper 250 metres, we are seeing multiple intervals with good value. That is a positive sign.

Note that these depths are not depths from surface, but distance along the drill hole. In reality the intervals may be slightly closer to surface, depending on the hole inclination.

Insitu Rock Value vs Interval Length:

The next question to ask is whether the higher value zones are narrow or wide?

In the example here one can see some wide zones (70 to 90m) with rock values in the range of $40-70/t. These are good open pit mining widths.

There are numerous higher grade zones ($70-$200/t) in the 5m to 20m width range. These widths are still fine for open pit mining.

Some intervals are quite narrow (<5m), being a bit more difficult to mine. Since many of these are higher grade, they will tolerate some mining dilution.

Conclusion

Although publishing insitu rock values is prohibited by NI-43-101, I find them important in my understanding the economic potential of a deposit. Reviewing the insitu rock values spatially is not difficult and can shed light on what is there. Even at a very early stage, one can get a sense of economic character of the orebody. This is a great approach to use when doing an acquisition due diligence on an exploration stage project consisting mainly of drill hole data.

In my view, it would be beneficial if all polymetallic drill results were reported with the individual grades and using a standardized industry wide insitu rock value formula. Then one could compare projects (or even different zones on the same project) on an equal basis. The cutoff to be applied to different projects would vary but the insitu value is what it is.

This might be better than each company applying their own unique equivalent grade calculation to their exploration results.

The equivalent grade calculation still requires assumptions on the metal prices and recoveries. The result is, unfortunately, presented as a grade value rather than a dollar value.

The intervals of interest published in news releases are usually not available for download. Great Bear is (was) one example where the data was available. It would be nice if more companies followed suit by releasing their interval data in CSV or Excel format. It worked out well for Great Bear!

Perhaps the detailed hole assay data may be too complex or voluminous to release. Maybe this level of information is not useful except to the more technically driven investors. Nevertheless it would still be nice to have access to this drill data in electronic form, at least in the core of the orebody.

For further light reading, the two previous articles referenced above are “Gold Exploration Intercepts – Interesting or Not?" and "Metal Equivalent Grade versus NSR for multi-metals – Preference?"

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Gold Exploration Intercepts – Interesting or Not?

Date: July 7, 2021 Author: Ken Kuchling Comments: Leave a reply

As a mining engineer, I am not usually called in to review a project that is still at the exploration stage. This is normally the domain of the geologist. However from time to time I have an interest in better understanding the potential of an early stage mining project. This could be on behalf of a client, for investing purposes, or just for personal curiosity.

At the exploration stage one only has drill interval data from news releases to examine. A resource estimate may still be unavailable.

The drill data can consist of long intervals of low grade or short intervals of high grade and everything in between. What does it all mean and what can it tell you?

The following describes an approach I use for examining early stage gold deposits. The logic can be expanded to other metals but would take more effort.

My focus is on gold because it has been the predominant deposit of interest over the last few years, and it is simpler to analyze quickly.

We All Like Scatter Plots

My approach relies on a scatter plot to visual examine the distribution of interval thicknesses and gold grades. Where these data points cluster or how they are distributed can provide some prediction on the overall economic potential of a project. Its not a guarantee, but only an indicator.

I try to group the analysis into potential open pit intervals (0 to 200 metres from surface) and potential underground (deeper than 200m) intervals. This is because a 20m wide interval grading 2.0 g/t is of economic interest when near surface, however of less interest if occurring at a 300m depth.

Using information from a news release, I create a two column Excel table of highlighted intervals and assay grades. The nice thing about using intervals is that the company has provided their view of the mineable widths.

If one is provided with raw 1-metre assay data you would have to make that decision, which can be a significant task. The company has already helped make those decisions.

Normally I tend to use the highlighted sub-intervals and not the main intervals since issues with grade smoothing can occur.

A large interval containing multiple high grade sub-intervals may see some grade smoothing.This happens if the grade between sub-intervals is very low grade or even waste. It takes a fair bit of effort to assess this for each drill hole, hence it is easier to work with the sub-intervals.

