Articles Written By: Ken Kuchling

Resources, Resources, and Mineral Reserves

Every so often I like to comment on issues related to the way the mining industry does things. This is one of those posts.
Currently the mining industry reports their exploration results as either Mineral Resources or Mineral Reserves. In my opinion, these two categories do not adequately reflect the reality of the current mining environment. I would suggest using a three category approach, as will be described below.
The implementation of this approach would not result in any more technical effort. However, it would provide clarity for stakeholders and investors and compare companies on a more equitable basis.

The issue

In today’s world, it is an onerous task to permit, finance, build, and operate a new mine. This is a significant achievement.
An operating company will be generating revenue and should be recognized for that big step. Hence does it make sense for an operating company to report Mineral Reserves while a junior company that has simply completed a pre-feasibility study to also report Mineral Reserves?
Both companies could report identical Reserves, but those reserves would not be the same thing. One company has built a mine while the other may have spent a few months doing a paper study. One company’s reserves will actually be mined in the foreseeable future while the other company’s project may never see the light of day. Yet both companies are allowed to present the same Mineral Reserves.
As a mine operates, the remaining ore reserves will deplete over time. However, a company can add to their reserves by finding satellite ore bodies or converting inferred material into a higher classification. The net of these adjustments will be reflected in the corporate Mineral Reserve Statement for all their operations.
A company can also increase the corporate Mineral Reserves simply by completing a pre-feasibility or feasibility study on a new project. However, is this a true reflection of the Reserves upon which the company should be evaluated?

Suggestion

I would suggest that the three reporting categories be used instead of two, described as follows:
1 – Mineral Resources (insitu): This category is the same as the current Mineral Resources being reported according to NI43-101. It is based on reasonable prospects for economic extraction. Hence open pit resources would be reported within an optimized shell and underground reserves within approximate stope shapes. No external dilution or mining criteria would be applied, as is the current approach.
2 – Economic Resources: This would be a new category that would simply be the outcome from a pre-feasibility or feasibility study, which is currently being labelled a “Mineral Reserve”. This Economic Resource would incorporate mining criteria, Measured & Indicated classes only, a mine plan, and an economic analysis. The differentiation from Reserves is because the mine is not built yet.
3 – Mineral Reserves: This highest-level category could be reported only once a mine has reached commercial production. The Economic Resources would automatically convert to Mineral Reserves once production is achieved. As the mine continues to operate, and as new ore sources are identified, the Mineral Reserves would increase / decrease. The Mineral Reserves would represent the remaining ore tonnage at operating mines and only that.
This three-category approach would help separate mine operators from junior development companies. The industry should recognize the difference between companies and projects at different life-cycle stages and that they are not all directly comparable. A junior explorer could be reporting huge reserves, but without a mine being there, should that company be compared to a mine operator that has similar reserves?
This approach would identify situations whereby a company suddenly reports a sizeable increase in Reserves. Is it because they found more ore at an existing operation (a great event) or because they did a paper study on a new project?
As a clarification, if a mine gets placed onto care & maintenance, likely due to poor economics, then the remaining tonnes at the mine would no longer be considered Mineral Reserves and may have to revert to Economic Resources, although even that would be questionable.

Examples

Out of curiosity I randomly selected three companies (Yamana Gold, Eldorado Gold, Alamos Gold) to compare their total Mineral Reserve tonnages based on their operations versus study stage development projects. The results are show in the images below. The percentage of Reserves provided by their producing (P) mines varied and ranged from 14% to 51%. A significant proportion of their Reserves (49% to 86%) are still at the development (D) stage. One or two large study-stage projects can boost the corporate reserves significantly. This is not immediately evident when looking at the total Mineral Reserves being reported.
For most junior miners 100% of their Reserves are still at the study-stage. They should not be able to declare Mineral Reserves and appear on an equal footing with mine operators. Their company should only be comparable to other companies with advanced study-stage projects.

Conclusion

The foregoing discussion is a suggestion as to how the mining industry can recognize the achievement and economic reality of building a mine, i.e. by being allowed to report Mineral Reserves. All others only get to report Resources. This would help clarify what long term tonnages are actually being mined versus simply being studied on paper.
The suggested approach does not create additional work for the mining companies. However, it provides a much fairer and transparent comparison between companies.
Interestingly, NI43-101 specifies that one cannot mathematically add together Indicated and Inferred resources because they are view as materially different. However, in a corporate Mineral Reserve Statement one is allowed to combine Reserves at an operating mine with Reserves from a study.  These two reserves, in my view, are even more materially different than Indicated and Inferred resources are.
Its great for a company to report Mineral Reserves from a pre-feasibility study.  However if for some reason that mine never gets built, then those Reserves are valueless. Maybe years ago it was foregone conclusion that a positive feasibility study would result in the construction of a mine, so the risk was less. That is no longer the case and this fact should be recognized when defining and reporting Mineral Reserves.
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Hard Rock Continuous Cutting – Reducing Drill & Blast

Several years ago I worked in the Saskatchewan potash industry where I grew my appreciation for continuous mining systems. Some of the key benefits were the high productivity per man-hour and the safe operating conditions.  On a 12 hour nightshift, with a crew of 16 people we could mine over 9,000 tonnes of ore.  Productivity is  likely even higher now with the larger machines.   Therefore, since that time, I have always kept an eye out for when similar technology can be applied in hard rock mining.
One of the research areas we are seeing these days is the development of continuous cutting technology for hard rock mine development.  The idea is to replace the conventional drill & blast approach with something more efficient and safer.  No need to deal with explosives, noxious gases, shatter the wall rock, or have personnel scale their way under loose conditions.
Recently I was contacted by someone associated with Robbins asking if I was aware of their MDM5000 mine development technology.  I wasn’t aware of it, but I wondered if there finally is a light at the end of the tunnel.

4-rotor miner

In Saskatchewan potash the entire mining operation relies on track-mounted continuous miner technology.   The miners are connected directly to the shaft area using a network of conveyors, up to 10 km worth of conveyor.
The potash miners are able to undertake both development work and production mining whilst connected to conveyor.
From time to time they will rely on shuttle cars, scooptrams, or grasshopper conveyors for small development tasks. A roadheader may also be available for localized ground stabilization.
All of this mechanical cutting is done in potash (sylvinite rock), considered a soft rock with a compressive strength of 20-40 MPa. For comparison, hard rock can have compressive strengths exceeding 250 MPa.

Two approaches in hard rock

Hard rock piloting trials are underway at a few operations, using different vendors with different equipment.  These trials include companies like Komatsu, Robbins, Sandvik, and Epiroc.  Each are testing their own equipment and cutting technologies.
The hard rock cutting approaches generally fall into two camps.

