Articles tagged with: Mining

The Double Life of Inferred Resources: Now You See It – Now You Don’t

Date: April 18, 2026 Author: Ken Kuchling Comments: Leave a reply
There is a unique paradox sitting at the heart of how the mining industry evaluates its projects. It’s called the Inferred Resource—now you see it, now you don’t.
A company can publish a Preliminary Economic Assessment (PEA) showing a mine life, a robust internal rate of return, and a strong net present value. That study can be based on mineral resources that regulators consider too geologically uncertain to support a production decision. These are the infamous Inferred resources: tonnes, grades, and dollars in the economic model, yet with a classification that effectively flags them as educated guesses. The PEA rules permit their inclusion because early-stage projects need a way to test whether chasing more resource certainty is worth the additional cost.
The paradox occurs when that same project advances to the pre-feasibility (PFS) or feasibility (FS) stage. Suddenly the Inferred ore tonnes are gone; they are now waste rock. The mine plan must be based on more certain Measured and Indicated resources. Theoretically, the life-of-mine production profile that looked compelling in the PEA may now shrink—so the NPV and IRR might shrink too. Nothing has gone wrong in any technical sense. The project simply requires a higher standard of certainty now.
Potentially, some investors who focused on the PEA economics may feel the subsequent feasibility study is a disappointment (especially if costs have also escalated). They’ll say the PEA is garbage. In reality, the project has moved from an aspirational study (i.e., the PEA) toward a bank-financeable study.  To compensate for the loss of Inferred material, companies will rely of step out drilling to grow the resource to maintain size.

What Are Inferred Resources?

Inferred resources represent the lowest confidence category of mineral resources; typically estimated in zones with limited sampling and unconfirmed geological continuity. They carry the highest geological uncertainty of the three resource categories.
In Preliminary Economic Assessments (PEAs), Inferred resources are allowed—but only under certain conditions:
  • They can be included in mine plans and economic models, which is the reason PEAs exist: to allow early-stage projects to test economic viability using all available resource data.
  • However, any PEA that includes Inferred resources cannot be used to support a production decision and must carry prominent cautionary language. Under NI 43-101, the technical report must explicitly state that the PEA is preliminary in nature, that Inferred resources are too speculative geologically to have economic considerations applied, and that there is no certainty the PEA will be realized. (It seems a PEA without Inferred resources can be used to support a production decision.)
  • Inferred tonnes are routinely used to extend mine life or improve project economics in PEA studies. Investors must understand this risk and should examine the proportion of mined tonnage that is classified as Inferred. This breakdown is normally presented in the Technical Report.
Conversely, in Pre-Feasibility Studies (PFS) and Feasibility Studies (FS), the rules for Inferred material are different:
  • Inferred resources cannot be included in mineral reserve estimates or in the economic analysis underpinning a PFS or FS. Inferred “ore” is treated as waste rock.
  • Only Indicated and Measured resources can be converted to Probable and Proven mineral reserves.
  • Including Inferred material in a PFS mine plan would typically disqualify the study from being used for project financing or a production decision.
  • Some companies might include Inferred material in a PFS as “upside” or as a sensitivity case, but that analysis must be clearly distinguished from the base case.
The resource upgrade requirement (from Inferred to Indicated) creates some interesting dynamics:
  • Companies may need additional funds to drill sufficiently to upgrade the resource before advancing to the PFS/FS stage. The cost and time for this infill drilling can be a major driver of exploration spending and can delay project timelines. Mining projects can take a long time to develop, and this is one reason why.
  • Companies will look at ways to compensate for the Inferred material deduction.  Cutoff grade changes and step out drilling are ways to mitigate this impact.
  • A large Inferred resource that cannot be upgraded without great cost (due to depth, remoteness, or lack of ore-zone continuity) can permanently stall a project at the PEA stage. Hence, one may see multiple PEAs completed on the same project (i.e., the PEA loop).
  • In closing, the peculiarity of the Inferred resource is that it is essentially a tiered permission structure. Inferred resources are useful for early economic screening, but they must be converted to higher-confidence categories before they can support a bankable study or project debt financing.