I have an online calculator (Drill Intercept Calculator) that lets you assess if grade smoothing is occurring.

When inputting the interval thickness, I prefer to use the true thickness and not the interval length. If the assay information does not specify true thicknesses, then I simply multiple the interval length by 0.70 to try to accommodate some possible difference in width. Its all subjective.

The assays can consist of Au (g/t) or AuEq (g/t) if more metals are present. If very high grades are encountered (greater than 10 g/t) I simply input 9.9 g/t into the Excel table so they fit onto my scatter plot. Extremely high grades can be sporadic and localized anyhow.

Finally I need to decide whether the project is located in a region of high operating cost, low cost or about average costs. High costs could be with a fly in/ fly out, camp operation, with diesel power, and seasonal access.

A low cost operation could be in temperate climate, with good access to local infrastructure, water, labour, and grid power. An average operation would be somewhere in between the two. Its just a gut feel.

Results

The following charts describe how it works, using randomly generated dummy assay data in this example.

In the Average cost scenario (left chart) the points are equally scattered both above and below the Likely Economic line. As one moves to a high-cost situation (middle chart) the curve moves upwards and more drill intervals now fall below the economic line.

This would give me an unfavorable impression of the project. The third graph is the Low-Cost scenario and one can see that more assays are now above the line. Hence the same project located in a different region would yield a different economic impression.

The economic boundaries (dashed lines) presented in the plots are based on my personal experience and biases. Other people may have different criteria to define what they would view as economic and uneconomic intervals.

Conclusion

There is not much that a layperson person can do with the multitude of exploration data provided in corporate news releases. However, by aggregating the data one can get a sense of where a gold project positions itself economically. The more data points available, the more that one can gather from the plot.

One should prepare separate plots for shallow and deep mineralization or for different zones and deposits on a property rather than aggregate everything together.

It may be possible to undertake a similar analysis with different commodities if one can summarize the assays into a single equivalent value or NSR dollar value. Unfortunately, exploration news releases don’t often include the poly-metallic interval equivalent grade or NSR value. Calculating these manually would add an extra step in the process, however it can be done.

If you want to try out the concept, I have posted the online spreadsheet to my website at the link Drill Intercept Potential where you can input Au exploration data of interest. Unfortunately, you cannot save your input data so it’s a one time event. Anyone can do this – its not rocket science.

Let me know your thoughts, suggestions, or other ways to play with news release data.

If your project contains metals other than gold, then the rock (or ore) value will be based on the revenue from a combination of metals. How to approach this in discussed in another blog post titled “Ore Value Calculator – What’s My Ore Worth?“

Great Bear Resources Example

Interesting the Great Bear Resources website allows one to download a data file with all their exploration intervals. I have not seen another company provide this level of transparency. I download their data file of over 1300 intervals and sub-divided them into major intervals and sub-intervals (more ore less). The two plots below show the outcome.

The graph on the left is the sub-intervals showing that many points are above the “economic” line. There are numerous data points along the top axis, indicating many sub-intervals at >10 g/t at widths ranging from 1 to 15 metres. The graph on the right shows the major intervals. While there are still many along the top axis, there are now more along the 40m width but at grades ranging from 1 g.t to 6 g/t.

One would surmise from these plots that overall there are many intervals above the line in the economic zone, showing the potential of the project. It also shows that GBR have encountered many intervals likely sub-economic, but that’s the exploration game.

Great Bear Resources data

Examining polymetallic drill results in a similar manner isn’t as simple as this. The mutiple metals of interest make the calaculations a bit more complex. Another blog post discusses the approach I use for polymetallic, at this this link “Polymetallic Drill Results – Interesting or Not?“

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AI versus the Geologists

Date: March 29, 2019 Author: Ken Kuchling Comments: 1 Reply

We likely have all seen recent articles about how Artificial Intelligence (AI) is going to change the mining industry. I have been wondering if AI is a real solution or just a great buzzword. My original skepticism has diminished somewhat and let me explain why.