Roadheader style

There are the track mounted roadheader style cutters, typically with a movable arm used to shape the excavation.  Any excavation shape is possible.

Tunnel Borer Style

Then there are the tunnel borer styles, where the machine propels itself with hydraulic shoes and the opening shape is based on the machine configuration. Normally a circular shaped opening is the result.
The roadheader style cutter is normally restricted to softer rock (< 50 MPa) while the tunnel borer is capable of much harder rock (200-250 MPa).

Robbins MDM5000

One system that peaked my interest is the Robbins MDM5000 because it can both cut hard rock and create a rectangular opening. Speaking with the vendor, this unit uses shoes to propel itself while cutting a rectangular shaped opening about 5m x 4.5m in size (see image).  A rectangular shape is preferred to the circular opening whereby the floor invert must be backfilled to provide a level operating surface.

MDM5000 opening shape

The MDM5000 configuration and advance rate allows the installation of ground support and utilities behind the advancing face.   Water sprays and dust collectors help to maintain visibility and air quality at the working face.
The Robbins unit is best suited for long straight drives although reportedly it can turn curves with 450-m radius.  Tighter turns may be feasibility in the future by tweaking the machine design.   Interestingly driving a drift uphill is easier than driving downhill due to the more efficient cuttings removal capability.
The MDM5000 unit can be linked to a Robbins conveyor system, which includes a head drive and an extensible belt storage unit that can feed out the conveyor belt as the machine advances forward.  This operation is similar to that used in the Saskatchewan potash industry.

Robbins MDM5000

A Robbins machine has been in operation at the Fresnillo mine for several years with favorable results (check out the link here).
One nice thing about disc cutters is that they can accommodate variable rock types (softer and harder) while road headers can be hindered by hard rock zones.  Roadheaders require a bit more consistency in rock quality.
Continuous cutting systems, such as the MDM5000, can be combined with vertical conveying technology, leading to safe and rapid development (>200m per month) in the right situation.

Conclusion

No doubt that we will eventually see more application of hard rock continuous cutting technology in the right situations.  The Stillwater Mine in Montana has been using a Robbins tunnel borer for years for development tasks.
No matter how well these new systems perform, there will still be some limitations.  This means the conventional drill and blast development will always be around.  However, keep your eyes on this mining technology sector as improvements in cutter head design and equipment mobility continue to evolve.
Coincidentally International Mining (Nov-Dec 2021) recently published an in-depth article on the various systems being looked at.  The link is here.

 

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Let A.I. Help Target Your Infill Drilling

From time to time I come across interesting new tech that I like to share with colleagues.  The topic of this blog relates to solving the problem of defining an optimal infill drill program.
In the past I have worked on some PEA’s whose economics were largely based on Inferred ore.  The company wanted to advance to the Pre-Feasibility (PFS) stage. However, before the PFS could start they would need additional drilling to convert much of the Inferred resource into Measured and Indicated resources.
I’ve seen similar experience with projects that are advance from PFS to FS where management has a requirement that the ore mined during the payback period consist of Measured classification.

The Problem

In both cases described above, it is necessary for someone to outline an infill drill program to upgrade the resource classification while also meeting other project priorities.  The goal is to design an infill drill program with minimal time and cost yet maximize resource conversion.  Possibly some resource expansion drilling, metallurgical sampling, and geotechnical investigations may be required at the same time.
I’m not certain how various resource geologists go about designing an infill drill plan.  However, I have seen instances where dummy holes were inserted into the block model and then the classification algorithm was re-run to determine the new block model tonnage classification.   If it didn’t meet the corporate objectives, then the dummy holes may be moved or new ones added, and the process repeated.
One would not consider such a trial & error solution as optimal. It may not necessarily meet the cost and time objectives although it may meet the resource conversion goals.

The Solution

The DRX Drill Hole and Reporting algorithm developed by Objectivity.ca uses artificial intelligence to optimize the infill drilling layout.  It intends to match the QP/CP constraints with corporate/project objectives.
For example, does company management require 70% of the resource in M&I classifications or do they require 90% in M&I?  Each goal can be achieved with a different drill plan.
The following description of DRX is based on discussions with the Objectivity staff as well as a review of some case studies.  The company is willing to share these studies if you contact them.
The DRX algorithm relies on the resource classification criteria specified by the company QP.  For example, the criteria could be something like “For a block to qualify as Measured, the average distance to the nearest three drill holes must be 30 m or less of the block centroid. For a block to qualify as Indicated, the average distance from the block centroid to the nearest three holes must be 50 m or less. For a block to qualify as Inferred it will generally be within 100 m laterally and 50 m vertically of a single drill hole.
The DRX algorithm will use these criteria to optimize drill hole placement three dimensionally to deliver the biggest bang for the buck.   Whatever the corporate objective, DRX will attempt to find an optimal layout to achieve it.  The idea being that fewer well targeted holes may deliver a better value than a large manually developed drill program.
The DRX outcome will prioritize the hole drilling sequence in case the drill program gets cut short due to poor weather, lack of funding, or the arrival of the PDAC news cycle.
The DRX approach can also be used to optimally site metallurgical holes and/or geotechnical holes in combination with resource drilling if there are defined criteria that must be met (by location, ore type, rock type, etc.).   The algorithm will rely on rules and search criteria developed by experts in those disciplines.  It does not develop the rules, it only applies them.
DRX can also help optimize step-out drilling, such that the step-out distance will not be beyond the range that negates the use of the hole in a resource estimate.  It can also consider geological structure in defining drill targets.

By optimizing the number of drill holes and their orientation, the company may see savings in drill pad prep, drilling costs, field support costs, and sample assaying.
One can even request drilling multiple holes from the same drill pad to minimize drill relocation costs and safety issues in difficult terrain.
A large benefit of DRX is to be able to examine what-ifs.  For example, one may desire 85% of the resource to be M&I.   However, if one is willing to accept 80%, then one may be able to save multiple holes and associated costs.   Perhaps with the addition of just a few extra holes one could get to 90% M&I.   These are optimizations that can be evaluated with DRX.

An Example

In the one case study provided to me, a $758,000 manually developed drill program would convert 96.6% of the Inferred resource to Indicated.  DMX suggested that they could achieve 96.7% for $465,000. Alternatively they could achieve 94% conversion for $210,000.  These are large reductions in drilling cost for small reductions in conversion rate.  This may allow the drill-metres saved to be used for other purposes.
For that same project, a subsequent study was done to convert Indicated to Measured in a starter pit area. DRX concluded that a 5000-metre program could convert 62% of Indicated into Measured.  A 12,000-metre program would convert 86%,  A 16,000-metre program would achieve 92%.
So now company management can make an informed decision on either how much money they wish to spend or how much Measure Resource they want to have.