Permitting via a PEA

Companies sometimes will commence the permitting process based on their PEA study. There are some risks to doing this, and the Inferred resource creates one of these risks.
With limited capital, a junior miner may not be able to afford the $5–20 million cost of a full feasibility study before determining whether a project is even permittable. A PEA, costing a fraction of a FS, can provide enough technical substance to engage regulators and begin the environmental baseline work that must precede any formal permit application.
Baseline studies for hydrology, ecology, and air quality typically require two to three years of data collection. So starting early makes sense, even with only a PEA-level project layout in hand.
Permitting and ongoing technical study work will run in parallel on most projects. Waiting for a completed FS before starting permitting would add years to the project timeline. Companies routinely will concurrently advance environmental impact assessments, indigenous consultation, and baseline data collection with subsequent PFS and FS work.
Jurisdiction may play a role too. Some areas are more receptive to early-stage permitting engagement. Other permitting processes may be more rigorous such that operators want at least a PFS in hand before committing to a full EIA process.
Now, with respect to the Inferred resource, the risk is that a project permitted around a PEA-scale footprint may shrink in size at the feasibility stage. Some reasons for this size reduction will be discussed in a future blog post, as well as the ways companies avoid this with ever increasing ore tonnage. Project shrinkage can result in a company acquiring permits and bonding for a proposed mine plan that no longer exists.

How Can Inferred Resources Affect Permitting

Let us examine some specific aspects of permitting that can be influenced by Inferred resources.
1. Project Footprint and Disturbance Area: Permits are issued for a defined physical footprint, consisting of pit limits, waste dumps, tailings facilities, and infrastructure corridors. If a PEA mine plan is inflated by Inferred tonnes and defines a large footprint versus the feasibility study, the company faces a choice:
(a) Permit the smaller FS footprint and risk under-permitting if Inferred is later upgraded. Requesting future permit modification for a suddenly larger project is sometimes viewed by regulators as “permitting by stealth”.
(b) Permit the larger PEA footprint to provide flexibility, which may trigger more extensive environmental review and higher bonding requirements.
2. Environmental Impact Assessment (EIA) Scope & Cost: A mine plan that includes Inferred material:
– May define a larger disturbance envelope, larger waste dumps, larger tailings facility, all of which require assessment of broader habitat, hydrology, and community impacts. Perhaps the project must advance into a new watershed. This can add permitting cost and time. If the Inferred material is later excluded, the assessment work may have been unnecessarily extensive.
3. Tailings and Waste Facility Sizing: Tailings storage facilities (TSFs) and waste rock dumps are sized to the life-of-mine tonnage. Inferred tonnes included in a PEA can drive facility sizing significantly. Permitting a TSF for a larger tonnage is:
– More difficult and time-consuming to obtain if the height and footprint increase
– Will be subject to more rigorous dam safety and closure review- However this could be potentially beneficial if the Inferred resource is later confirmed during mining
Conversely, I have seen situations where permitting was done on the pre-feasibility level design, thereby excluding Inferred ore from the plan. The operability of a planned co-disposal waste facility relied on relative ratios of clean waste rock, acid generating rock, and tailings. During production, the conversion of Inferred material from “waste” to “ore” would mean more tailings, less waste rock, and could shift the required material balance for co-disposal in a negative way. Permitting based on a PEA might make more sense here.
4. Financial Assurance and Reclamation Bonding: Regulators require bonds or financial assurances sized to the cost of full site reclamation. A larger mine footprint driven by Inferred tonnes means:
– Higher bonding requirements
– Larger financial burden on the company during the project development phase
– Potential difficulty for junior companies in securing bonds for Inferred-inflated footprints that have not been proven out yet.
5. Water Licences and Discharge Permits: Water use and discharge volumes scale with throughput and mine life. A longer mine life driven by Inferred tonnes may require expanded water licences. If those tonnes are later excluded, the licence may be oversized. Keep in mind that obtaining an amendment to increase a water licence later can be harder than acquiring a larger one initially, so there is a trade-off here.
6. Indigenous and Community Consultation: In jurisdictions with consultation requirements (Canada’s duty to consult, FPIC principles, etc.), the scope of consultation is tied to the project’s impact footprint and duration. A mine life extended by Inferred tonnes:
– Triggers consultation over a longer operational period
– May affect benefit agreement negotiations (royalties, employment commitments) tied to mine life or total tonnage
– If mine life subsequently shrinks at FS stage, it can create credibility and trust issues with communities who were counting on a longer mine life.
In closing, personally I feel that project proponents should try to permit to a footprint somewhat larger than the Pre-Feasibility base case to preserve operation flexibility. For more on the benefits of flexibility, see the blog post “Mining’s Obsession with Optimization – Good or Bad”.