At a booth at the 2019 PDAC I had a chance to speak with a publicly traded company called Albert Mining (referencing Albert Einstein’s intelligence). They are providing exploration consulting services by applying a form of AI and have been doing so for many years. The company has been around since 2005 but were not using the term AI to describe their methods.

These days the term “AI” has become very trendy. Currently IBM Canada and Goldcorp are using Watson and AI to further their exploration efforts on the Red Lake property. GoldSpot Discoveries is another recent player in the mining AI field. It appears Goldspot offers something similar to Albert Mining but they extend their platform to include picking projects, picking teams, and picking investments. That’s a lot of analysis to undertake. Albert Mining is focused solely on mineral exploration.

Here is what I learned

Albert Mining’s system, called CARDS (Computer Aided Resource Detection System) uses pattern recognition and multi-variate analysis to examine a mineral property to look for targets. The system requires that the property has some known mineralization hits and assay samples. These are used to “teach” the software. Both positive hits and negative hits are valuable in this teaching step.

The exploration property is sub-divided into cells and data are assigned to each cell. These data attributes could be derived from geophysics, geochemistry, topography, soil samples, indicator minerals, assayed samples, geological maps, etc. I was told that a cell could contain over 700 different data attributes.

The algorithm then examines the cell data to teach itself which attributes correlate to known mineralization and which attributes correlate with barren areas. It essentially determines a geological “signature” for each mineralization type. There could be millions of data points and combinations of attributes. Correlation patterns may be invisible to the naked eye, but not to the computer algorithm.

Once the geological signatures are determined, the remainder of the property is examined to look for similar signature hits. Geological biases are eliminated since it is all data driven. The newly defined exploration targets are given a ranking score based on the extent of correlation.

Some things to note are that the system works best for shallow deposits, unless one has some deep penetrating geophysical surveys. The system works best if there is fairly uniform data coverage across the entire property. The property should also have generally similar geological conditions and as mentioned before, the property needs to have some mineralized assay information.

This exploration approach reminds me somewhat of the book Moneyball. This book is about the Oakland A’s baseball team where unconventional statistics were used to rank players in order to find hidden gems.

Are geologists becoming obsolete?

I was told that many in the geological community tend to discount the AI approach. Either they don’t think it will work or they are fearing for their jobs. Personally I don’t understand these fears nor can I really see how geologists can ever be eliminated. Someone still has to collect and prepare the data as well as ultimately make the final decision on the proposed targets. I don’t see the downside in using AI as another tool in the geologist’s toolbox.

Albert Mining’s stock price has recently gained some traction (note: I am not promoting them) because junior mining news releases are starting to mention their name more often (Spruce Ridge Resources and Falco Resources are some examples).

Probably years ago if a mining company said their drill targets were generated by an algorithm, they might have gotten strange looks. Today if a mining company says their drill targets were generated by AI, it gives them a cutting edge persona. Times have changed.

In conclusion

I suggest we all take a closer looks at the AI technology to better understand what it does.

P.S. I might also suggest that Albert Mining consider revising their company name to incorporate the term “AI” to stay on trend. (Update: In October 2019, Albert Mining changed their name to Windfall Geotek; I’m not sure it better explains what they do).

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The Mining Bank or eBay for Mining Properties

Date: September 20, 2017 Author: Ken Kuchling Comments: Leave a reply

I recently attended the Money Show here in Toronto to learn a bit more about personal finanace, investing strategies, and to check out the latest stock analysis software.

There was also a trade show, but only one mining company booth was present. This definitely wasn’t the PDAC. Interestingly there were about five marijuana company booths, so that is where the promotion is today.

The lone mining company was Globex Mining, here is their website. They referred to themselves as a “mining bank”, so that was something that peaked my interest.

Mining bank

Speaking with their president, Jack Stoch, he gave me an overview on their business model. As I understood it, GLOBEX’s model is to acquire a portfolio of mineral properties. They would try to enhance their value by undertaking some limited geological work. Finally they would option, JV, or sell the property while retaining an NSR royalty.