Conclusion

Although I have not yet worked with DRX, I can see the value in it.   I look forward to one day applying it on a project I’m involved with to develop a better understanding of what goes in and what comes out.   DRX hopes to become to resource drilling what Whittle has become to pit design – an industry standard.
The use of the DRX algorithm may help mitigate situations where, moving from a PEA to PFS, one finds that the infill program did not deliver as hoped on the resource conversion.  Unfortunately, this leaves the PFS with less mineable ore than anticipated and sub-optimal economics.
New tech is continually being developed in the mining industry.  Hopefully this is one we continue to see forward advancement. It makes sense to me and DRX could be another tool in the geologist toolbox.  Check out their website at objectivity.ca
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Mining Financial Modeling – Make it Better!

In my view one thing lacking in the mining industry today is a consistent approach to quantifying and presenting the risks associated with mining projects. In a blog written in 2015, I discussed the limitations of the standard “spider graph” sensitivity analysis (blog link here) often seen in Section 22 of 43-101 reports. This new blog expands on that discussion by describing a preferred approach. A six-year time gap between the two articles – no need to rush I guess.
This blog summarizes excerpts from an article written by a colleague that specializes in probabilistic financial analysis. That article is a result of conversations we had about the current methods of addressing risk in mining. The full article can be found at this link, however selected excerpts and graphs have been reprinted here with permission from the author.
The author is Lachlan Hughson, the Founder of 4-D Resources Advisory LLC. He has a 30-year career in the mining/metals and oil gas industry as an investment banker and a corporate executive. His website is here 4-D Resources Advisory LLC.

Excerpts from the article

Mining can be risky

“The natural resources industry, especially the finance function, tends to use a static, or single data estimate, approach to its planning, valuation and M&A models. This often fails to capture the dynamic interrelationships between the strategic, operational and financial variables of the business, especially commodity price volatility, over time.”
“A comprehensive financial model should correctly reflect the dynamic interplay of these fundamental variables over the company life and commodity price cycles. This requires enhancing the quality of key input variables and quantitatively defining how they interrelate and change depending on the strategy, operational focus and capital structure utilized by the company.”
“Given these critical limitations, a static modeling approach fundamentally reduces the decision making power of the results generated leading to unbalanced views as to the actual probabilities associated with expected outcomes. Equally, it creates an over-confident belief as to outcomes and eliminates the potential optionality of different courses of action as real options cannot be fully evaluated.”

Monte Carlo can be risky

“Fortunately, there is another financial modeling method – using Monte Carlo simulation – which generates more meaningful output data to enhance the company’s decision making process.”
Monte Carlo simulation is not new.  For example  @RISK has been available as an easy to use Excel add-in for decades. Crystal Ball does much the same thing.
“Dynamic, or probabilistic, modeling allows for far greater flexibility of input variables and their correlation, so they better reflect the operating reality, while generating an output which provides more insight than single data estimates of the output variable.”
“The dynamic approach gives the user an understanding of the likely output range (presented as a normal distribution here) and the probabilities associated with a particular output value. The static approach is relatively “random” as it is based on input assumptions that are often subject to biases and a poor understanding of their potential range vs. reality (i.e. +/- 10%, 20% vs. historical or projected data range).”
“In the case of a dynamic model, there is less scope for the biases (compensation, optionality, historic perspective, desire for optimal transaction outcome) that often impact the static, single data estimates modeling process. Additionally, it imposes a fiscal discipline on management as there is less scope to manipulate input data for desired outcomes (i.e. strategic misrepresentation), especially where strong correlations to historical data exist.”
“It encourages management to consider the likely range of outcomes, and probabilities and options, rather than being bound to/driven by achieving a specific outcome with no known probability. Equally, it introduces an “option” mindset to recognize and value real options as a key way to maintain/enhance company momentum over time.”

Image from the 4-D Resources article

“In the simple example (to the right), the financial model was more real-world through using input variables and correlation assumptions that reflect historical and projected reality rather than single data estimates that tend towards the most expected value.”
“Additionally, the output data provide greater insight into the variability of outcomes than the static model Downside, Base and Upside cases’ single data estimates did.”
The tornado diagram, shown below the histogram, essentially is another representation of the spider diagram information. ie.e which factors have the biggest impact.
“The dynamic data also facilitated the real option value of the asset in a manner a static model cannot. And the model took less time to build, with less internal relationships to create to make the output trustworthy, given input variables and correlation were set using the @RISK software options. This dynamic modeling approach can be used for all types of financial models.”
To read the full article, follow this link.

Conclusion

image from 4-D Resources article

Improvements are needed in the way risks are evaluated and explained to mining stakeholders. Improvements are required given increasing complexity in the risks impacting on decision making.
The probabilistic risk evaluation approach described above isn’t new and isn’t that complicated. In fact, it can be very intuitive when undertaken properly.
Probabilistic risk analysis isn’t something that should only be done within the inner sanctums of large mining companies. The approach should filter down to all mining studies and 43-101 reports. It should ultimately become a best practice or standard part of all mining project economic analyses. The more often the approach is applied, the sooner people will become familiar (and comfortable) with it.
Mining projects can be risky, as demonstrated by the numerous ventures that have derailed. Yet recognition of this risk never seems to be brought to light beforehand. Essentially all mining projects look the same to outsiders from a risk perspective, when in reality they are not. The mining industry should try to get better in explaining this.
UPDATE:  For those interesting in this subject, there is a follow up article by the same author published in January 2022 titled “Using Dynamic Financial Modeling to Enhance Insights from Financial Reports!“.
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Pit Optimization – More Than Just a “NPV vs RF” Graph

In this blog I wish to discuss some personal approaches used for interpreting pit optimization data. I’m not going to detail the basics of pit optimization, instead assuming the reader is familiar with it .
Often in 43-101 technical reports, when it comes to pit optimization, one is presented with the basic “NPV vs Revenue Factor (RF)” curve.  That’s it.
Revenue Factor represents the percent of the base case metal price(s) used to optimize for the pit. For example, if the base case gold price is $1600/oz (100% RF), then the 80% RF is $1280/oz.
The pit shell used for pit design is often selected based on the NPV vs RF curve, with a brief explanation of why the specific shell was selected. Typically it’s the 100% RF shell or something near the top of the curve.
However the pit optimization algorithm generates more data than shown in the NPV graph (see table below). For each Revenue Factor increment, the data for ore and waste tonnes is typically provided, along with strip ratio, NPV, Profit, Mining cost, Processing, and Total Cost at a minimum. It is quick and easy to examine more of the data than just the NPV.