Conclusion

Inferred resources present a unique paradox; they can and can’t be used in mining economic analysis. They can be used to examine project viability but can’t be used to make a production decision.
The manner in which Inferred resources are viewed can also affect permitting. Although they don’t directly enter the regulatory process, they can shape the physical parameters of the mine plan that regulators will evaluate.
Even if a company grows the resource size between the PEA and PFS, there will still be a component of Inferred material within the PFS mine design that might be considered real tonnage or not.
Getting the permitted footprint right relative to the eventual resource confidence level is an underappreciated skill in project development. Each mining project is unique, and there is no easy one-size fits all solution when considering the impact of Inferred resources on project development.

 

In case you missed it, the last blog post was ” Mining’s Obsession with Optimization – Good or Bad“. https://kuchling.com/minings-obsession-with-optimization/ The entire blog post library can be found at https://kuchling.com/library/
You can sign up for the KJK mailing list to get notified when new blogs are posted. Follow me on LinkedIn or Twitter (@KJKLtd) for updates and other mining commentary.
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Mining’s Obsession with Optimization – Good or Bad?

Date: March 31, 2026 Author: Ken Kuchling Comments: Leave a reply
You read a lot these days about the push for more optimization in mining. Ore grades are declining and high-grade, easy-to-process deposits are becoming scarcer, forcing new projects to face greater risk. To compensate for this, miners are told to optimize and innovate more. They are doing both; including making technological gains.
Mining has gotten better at squeezing more value from each tonne of ore. So why do see mining projects still stumbling and everyone being pushed to do even more optimization?
The answer may be that the industry is confusing optimization with resilience. A mine tuned to perform perfectly under one set of conditions may become fragile when those conditions shift. And in mining, things are always shifting. Maybe the head grades don’t meet expectations or metal prices collapse. Maybe there is a shift in community sentiment or a geotechnical surprise in the mine.
The pursuit of a single “optimal” outcome might leave projects well engineered, yet poorly equipped for reality. Flexibility (or resiliency) aren’t the enemy of efficiency; they may be the only way to make efficiency sustainable.

Which Aspects Should Be Optimized

Is the concept of optimization the most important factor in a project’s design? If so, which aspect is the most important to optimize? A danger is optimizing for a single criteria, for example NPV, at the expense of everything else. Selecting the optimal design for one aspect will likely result in being sub-optimal in some of the others.
Once one has selected the aspect to optimize, the next issue becomes what to base the optimization on. Optimization typically is founded on a specific set of inputs. When these change, the optimized design will likely require revision. This then forces a new optimization, which can create a never-ending optimization loop because things are always changing in mining.
The design aspects that I have seen recommended for optimization range from:
  • optimize your drill hole locations
  • optimize your pit size
  • optimize your production schedule
  • optimize your throughput and/or recovery
  • optimize your water consumption
  • optimize your carbon footprint
  • optimize your project design
  • optimize your labour productivity
  • optimize either NPV, IRR, or payback
  • optimize your metal production cash cost
There are a lot of suggestions and recommendations and people will have differing opinion on which are the most important optimizations. This opinion is typically driven by their own expertise or field of work, not necessarily by what is best for the project.

Optimal vs Resilient Design

Optimization of a mining project can yield meaningful cost and efficiency gains. However mines face inherent constraints, such as ore grade variability, geological surprises, equipment life cycles, and regulatory issues.
Company success is typically driven by a broader set of variables: commodity price cycles, capital availability, asset portfolio quality, ESG and social license, M&A timing, and balance sheet strength. A perfectly optimized mine in a declining commodity or in a politically unstable jurisdiction may underperform a less-optimized mine in the right location at the right time.
Chasing optimization can sometimes lead to over-investment in a single asset, reduced flexibility, or operational fragility. The system performs well only under the ideal conditions.
Hence flexibility is important. If the mine plan is so rigid that it cannot pivot when a new high-grade zone is discovered or a pit wall becomes unstable, then one has optimized for a single scenario rather than for long-term resilience. Rather than designing for the “best case,” design for resilience.
Flexibility builds in the ability to scale production up or down, switch mining sequences, or pivot processing approaches as conditions change. Resilience has real value in mining, where geology, markets, and costs are unpredictable.
Flexibility identifies and can mitigate technical, geopolitical, regulatory, environmental, and market risks. The mines that do run into trouble rarely do so because they weren’t optimized; they fail because key risks weren’t anticipated or managed.
Workforce capability, safety culture, and leadership quality are key predictors of operational success. Optimization alone may not be able to address high turnover, poor safety records, and weak supervisory capacity. These can erode profitability far more than sub-optimal scheduling.
In my experience, the best operations have systems for ongoing learning and improvement rather than seeking a one-time optimal design. However, there is still a place for full optimization in some situations.
When does a flexible project design win?
  • Commodity prices are volatile up and down
  • Geological uncertainty is high (low proportion of Measured Resource)
  • Mining uncertainty (limited geotechnical investigations)
  • Long mine life (10–30+ years), where conditions will certainly change
  • Regulatory or social environments are unpredictable
  • Capital markets may require staged investment rather than full financing
When does an optimal project design win?
  • Shorter mine life where conditions are unlikely to change materially
  • Commodity is stable, well-hedged, or under long term offtake contract pricing
  • Geology and processability is well-understood (mature, well drilled-out deposit)
  • Capital is constrained and upfront efficiency is critical (you need to get it right)
Unfortunately some might view flexibility as a weakness.  If a company has to change a plan or pivot, some will view that as a sign that the company is poor at planning and they don’t know what they are doing.   In some cases, this might be true.  Conversely the company may simply be reacting to unforeseeable outside influences.