Mr. Stoch told me that Globex currently has over 140 land packages in their inventory. Their properties will be at different stages. Some have resource estimates, others only mineralized drill intersections, mineral showings, untested geophysical targets, or combinations of these.

They are focusing their acquisitions on lower risk jurisdictions like Quebec, Ontario, Nova Scotia, New Brunswick, Tennessee, Nevada, Washington, and Germany. They try to acquire historical mines that have old shafts, following the adage the best place to find a new mine is next to an old mine. They also have some industrial mineral properties.

Globex’s only NSR revenue property right now is a zinc project in Tennessee that can generate a seven-figure royalty each year, when that operation is up and running. Unfortunately for Globex the zinc operation has not been in consistent operation the last few years.

Its a good concept

I like the concept that Globex are promoting. I like the idea of having a one-stop shop that acquires and options out exploration properties to mining companies looking for new projects.

I also like the idea of trying to consolidate land packages in an area, minimizing the patchwork of multiple ownership claims that can hinder advanced development.

Globex hope that by putting time and effort into a bunch of properties a few of them will pay off. If they can generate sufficient NSR revenues, the company may get to the self-sustaining stage.

Its not a new idea

The idea of companies involving themselves in a portfolio of early stage prospects isn’t new. This has been being done by EMX Royalty Corp (formerly Eurasian Minerals) for properties around the globe. Abitibi Royalties is also doing something vaguely similar, whereby they would help fund prospectors in exchange for a long term royalty on a property. There are likely others.

There is a high risk to being successful but the cost of entry is relatively low.

It will be interesting to watch Globex over the longer term to see how many properties they can acquire and how many of these will pay off. Spending a bit of money on mapping and exploration on a property may benefit them by increasing value in the eyes of potential partners.

Statistically, mineral exploration is a high risk game but by limiting expenditures and diversifying the portfolio, some of that risk can be mitigated.

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Ore Stockpiling – Why are we doing this again?

Date: April 28, 2016 Author: Ken Kuchling Comments: 3 Replies

In many of the past mining studies that I have worked, stockpiling strategies were discussed and usually implemented. However sometimes team members were surprised at the size of the stockpiles that were generated by the production plan. In some cases it was apparent that not all team members were clear on the purpose of stockpiling or had preconceived ideas on the rationale behind it. To many stockpiling may seem like a good idea until they saw it in action.

In this blog I won’t go into all the costs and environmental issues associated with stockpile operation. The discussion focuses on the reasons for stockpiling and why stockpiles can get large in size or numerous in quantity.

In my experience there are four main reasons why ore stockpiling might be done. They are:

1. Campaigning: For metallurgical reasons if there are some ore types that can cause process difficulties if mixed with other ores. The problematic ore might be stockpiled until sufficient inventory allows one to process that ore (i.e. campaign) through the mill. Such stockpiles will only grow as large as the operator allows them to grow. At any time the operator can process the material and deplete the stockpile. Be aware that mining operations might still be mining other ore types, then those ores may need to be stockpiled during the campaigning. That means even more ore stockpiles at site.

2. Grade Optimization: This stockpiling approach is used in situations where the mine delivers more ore than is required by the plant, thereby allowing the best grades to be processed directly while lower grades are stockpiled for a future date. Possibly one or more grade stockpiles may be used, for example a low grade and a medium-low grade stockpile. Such stockpiles may not get processed for years, possibly until the mine is depleted or until the mined grades are lower than those in the stockpile. Such stockpiles can grow to enormous size if accumulated over many years. Oxidation and processability may be a concern with long term stockpiles.

3. Surge Control: Surge piles may be used in cases where the mine may have a fluctuating ore delivery rate and on some days excess ore is produced while other days there is underproduction. The stockpile is simply used to make up the difference to the plant to provide a steady feed rate. These stockpiles are also available as short term emergency supply if for some reason the mine is shut down (e.g. extreme weather). In general such stockpiles may be relatively small in size since they are simply used for surge control.