In many 43-101 reports, limited optimization analysis is presented.  Perhaps the engineers did drill down deeper into the data and merely included the NPV graph for simplicity purposes. I have sometimes done this to avoid creating five pages of text on pit optimization alone. However, in due diligence data rooms I have also seen many optimization summary files with very limited interpretation of the optimization data.
Pit optimization is a approximation process, as I outlined in a prior post titled “Pit Optimization–How I View It”. It is just a guide for pit design. One must not view it as a final and definitive answer to what is the best pit over the life of mine since optimization looks far into the future based on current information, .
The pit optimization analysis does yield a fair bit of information about the ore body configuration, the vertical grade distribution, and addresses how all of that impacts on the pit size. Therefore I normally examine a few other plots that help shed light on the economics of the orebody. Each orebody is different and can behave differently in optimization. While pit averages are useful, I also prefer to examine the incremental economic impacts between the Revenue Factors.

What Else Can We Look At?

The following charts illustrate the types of information that can be examined with the optimization data. Some of these relate to ore and waste tonnage. Some relate to mining costs. Incremental strip ratios, especially in high grade deposits, can be such that open pit mining costs (per tonne of ore) approach or exceed the costs of underground mining. Other charts relate to incremental NPV or Profit per tonne per Revenue Factor.  (Apologies if the chart layout below appears odd…responsive web pages can behave oddly on different devices).

Conclusion

It’s always a good idea to drill down deeper into the optimization data, even if you don’t intend to present that analysis in a final report. It will help develop an understanding of the nature of the orebody. It shows how changes in certain parameters can impact on a pit size and whether those impacts are significant or insignificant. It shows if economics are becoming very marginal at depth. You have the data, so use it.
This discussion presents my views about optimization and what things I tend to look at.   I’m always learning so feel free to share ways that you use your optimization analysis to help in your pit design decision making process.

 

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Gold Exploration Intercepts – Interesting or Not?

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.

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

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Stories from 3000 Feet Down – Part 2

This is Part 2 of my story about working at a potash mine in Saskatchewan. If you haven’t read Part 1, here is the link to it “Stories from 3000 Feet Down – Part 1“.  It’s best to read it first.

Flooded Russian Potash Mine

As mentioned in Part 1, water seepage and potential leaks were always an operational concern. There were essentially two main fears; (i) that a borer would tunnel into an unforeseen collapse zone (i.e. an ancient sink hole) or (ii) that long term deformations in the mine would result in cracking of the overlying protective salt layer resulting in water inflow.
Any time wet spots were seen on the roof, the mining engineers or geologists were called out to take a look.
Sometimes the wet area was due to pockets of interstitial moisture. Other times it might have just been oil from a blown hydraulic hose on the borer. Wet spots all look the same when covered in dust.
Water ingress was such a concern in that an unmined pillar of 100 ft. would be left around all exploration core holes. These 3,000 ft. holes were supposedly plugged after drilling but you could never be certain of that. Furthermore, you couldn’t be certain of their location at potash depth. Hence, we didn’t want to mine anywhere close to them.
The process plant also had several water injection wells whereby excess water was injected into geological formations deep below the potash level. We left a 700 ft. pillar around these injection wells.
Carnallite is a magnesium salt that we encountered in some areas of the mine. It was weaker than the halite, resulting in more rapid room closure and deteriorating ground conditions. It was also hydroscopic and could absorb moisture out of the air. Sometimes we would water the underground travel ways to mitigate dust issues. With the resulting high humidity sometimes the carnallite areas might start to drip water. This resulted in another call to the engineers to come out and investigate.

Working on a production crew brings new learnings.

My period as a production foreman was great. When first assigned to this role, I was less than enthusiastic but when it was over 6 months later, I appreciated the opportunity. As a production foreman, we had a crew of 15 to 20 people responsible for mining 9,500 tons over a 12 hour shift. There was one foreman in the underground dispatch room and one face foreman travelling around supervising the borers and inspecting conveyors.
Ore grade control was a key responsibility of both the borer operator and mine foreman. The goal for the borer operator was to cut the roof even with the top of the high grade potash bed. The goal for the foreman was to ensure the operator was maintaining his goal. However, when looking at the potash face all the beds generally looked the same, especially when they are dusty.

Feel the glow

One key distinction was that the middle low grade bed had a higher percentage of insol clays. It was used as a marker bed. You would take your hardhat lamp and run it down against the wall. In the upper high grade potash bed, the cap lamp would have a halo, not unlike like the glowing salt rock lamps you see in stores. In the marker bed the halo would disappear, like putting a lamp against a rock wall.
Thus using the lamp you could identify the top of the marker bed, which was supposed to be kept 3.5 to 4 ft. off the floor. If borer operators were consistently more than 12 “ inches off optimal level, they could be written up (i.e. reprimanded). This was one of my tasks as foreman and I always hated doing it.
Lasers were used to guide the borer in a straight line but the marker bed was used for vertical control. Nowadays the use of machine mounted ore grade monitors is an option. By the way, if you’re looking at a potash project, be aware of the grade units being reported. A previous blog discusses this “Potash Ore Grades – Check the Units”.
The underground conveyor network consisted of 32” conveyors, feeding onto 42” conveyors, feeding on to 48”or 54” conveyors. Typically the length of the larger conveyors was in the range of a mile (5,000-6,000 ft.). The conveyors were all roof mounted, allowing for easy clean up underneath. Roof mounting was critical. Even some of the 600 hp conveyor drive stations were roof mounted, structure and all.

Conveyors were the reason for my one and only safety incident.

4-rotor side pass

4-rotor borer side pass

First a little background. The underground ore storage capacity at K1 was about 3,000 tons. If the underground bins were filled anytime during a shift, the entire conveyor system would automatically trip off; all 10 miles of it. If you happened to have a mile long conveyor shut off while it was loaded to the brim with ore, good luck starting it up again.
If this happened, there were two choices. You could bring in the operators from the borers to start shovelling off the conveyor until it was unloaded enough to re-start. This option went over like a lead balloon with the crew.
The other not so great option was to use a scooptram to lift the belt counterweight up to reduce the belt tension. This allows the drive pulleys to start spinning. Then by lowering the counterweight back down perhaps the drives can inch the belt along. The idea being that possibly the momentum of the moving mass of potash would keep it moving. The downside is that you could break the belt. There was nothing worse than having to tell the cross shift they have both a stalled conveyor and a broken belt. Have a good shift people.
At 4 a.m. working as night shift face foreman, I knew the underground bins were nearing full. Driving along I saw that the mainline conveyor was full and spilling over the sides. A worst case conveyor shutdown was imminent. I called the dispatch office to ask why he hasn’t been shutting down borers and conveyors but there was no answer.
After several unanswered calls I started to hustle back to dispatch. I remember driving alongside the conveyor thinking “don’t shut off, don’t shut off”. Just then a heavy duty service vehicle pulled out of a cross-cut and I plowed right into it. I wasn’t going very fast (~20 km), but when a Toyota Land Cruiser hits a steel plate truck, the Toyota is the loser. The front end crumpled, and I later was told that there was major frame damage.
I’m not sure why the other driver didn’t see my lights. I’m also certain his lights were not on. Nevertheless, I did get written up for this incident with a reprimand for my personnel file. The reprimander had become the reprimandee. I still insist that the incident wasn’t my fault.
The Land Cruiser laid around the shaft for a few days until it could be hoisted up to surface. Everyone coming on shift got to see it . Once it was hoisted up, it laid outside the headframe for a few more days for all the surface workers to see. Ultimately, this incident resulted in the underground miners giving me the nickname “Crash”.
This is where I’ll end the potash story.