4. Blending: Blending stockpiles may be used where a processing plant needs a certain quality of feed material with respect to head grade or contaminant ratios (silica, iron, etc.). Blending stockpiles enables the operator to ensure the plant feed quality to be within a consistent range. Such stockpiles may not be large individually; however there could be several of them depending on the nature of the orebody.

There may be other stockpiling strategies beyond the four listed above but those are the most common.

Test Stockpiling Strategies

Using today’s production scheduling software, one can test multiple stockpiling strategies by applying different cutoff grades or using multiple grade stockpiles. The scheduling software algorithms determine whether one should be adding to stockpile or reclaiming from it. The software will track grades in the stockpile and sometimes be able to model stockpile balances assuming reclaim by average grade, or first in-first out (FIFO), or last in-first out (LIFO).

Stockpiling in most cases provides potential benefits to an operation and the project economics. Even if metallurgical blending or ore campaigning is not required, one should always test the project economics with a few grade stockpiling scenarios.

Unfortunately these are not simple to undertake when using a manual scheduling approach and so are a reason to move towards automated scheduling software.

Make sure everyone on the team understands the rationale for the stockpiling strategy and what the stockpiles might ultimately look like. They might be surprised.

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Higher Metal Prices – Should Miners Lower the Cut-Off Grade?

Date: February 23, 2016 Author: Ken Kuchling Comments: 7 Replies

When metals prices are high, we are generally told that we should lower the cutoff grade. Our cutoff grade versus metal price formula tells us this is the correct thing do. Our grade-tonnage curve reaffirms this since we will now have more metal in the mineral reserve.

But is lowering the cutoff grade the right thing?

Books have been written on the subject of cutoff grades where readers can get all kinds of detailed logic and calculations using Greek symbols (F = δV* − dV*/dT). Here is one well known book by Ken Lane, available on Amazon HERE.

Recently we have seen a trend of higher cash costs at operating mines when commodity prices are high. Why is this?

It may be due to higher cost operating inputs due to increasing labour rates or supplies. It may also be partly due to the lowering of cutoff grades. This lowers the head grade, which then requires more tonnes to be milled to produce the same quantity of metal.

A mining construction manager once said to me that he never understood us mining guys who lower the cutoff grade when gold prices increase. His concern was that since the plant throughput rate is fixed, when gold prices are high we suddenly decide to lower the head grade and produce fewer and higher cost ounces of gold.

Do the opposite

His point was that we should do the opposite. When prices are high, we should produce more ounces of gold, not fewer. In essence, periods when supply is low (or demand is high) may not be the right time to further cut supply by lowering head grades.

Now this is the point where the grade-tonnage curve comes into play.

Certainly one can lower the cutoff grade, lower the head grade and produce fewer ounces of gold. The upside being an extension in the mine life. A company can report more ounces in reserves and perhaps the overall image of the company looks better (if it is being valued on reserves). To read more about the value of grade-tonnage curves, you check out this blog post “Grade-Tonnage Curves – Worthy of a Good Look“.

What if metal prices drop back?

The problem is that there is no guarantee that metal prices will remain where they are and the new lower cutoff grade will remain where it is. If the metal prices drop back down, the cutoff grade will be increased and the mineral reserve will revert back to where it was. All that was really done was accept a year of lower metal production for no real long term benefit.

This trade-off contrasts a short term vision (i.e. maximizing annual production) against a long term vision (i.e. extending mineral reserves).

Conclusion

The bottom line is that there is no simple answer on what to do with the cutoff grades. Hence there is a need to write books about it.

Different companies have different corporate objectives and each mining project will be unique with regards to the impacts of cutoff grade changes on the orebody.

I would like to caution that one should be mindful when plugging in new metal prices, and then running off to the mine operations department with the new cutoff grade. One should fully understand both the long term and short term impacts of that decision.

In another blog post on the cutoff grade issue, I discuss whether in poly-metallic deposits the cutoff should be based on metal equivalent or block NSR value. Neither approach is perfect, but I prefer the NSR option. You can read that post at “Metal Equivalent Grade versus NSR for Poly-Metallics“.