Conclusion

Saskatchewan potash is a unique mining situation. It has its own history and mining method. The people are great and it’s a great place to learn the difference between engineering school and real life.

Mine Engineering Dream Team

By the way, I also learned that small town Saskatchewan loves their senior hockey league (20-30 year age range). The local towns compete all winter; sometimes combatively. It was Esterhazy vs. Langenburg vs. Whitewood vs. Rocanville vs. Stockholm vs. Moosomin.
One of the first questions asked in my job interview at Mosaic was if I played hockey. You see, the ideal candidate for the job would have been an ex-NHL player, preferably an enforcer, who is also a mining engineer. Gotta stack the local team.

 

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Stories from 3000 Feet Down – Part 1

Mosaic K1 Mine

Between 1985 and 1989 I worked at the Mosaic K1 potash mine in Saskatchewan, Canada.  I had roles that included mine engineer, chief mine engineer and production foreman.   This was relatively early in my work career so it represented an important learning period of time for me.  Each of these roles gave me a different perspective about a mining operation.   In this two part blog, I’ll share some stories relating to the uniqueness of potash mining.
The K1 mine is 15 kilometres outside the town of Esterhazy; about 2.5 hours east of Regina.  The mine is located at a depth of around 3,000 feet below surface, hence the title of this blog.  I will be referring to imperial units in this text because when the mine started production in the early 1960’s the maps and units were imperial and continued on through the 80’s.   At my previous job with Syncrude we used metric units, so it took some time to mentally recalculate back.
Geologically, the province wide Esterhazy Member was being mined, named after the town.  The layer was about 8 ft high.  In other regions of Saskatchewan they are mining a different potash layer (the Patience Lake Member) which is located a few feet higher up. These mines have slightly different mining conditions than we experienced in Esterhazy.  An example of their conditions is shown in the photo, where a parting layer can result in a roof collapse.
The Mosaic K1 and K2 mine shafts are interconnected at depth 6 miles.  The total expanse of the K1 and K2 underground workings probably extends laterally over 18 miles.  Back in the 80’s they said there were over 1,000 miles of tunnel underground and probably a lot more now since the mines are still operating.  There is now a new K3 shaft which allows access to more distant potash reserves.

4-rotor borer

Potash, also termed sylvanite, mainly consists of intermixed halite (rock salt) and sylvite (potash) crystals. There are also minor amounts of insolubles (clays) and sometimes carnallite (a magnesium salt).  Sylvite (KCl) is the pay dirt, salt is the gangue mineral.
The production rooms being mined were about 75 ft. wide and 5,000 ft. long.  That is quite a large span, not likely possible in many other rock types other than salt rock.  Overall, the mine would extract about 40-45% of the potash, leaving behind the rest in the form of large pillars to support the overlying rock mass.

2-rotor borer

The mines use continuous miners or borers. In the 80’s they were Marietta miners and now they use borers from Prairie Machine (read more here).   When I was there they were starting to transition from two-rotor to four rotor machines.   The small machines would carve out ~350 tph, and the large ones could do over ~700 tph.
All borers are directly connected to the massive underground conveyor network that moves the ore from the cutter head to the shaft in a continuous process.
Mining excavates an 8 ft. high room consisting of three layers of interest.  A 4.3 ft. layer of high grade ore, a 1.7 ft. layer of low grade ore, and a 2.5 ft. layer of moderate grade potash.  This adds up to 8.5 ft., so the miners try to take the best 8 feet.  The best head grade would be delivered if the borer cut exactly to the top of the high grade 4.3 ft. seam. One didn’t want to overcut into overlying salt or undercut and leave high grade behind in the roof.  I’ll have more on how grade control was done in Part 2.
The air temperature underground is about 25C, so it’s quite a pleasant short sleeve climate.  Around the cutting face, the electric motors, and cutter head, temps can reach into the high 30 degree range. Hot but better than freezing. The mine was dry with very low humidity.   Hence metal didn’t rust.  However, bring the metal to surface and it would rust in no time.
Potash is termed a plastic rock, in that it will deform slowly under stress.  Hard rock will build up stresses and erupt violently in a “rock burst”.  Potash will go with the flow and deform.  Pillars will compress vertically and expand horizontally.  Room heights can decrease over time as much as 6 inches over several weeks in higher stress areas.
Interestingly when the borer shut down and all was quiet, one could walk to the freshly cut face.   You could hear the potash walls gently crackling like rice krispies, as the potash expanded into the opening.  After all, a few moments earlier the potash was being laterally confined under a vertical stress of 3,000 psi. That confinement is suddenly gone.
Roof closure was always an issue.  In panels that were almost mined out, all the ground stress was being carried by the unmined ground.  When advancing into this ground, roof closure could be so rapid that once a borer finished a 4 to 6 week room, the miner operator would need to cut a few inches off  the roof to get back to the front of the room.  It took a couple of days to get the borer out, rather than during a regular shift.
In very high stress areas you could see the floor heaving up as pillars were compressing laterally. That’s when you really knew that mining panel was done and operations should relocate to a new area.
I recall inspecting some of the very old workings from 20 years past.  The rooms looked like new except the roof had compressed down to 5 ft. in height.   We’d have to drive leaning sideways out of the jeep because the steering wheel was literally scraping the roof.