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Resource Estimates – Are Independent Audits A Good Idea?

Date: February 2, 2016 Author: Ken Kuchling Comments: 2 Replies

Question: How important is the integrity of a tailings dam to the successful operation of a mine?

Answer: Very important.

Tailings dam stability is so important that in some jurisdictions regulators may be requiring that mining companies have third party independent review boards or third party audits done on their tailings dams. The feeling is that, although a reputable consultant may be doing the dam design, there is still a need for some outside oversight.

Differences in interpretation, experience, or errors of omission are a possibility regardless of who does the design. Hence a second set of eyes can be beneficial.

Is the resource estimate important?

Next question is how important is the integrity of the resource and reserve estimate to the successful operation of a mine?

Answer: Very important. The mine life, project economics, and shareholder value all rely on it. So why aren’t a second set of eyes or third party audits very common?

NI 43-101 was the first step

In the years prior to 43-101, junior mining companies could produce their own resource estimates and disclose the results publicly. With the advent of NI 43-101, a second set of eyes was introduced whereby an independent QP could review the company’s internal resource and/or prepare their own estimate. Now the QP ultimately takes legal responsible for the estimate.

Nowadays most small companies do not develop their own in-house resource estimates. The task is generally awarded to an independent QP.

Resource estimation is a special skill

Possibly companies don’t prepare their own resource estimates due to the specialization needed in modelling and geostatistics. Maybe its due to the skills needed to operate block modeling software. Maybe the companies feel that doing their own internal resource estimate is a waste of time since an independent QP will be doing the work anyway.

The QP is the final answer..or is it?

Currently it seems the project resource estimate is prepared solely by the QP or a team of QP’s. In most cases this resource gets published without any other oversight. In other words no second set of eyes has taken a look at it. We assume the QP is a qualified expert, their judgement is without question, and their work is error free.

As we have seen, some resources estimates have been mishandled and disciplinary actions have been taken against QP’s. The conclusion is that not all QP’s are perfect.

Just because someone meets the requirements to be a Competent Person or a Qualified Person does not automatically mean they are competent or qualified. Geological modeling is not an exact science and will be based on their personal experience.

What is good practice?

The question being asked is whether it would be good practice for companies to have a second set of eyes take a look at their resource estimates developed by independent QP’s?

Where I have been involved in due diligence for acquisitions or mergers, it is not uncommon for one side to rebuild the resource model with their own technical team. They don’t have 100% confidence in the original resource handed over to them. The first thing asked is for the drill hole database.

One downside to a third party review is the added cost to the owner.

Another downside is that when one consultant reviews another consultant’s work there is a tendency to have a list of concerns. Some of these may not be material, which then muddles the conclusion of the review.

On the positive side, a third party review may identify serious interpretation issues or judgement decisions that could be fatal to the resource.

If tailings dams are so important that they require a second set of eyes, why not the resource estimate? After all, it is the foundation of it all.

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The next time you see the grade-tonnage relationship, I suggest taking a few seconds to study it a bit further. There might be some interesting things in there.

Typical Grade-Tonnage Information

Useful Grade-Tonnage Curve Information

When I am undertaking a due diligence review or working on a study, very early on I like to have a look at the grade-tonnage information. This could be for the entire deposit resource, within a resource constraining shell, or in the pit design.

The grade-tonnage information gives an understanding of how future economics or technical issues may impact on the mineable tonnage.

An example of a typical grade-tonnage curve is shown here.

The cutoff grade along the x-axis will be impacted by changes in metal price or operating cost. The cutoff grade will increase if metal prices decrease or if operating costs increase.

The question is how sensitive is the mineable tonnage to these economic factors. The slope of the tonnage and grade curves will help answer this question.

In the example shown, the tonnage curve (blue dots) is fairly linear, meaning the ore tonnage steadily decreases with increasing cut-off grade. That is expected and is reasonable.

However, if the tonnage curve profile resembled the light blue line in this image, with a concave shape, the ore tonnage is decreasing rapidly with increasing cutoff grade. This is generally not a favorable situation.

I also like to compare the ratio of the average grade to the cutoff grade. Its nice to see a ratio of 4:1 to 5:1 to ensure the overall average grade isn’t close to the cutoff. In this example, the cutoff grade is 0.5 g/t and the average grade is 4.5 g/t, a ratio of 9:1.

The tonnage curve and grade curve provide information on the nature of the mineral resource. Study them both.

Reporting Waste Within a Shell

One complaint I have about reporting mineral resources inside a resource constraining shell is the lack of strip ratio information. This applies whether disclosing a single mineral resource estimate or variable grade-tonnage data.

In my view, the strip ratio is even more important to be aware of when looking at grade tonnage data.

Its common to see mention that the mining cost is (say) $2.50/t, but if the strip ratio is 10:1, that equates to an effective mining cost of $27.50 per tonne of ore. That’s an important cost to know, especially if one is pushing a pit shell deep to maximum the mineral resource tonnage.

Spider Diagram Downsides

In 43-101 technical reports, the financial Chapter 22 normally presents the project sensitivities expressed in a spider diagram or a table format.

In a previous blog post I had discussed the flaws in the spider diagram approach. That article link is at “Cashflow Sensitivity Analyses – Be Careful”. The grade-tonnage curve helps explain why that is.

In the spider diagrams, we typically see sensitivities related to +/- 20% on metal prices and operating costs. If either of these factors change, then in reality the cutoff grade would change.

If the metal price decreases by -20%, or the operating cost climbs by +20%, the cutoff grade must increase. This adjustment is normally not made in the sensitivity analysis because it requires a lot of re-work.

Conclusion

The grade-tonnage information is always presented in technical reports. It examines the sensitivity of the orebody size to changes in cutoff grade. The next time you see grade-tonnage data, don’t skip over it. Take a minute to study it further to see what can be learned.

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When disclosing polymetallic drill results, many companies will convert the multiple metal grades into a single equivalent grade. I am not a big proponent of that approach.

I prefer using the rock value, whether calculated as a recoverable “NSR dollar value per tonne” or as an “insitu value per tonne”. Either rock value is fine for my purposes.

Interestingly NI 43-101 prohibits the disclosure of insitu rock value but allows the use of metal-equivalents. In my view this is a bit counter-intuitive since the equivalent grade can be more misleading than rock value.

What can drill intercepts show

The three aspects that interest me the most when looking at early-stage drill results are:

The economic value of the rock (in $/t tonne). This can either be “insitu value” (assuming 100% recovery, 100% payable) or the “NSR value” incorporating recovery and payable factors (if available). Personally, the 100% insitu value is simpler to calculate and assess.

The depth to the top of the economic zone, which indicates if this deposit would be a lower cost open pit mine or must be a higher cost underground mine.

The length of the economic intervals, which indicates whether bulk mining approaches are viable versus the need to selectively mine narrow ore zones. The economic interval lengths also give a sense for the potential tonnage size (i.e. is it a big deposit or a small one).

One can examine individual drill hole assays to calculate the rock value profile along each drill hole. One can also examine the rock values for the major and minor intervals of interest reported in company news releases.

I normally like to examine both, but the intervals of interest data is publicly disclosed and more readily available. Drill hole assays are often a bit harder, if not impossible, to track down.

Economic Parameters

Next one must determine what insitu rock value is deemed potentially economic, i.e. the breakeven cutoff.

In our example, lets assume a unit processing cost of $12/t and a G&A cost of $$2/t, for a combined cost of $14/t. If we envision a metal recovery range of 75%-95%, we can assume 85% for now.

If we envision a smelter payable range of 75% to 95%, we will assume 85% for that also.

Normally it would be nice to see the average head grade (or rock value) at 3 to 4 times greater than the cutoff grade. This is not a necessity but it is a positive factor.