Flooded Russian Potash Mine

The biggest fear in potash mining is water inflow and mine flooding. There can be a water bearing layer about 50-70 feet above the mining level.  A layer of salt rock separates the two.  If you have groundwater flowing through a dissolvable material, it’s no surprise that the pathway will keep getting larger and larger. That’s why any sign of water seepage is taken seriously and causes the engineering team to leap into action (more on that in Part 2).
At least one potash mine in Saskatchewan has flooded.  A couple of others have come close but have managed to deal with the water inflows.
Barren areas where the sylvite has been leached away and replaced with pure halite are called salt horses.   I never knew why and still don’t.
Exploration core holes could be a mile apart so salt horses would be encountered unexpectedly.  They could be 20 or 2,000 feet in size; you never knew which.   They were a nuisance and an economic penalty.  If you tried to tunnel through them, you would send a lot of uneconomic salt up the shaft to the mill (which they did not like). Conversely, pulling out and abandoning a room was a painful decision because it took that borer off line for a couple of days to relocate. It’s an unplanned outage, which is not good if another borer happens to be moving at the same time.
On occasion, a borer would abandon the room and move to the next room 50 feet away and could pass by the same area without seeing the salt horse.  Upon reflection, perhaps we should have persevered in the previous room and gone another 20 ft. and we might have been through it.  Often the mill manager hollering about the mill getting too much salt was a deciding factor in whether to abandon a room or keep cutting.
For a year or so,  I also worked as a production foreman.  It was an interesting role. How does a young mining engineer four years out of school tell  guys working underground for 20 years what they need to do?
This also leads to the time when I wrecked a Toyota Land Cruiser underground.   I’ll leave that account to Part 2.  I’ve rambled long enough for today.
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Two More Mining Productivity Innovations

The mining industry is always on the lookout for new innovations as it strives to keep up with other industries.  In that light, periodically I like to highlight new technologies that I become aware of.   I’m trying to help spread the word  about them, which in turn may assist them in their on-going growth and development.
In this article I want to briefly describe two hardware / software companies that are working on technologies related to mine equipment productivity.    In no particular order, the two companies are Loadscan and SedimentIQ.  SedimentIQ is more of a startup than Loadscan which has a longer operating track record.
These technology companies are both targeting the open pit and underground markets, looking to provide simpler and less costly productivity solutions. Their technologies may be well suited for small to mid tier mines that cannot afford or don’t require the comprehensive Minestar type fleet management systems.
For the record, I get no fee or commission for promoting these companies; I just like what they are doing.

Loadscan

Loadscan has been around for a few years, but I only became aware of it recently.  It is a technology that allows the rapid assessment of the load being carried in truck.  It does not rely on the use of load cells or weigh scales to measure the payload.
Instead Loadscan uses a laser scanner and proprietary software to three dimensionally map the surface of the truck payload and then calculate its volume.  The results will indicate how consistent and optimal truck loading is volumetrically.   One can then calculate the payload tonnage by applying a bulk density.
The Loadscan technology will assess whether trucks are being over or under loaded, whether the loads are off-centre, or whether there is excess carryback on the return trip.
Successive truck payloads can be tracked manually or with RFID tags.   A cloud based database and web based dashboard are used to store the data and summarize it. The output can include an image of each individual load.
What is interesting about this technology is that it is simple to install in an operation.  It does not require retrofitting of a truck.
Results are immediate.  Loadscan provided an example where a message readout board can let the shovel operator immediately know how well each truck was loaded, resulting in improved education and better performance efficiency.
One can also assess how much better shovel bucket factors are in well blasted rock versus in blocky rock.
The Loadscan system is already in use in several mines globally.  The vendors can provide more technical  data if you need it.
Their website is https://www.loadscan.com/

SedimentIQ

SedimentIQ is a vehicle tracking platform using a smartphone app.  Their technology makes use of a phone’s built-in GPS, Bluetooth, and accelerometer to track vehicle operation.  The phone’s sensor can measure vibrations produced by an operating truck or loader.
Vibration is a fingerprint of a vehicle’s activity.  Therefore using machine learning, the SedimentIQ app can produce an “activity score” that decides whether a machine is parked, idling, or performing productive work.  The phone is not connected to the machine diagnostics system, so its very easy to install, only needing a power source.
The system can be used on any vehicle you want tracked, including trucks, drills, loaders, graders, dozers, etc. The system has the capability to monitor equipment location and speed.
In an open pit environment it uses the phone’s GPS to monitor vehicle location. In an underground setting the phone reads inexpensive Bluetooth beacons mounted along the side walls to track location.
The app will identify delay and downtime based on equipment vibration levels.  The system currently requires no interaction with the operator, working in the background.  Hence it will not identify the cause of delay (i.e. blasting delay, breakdown, inter-equipment delay, etc).  I would expect that in the future they could add a feature for the operator to tag delay types on the touch screen.
The SedimentIQ software will aggregate the cycle time and delay information and upload it in real time to a cloud based database.  A web-based dashboard allows anyone with access to view the real time production data graphically or export it to Excel.
The SedimentIQ platform is less expensive than high end fleet management software.  Although it may not provide all the bells and whistles of the high end software, it may deliver just what you need to monitor productivity in your mining operation.  It relies on relatively inexpensive smart phones that are locked to the application.
I recall as a mining student doing time studies.  I rode the shift crew bus with pencil in hand, timing the travel  from the mine dry to the various shovels to measure start up times.  I recall sitting with a stopwatch timing shovel buckets and truck loading times.  Both of these tasks can be done for every shift, every truck by equipping the crew bus and mine trucks with the SedimentIQ tech.
The platform is currently being tested at a couple of trials mines and the founders are looking for more mines willing to adopt and further refine their technology.
The website is https://sedimentiq.com/.

Conclusion

Both of these innovative technologies can provide useful information to open pit and underground mine operations.  They are in the growth stage, looking for wider adoption.   Input from users, whether positive or negative, will assist them with on-going development and enhancements. Their websites obviously have more on what their technology offers, including presentations, white papers, and case studies.
It would be nice to meld these two technologies in some way to allow the SedimentIQ cycle times to also track payloads.
Check them out.  Try them out.  Tell them Ken sent you.

 

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O/P to U/G Cross-Over – Two Projects into One

Over the years I have been involved in numerous mining tradeoff studies. These could involve throughput rate selection, site selection, processing options, tailings disposal methods, and equipment sizing. These are all relatively straightforward analyses. However, in my view, one of the more technically interesting tradeoffs is the optimization of the open pit to underground crossover point.
The majority of mining projects tend to consist of either open pit only or underground only operations. However there are instances where the orebody is such that eventually the mine must transition from open pit to underground. Open pit stripping ratios can reach uneconomic levels hence the need for the change in direction.
The evaluation of the cross-over point is interesting because one is essentially trying to fit two different mining projects together.

Transitioning isn’t easy

There are several reasons why open pit and underground can be considered as two different projects within the same project.
There is a tug of war between conflicting factors that can pull the cross-over point in one direction or the other. The following discussion will describe some of these factors.
The operating cut-off grade in an open pit mine (e.g. ~0.5 g/t Au) will be lower than that for the underground mine (~2-3 g/t Au). Hence the mineable ore zone configuration and continuity can be different for each. The mined head grades will be different, as well as the dilution and ore loss assumptions. The ore that the process plant will see can differ significantly between the two.
When ore tonnes are reallocated from open pit to underground, one will normally see an increased head grade, increased mining cost, and possibly a reduction in total metal recovered. How much these factors change for the reallocated ore will impact on the economics of the overall project and the decision being made.
A process plant designed for an open pit project may be too large for the subsequent underground project. For example a “small” 5,000 tpd open pit mill may have difficulty being kept at capacity by an underground mine. Ideally one would like to have some satellite open pits to help keep the plant at capacity. If these satellite deposits don’t exist, then a restricted plant throughput can occur. Perhaps there is a large ore stockpile created during the open pit phase that can be used to supplement underground ore feed. When in a restricted ore situation, it is possible to reduce plant operating hours or campaign the underground ore but that normally doesn’t help the overall economics.
Some investors (and companies) will view underground mines as having riskier tonnes from the perspective of defining mineable zones, dilution control, operating cost, and potential ore abandonment due to ground control issues. These risks must be considered when deciding whether to shift ore tonnes from the open pit to underground.
An underground mine that uses a backfilling method will be able to dispose of some tailings underground. Conversely moving towards a larger open pit will require a larger tailings pond, larger waste dumps and overall larger footprint. This helps make the case for underground mining, particularly where surface area is restricted or local communities are anti-open pit.
Another issue is whether the open pit and underground mines should operate sequentially or concurrently. There will need to be some degree of production overlap during the underground ramp up period. However the duration of this overlap is a subject of discussion. There are some safety issues in trying to mine beneath an operating open pit. Underground mine access could either be part way down the open pit or require an entirely separate access away from the pit.
Concurrent open pit and underground operations may impact upon the ability to backfill the open pit with either waste rock or tailings. Underground mining operations beneath a backfilled open pit may be a concern with respect to safety of the workers and ore lost in crown pillars used to separate the workings.
Open pit and underground operations will require different skill sets from the perspective of supervision, technical, and operations. Underground mining can be a highly specialized skill while open pit mining is similar to earthworks construction where skilled labour is more readily available globally. Do local people want to learn underground mining skills? Do management teams have the capability and desire to manage both these mining approaches at the same time?
In some instances if the open pit is pushed deep, the amount of underground resource remaining beneath the pit is limited. This could make the economics of the capital investment for underground development look unfavorable, resulting in the possible loss of that ore. Perhaps had the open pit been kept shallower, the investment in underground infrastructure may have been justifiable, leading to more total life-of-mine ore recovery.
The timing of the cross-over will also create another significant capital investment period. By selecting a smaller this underground investment is seen earlier in the project life. This would recreate some of the financing and execution risks the project just went through. Conversely increasing the open pit size would delay the underground mine and defer this investment and its mining risk.

Conclusion

As you can see from the foregoing discussion, there are a multitude of factors playing off one another when examining the open pit to underground cross-over point. It can be like trying to mesh two different projects together.
The general consensus seems to be to push the underground mine as far off into the future as possible.  Maximize initial production based on the low risk open open pit before transitioning.
One way some groups will simplify the transition is to declare that the underground operation will be a block cave. That way they can maintain an open pit style low cutoff grade and high production rate. Unfortunately not many deposits are amenable to block caving.  Extensive geotechnical investigations are required to determine if block caving is even applicable.
Optimization studies in general are often not well documented in 43-101 Technical Reports. In most mining studies some tradeoffs will have been done (or should have been done).  There might be only brief mention of them in the 43-101 report. I don’t see a real problem with this since a Technical Report is to describe a project study, not provide all the technical data that went into it. The downside of not presenting these tradeoffs is that they cannot be scrutinized (without having data room access).
One of the features of any optimization study is that one never really knows if you got it wrong. Once the decision is made and the project moves forward, rarely will someone ever remember or question basic design decisions made years earlier. The project is now what it is.

 

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Are Engineers Too Pessimistic

Geological colleagues have often joked that engineers are a pessimistic lot; they are never technically satisfied. The engineers will fire back that geologists are an overly optimistic lot; every speck of mineralization makes them ecstatic. Together they make a great team since each cancels the other out.
In my opinion engineers are often pessimistic. This is mainly because they have been trained to be that way. Throughout my own engineering career I have been called upon many times to focus on the downsides, i.e. what can happen that we don’t want to happen.

It starts early and continues on

This pessimism training started early in my career while working as a geotechnical engineer. Geotechnical engineers were always looking at failure modes and the potential causes of failure when assessing factors of safety.
Slope failure could be due to the water table, excess pore pressures, seismic or blast vibrations, liquefaction, unknown weak layers, overly steepen slopes, or operating error. As part of our job we had to come up with our list of negatives and consider them all. The more pessimistic view you had, the better job you did.
This training continued through the other stages of a career. The focus on negatives continues in mine planning and costing.
For example, there are 8,760 hours in a year, but how many productive hours will each piece of equipment provide? There will delays due to weather conditions, planned maintenance, unplanned breakdowns, inter-equipment delays, operator efficiency, and other unforeseen events. The more pessimistic a view of equipment productivity, the larger the required fleet. Geotechnical engineers would call this the factor of safety.
In the more recent past, I have been involved in numerous due diligences. Some of these were done for major mining companies looking at acquisitions. Others were on behalf of JV partners, project financiers, and juniors looking at acquisitions.
When undertaking a due diligence, particularly for a major company or financier, we are not hired to tell them how great the project is. We are hired to look for fatal flaws, identify poorly based design assumptions or errors and omissions in the technical work. We are mainly looking for negatives or red flags.
Often we get asked to participate in a Risk Analysis or SWOT analysis (Strengths-Weaknesses-Opportunities-Threats) where we are tasked with identifying strengths and weaknesses in a project.
Typically at the end of these SWOT exercises, one will see many pages of project risks with few pages of opportunities.
The opportunities will usually consist of the following cliches (feel free to use them in your own risk session); metal prices may be higher than predicted; operating costs will be lower than estimated; dilution will be better than estimated; and grind size optimization will improve process recoveries.
The project’s risk list will be long and have a broad range. The longer the list of risks, the smarter the review team appears to be.