For example, in a gold deposit with a 0.3 g/t cutoff, one would like to see average head grades at least 0.9 to 1.2 g/t or more. If the average head grade is close to the cutoff grade, then possibly the orebody tonnage may be very sensitive to changes in cutoff. This may not be a good thing.

In our example, with a breakeven cutoff rock value of $20/t, one would like to see some ore zones with insitu values 3-4x higher, or above $60 - $80/t. We can target >$70/t rock as a "nice to have" with $20/t as the cutoff.

So far, its all pretty simple. Let’s look at some actual exploration data to see how to apply this approach.

Our example will be a polymetallic deposit containing four metals of interest; copper, gold, cobalt, and iron. One can examine a few drill holes as well as the intervals of interest.

Metal prices used in this example are Cu = $4/lb, Au = $1980/oz, Co = $15.50/lb, Fe concentrate = $100/tonne, assuming 100% recovery and 100% payable for everything.

Drill Hole Assays Examples

Hole A:

Shows positive economic results with ore quality rock starting near surface and extending down to 120 metres.

While many of the assay values are between $20-$70/t there are a significant number exceeding $70/t.

This hole has good economic potential for production.

Hole B:

Shows positive economic results with economic rock starting near surface. There are multiple economic zones extending all the way down to 370 metres.

The upper part of the hole, from 40m to 100m, shows multiple assay values exceeding the $70 target.

A second potentially economic zone is seen at a depth of 130m to 190m, which is still within the open pit mining range.

This hole also has good economic potential.

Hole C:

For comparison purposes, Hole C is neutral in that while there are multiple potentially economic zones, they have lower insitu value.

This hole doesn't have the economic consistency that was seen in Holes A and B.

Possibly this hole may be near the edge of the ore body, in which case such a profile is not unexpected.

Normally I would not spend a lot of time examining holes with little to no grade. Some may consider this as a biased view. However, every orebody has its limits, and what is occurring along the edges isn’t that critical in my view.

Intervals of Interest Example

The next series of plots examines the insitu rock values over drill intervals typically published in a company news releases. The intervals of interest will composite the individual assays over larger widths based on the company’s technical judgement.

It is interesting to see whether the larger intervals have good economic potential. The following charts combine both major intervals with minor zones, often referred to as “including” in news releases. Both major and minor intervals can provide useful information.

Insitu Rock Value vs Depth:

This chart shows the rock values for multiple report intervals versus their depth (top) along the hole.

One can see multiple intervals at open pit depths (<250 m) with insitu values above the $20/t cutoff and above the $70/t threshold.

Within the upper 250 metres, we are seeing multiple intervals with good value. That is a positive sign.

Note that these depths are not depths from surface, but distance along the drill hole. In reality the intervals may be slightly closer to surface, depending on the hole inclination.

Insitu Rock Value vs Interval Length:

The next question to ask is whether the higher value zones are narrow or wide?

In the example here one can see some wide zones (70 to 90m) with rock values in the range of $40-70/t. These are good open pit mining widths.

There are numerous higher grade zones ($70-$200/t) in the 5m to 20m width range. These widths are still fine for open pit mining.

Some intervals are quite narrow (<5m), being a bit more difficult to mine. Since many of these are higher grade, they will tolerate some mining dilution.

Conclusion

This might be better than each company applying their own unique equivalent grade calculation to their exploration results.

The equivalent grade calculation still requires assumptions on the metal prices and recoveries. The result is, unfortunately, presented as a grade value rather than a dollar value.

The intervals of interest published in news releases are usually not available for download. Great Bear is (was) one example where the data was available. It would be nice if more companies followed suit by releasing their interval data in CSV or Excel format. It worked out well for Great Bear!

For further light reading, the two previous articles referenced above are “Gold Exploration Intercepts – Interesting or Not?" and "Metal Equivalent Grade versus NSR for multi-metals – Preference?"

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At the exploration stage one only has drill interval data from news releases to examine. A resource estimate may still be unavailable.

The drill data can consist of long intervals of low grade or short intervals of high grade and everything in between. What does it all mean and what can it tell you?