Investing isn’t easy

After decades of the training described above, it becomes a challenge for me to invest in junior miners. My skewed view of projects carries over into my investing approach, whereby I tend to see the negatives in a project fairly quickly. These may consist of overly optimistic design assumptions or key technical aspects not understood in sufficient depth.
Most 43-101 technical reports provide a lot of technical detail; however some of them will still leave me wanting more. Most times some red flags will appear when first reviewing these reports. Some of the red flags may be relatively inconsequential or can be mitigated. However the fact that they exist can create concern. I don’t know if management knows they exists or knows how they can mitigate them.
It has been my experience that digging in a data room or speaking with the engineering consultants can reveal issues not identifiable in a 43-101 report. Possibly some of these issues were mentioned or glossed over in the report, but you won’t understand the full extent of the issues until digging deeper.
43-101 reports generally tell you what was done, but not why it was done. The fact I cannot dig into the data room or speak with the technical experts is what has me on the fence. What facts might I be missing?
Statistics show that few deposits or advanced projects become real mines. However every advanced study will say that this will be an operating mine. Many projects have positive feasibility studies but these studies are still sitting on the shelf. Is the project owner a tough bargainer or do potential acquirers / financiers see something from their due diligence review that we are not aware of?   You don’t get to see these third party reviews unless you have access to the data room.
My hesitance in investing in some companies unfortunately can be penalizing. I may end up sitting on the sidelines while watching the rising stock price. Junior mining investors tend to be a positive bunch, when combined with good promotion can result in investors piling into a stock.
Possibly I would benefit by putting my negatives aside and instead ask whether anyone else sees these negatives. If they don’t, then it might be worth taking a chance, albeit making sure to bail out at the right time.
Often newsletter writers will recommend that you “Do your own due diligence”. Undertaking a deep dive in a company takes time. In addition I’m not sure one can even do a proper due diligence without accessing a data room or the consulting team. In my opinion speaking with the engineering consultants that did the study is the best way to figure things out. That’s one reason why “hostile” due diligences can be difficult, while “friendly” DD’s allow access to a lot more information.

Conclusion

Sometimes studies that I have been involved with have undergone third party due diligence. Most times one can predict ahead of time which issues will be raised in the review. One knows how their engineers are going to think and what they are going to highlight as concerns.
Most times the issue is something we couldn’t fully address given the level of study. We might have been forced to make best guess assumptions to move forward. The review engineers will have their opinions about what assumptions they would have used. Typically the common comment is that our assumption is too optimistic and their assumption would have been more conservative or realistic (in their view).
Ultimately if the roles were reversed and I were reviewing the project I may have had the same comments. After all, the third party reviewers aren’t being hired to say everything is perfect with a project.
The odd time one hears that our assumption was too pessimistic. You usually hear this comment when the reviewing consultant wants to do the next study for the client. They would be a much more optimistic and accommodating team.
To close off this rambling blog, the next time you feel that your engineers are too negative just remember that they are trained to be that way.  If you want more positivity, hang out with a geologist (or hire a new grad).

 

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Vertical Conveyors Give Mining a Lift

There are not many things that are novel to me after having worked in the mining industry for almost 40 years.  However recently I came across a mining technology that I had heard very little about.  It’s actually not something new, but it has never been mentioned as a materials handling option on any project that I am aware of.
That innovative technology is vertical conveying. Not long ago I read about a vertical conveyor being used at the Fresnillo underground mine, hoisting 200 tph up from a depth of 400 metres and had a capital cost of $12.7 million.
I was aware of steep angle conveyors being used in process plants.  However they tended to be of limited height and have idlers and hardware along their entire length. Vertical conveyors are different from that.
After doing a bit of research, I discovered that vertical conveyors have been used since the 1970’s.  Their application was mainly in civil projects; for example in subway construction where one must elevate rock from the excavation level up to street level.   The mining industry is taking vertical conveyors to the next level.
I have never personally worked with vertical conveyors.  Therefore I am providing this discussion based on vendor information.  My goal is to create awareness to readers so that they might consider its application for their own projects.

How vertical conveying works

The background information on vertical conveying was provided to me by FKC-Lake Shore, a construction contractor that installs these systems.  FKC itself does not fabricate the conveyor hardware.  A link to their website is here.
The head station and tail station assemblies are installed at the top and bottom of a shaft.  The conveyor belt simply hangs in the shaft between these two points.  There is no need for internal guides or hardware down the shaft.   The conveyor belting relies on embedded steel cables for tensile strength and pockets (or cells) to carry the material.
The Pocketlift conveyor system is based on the Flexowell technology.  This has been advanced for deep underground applications with a theoretical lift height of 700 metres in one stage.   The power transfer is achieved by two steel cord belts that are connected with rigid cross bars. The ore is fed into rubber pockets, which are bolted onto the cross bars.    The standard Pocketlift can reaches capacities up to 1,500 m3/h and lift heights up to 700 m, while new generations of the technology may achieve capacities up to 4,000 m3/h.
The FLEXOWELL®-conveyor system is capable of running both horizontally and vertically, or any angle in between.  These conveyors consist of FLEXOWELL®-conveyor belts comprised of 3 components: (i) Cross-rigid belt with steel cord reinforcement; (ii) Corrugated rubber sidewalls; (iii) transverse cleats to prevent material from sliding backwards.   They can handle lump sizes varying from powdery material up to 400 mm (16 inch). Material can be raised over 500 metres with reported capacities up to 6,000 tph.

 

The benefits of vertical conveying

Vendors have evaluated the use of vertical conveying against the use of a conventional vertical shaft hoisting.    They report the economic benefits for vertical conveying will be in both capital and operating costs.
Reduced initial capital cost due to:
  • Smaller shaft excavation diameter,
  • Reduced cost of structural supports vs a typical shaft headframe,
  • Structural supports are necessary only in the loading and unloading zones and no support structures in the shaft itself since the belt hangs free.
Lower operating costs due to:
  • Significantly reduced power consumption and peak power demand,
  • Lower overall maintenance costs,
  • No shaft inspections required,
  • The belt is replaced every 8 – 10 years.

Conclusion

I consider vertical conveying as another innovation in the mining industry. There may be significant energy and cost benefits associated with it when compared to conventional shaft hoisting or truck haulage up a decline.
With raise boring, one can develop relatively low cost shafts for the vertical conveyor.  Hardware installation would be required only at the top and bottom of the shaft, not inside it.
The vendors indicate the conveying system should be able to achieve heights of 700 metres.  This may facilitate the use of internal shafts (winzes) to hoist ore from even greater depths in an expanding underground mine. It may be worth a look at your mine.
As stated earlier, I have no personal experience with vertical conveying. Undoubtedly there may be some negative issues associated with the system that I am currently unaware of.
I would appreciate anyone sharing their experience with these conveyors either in a civil application or a mining environment.   I will gladly update this blog article with additional observations or comments.
Update: for those interested in open pit applications for high angle conveyors, here is a recent article.  This is a 37 degree angle 3,000 tph sandwich belt, which is different than the vertical conveyors discussed above.
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