The Path to Resiliency

If one decides to pursue the path of operational flexibility, what are the things that help make it happen?
  1. Design for flexibility at the start: Build project components that can scale up or down as needed. This might include wider pit ramps, larger infrastructure, some modularization in the processing system and the mine. Building a single rigid optimal design can be a trap. Open pit mines may be inherently more flexible than underground mines.
  2. Maintain multiple ore sources: Maintain flexibility across different mining areas and ore zones with different metallurgy or head grades means one can blend ore as needed. Multiple mining areas provide flexibility in the case of geotechnical or weather events. Multiple stockpiling is also part of flexibility in design and operation.
  3. Be careful consuming all high grade ore:  In order to boost NPV, often most of the high grade ore is consumed early in the schedule, meaning the back part of the schedule relies on low grade material.   This reduces economic flexibility if prices decrease in the future and may also miss out on the benefits if prices rise.
  4. Real-time data collection and adaptive planning: Real time control systems let operations respond to actual conditions rather than following a fixed weekly plan. The idea is to shorten the time between observation and reaction, not to automate rigidly but enable the system to adapt rapidly.
  5. Keep a cross-trained workforce: Operational flexibility may be enhanced if people can fill multiple roles. Cross-training operators means one can redeploy people as needed when conditions change.
  6. Maintain financial health: A company with low debt, high cash assets, and easy credit access can keep a mine on basic functionality (or care-and-maintenance) rather than being forced to sell assets or close the doors during a downturn. Financial health will help ensure operational flexibility. The major miners already know this. The junior miners learn it the hard way.
  7. Build supplier and contractor relationships before needed: Much like access to credit, long-term supplier arrangements might mean one can find labor and materials faster than competitors scrambling during downturns or upturns.
  8. Scenario-plan continuously: Run multiple what-if commodity price, head grade, geotechnical & water management scenarios regularly during operations, not just at the feasibility or permitting stage. Operations change over time, and teams that have already pre-planned “what if this happens” respond better when it really happens.
Flexible mining operations may sacrifice a little efficiency at peak conditions and not meet the fully optimized vision. However this flexibility is a trade-off for the ability to stay profitable over a range of scenarios.

Conclusion

Rather than focus on constant optimization in design, it may be wiser to focus on a flexible design. Adaptability, flexibility, and resilience may be more important than being fully optimized.
Modern mine planning is starting to consider Real Options Analysis and stochastic optimization (Monte Carlo simulation) to help quantify the value of flexibility. They may find that a slightly suboptimal design is actually worth more than a rigid optimized one when uncertainty is priced in.
Probabilistic analysis can provide some assistance by highlighting the impact of unforeseen events. However the key is not just to know the event’s impact, but also how will one respond even if there is only a 10% probability of it occurring.
Optimization may be great, but it isn’t everlasting. Squeezing the last dollar out of a plan may be less important than keeping a mine in business. A flexible plan may actually be the optimal plan.
*end*
In case you missed it, the last blog post was “The Surprising Parallels Between Junior Miners and Tech Startups“. The entire blog post library can be found at https://kuchling.com/library/
You can sign up for the KJK mailing list to get notified when new blogs are posted. Follow me on Twitter at @KJKLtd for updates and other mining posts.
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The Surprising Parallels Between Junior Miners and Tech Startups

Date: March 22, 2026 Author: Ken Kuchling Comments: 2 Replies
Recently I’ve seen a few LinkedIn conversations about whether the mining industry is spending enough money on Research and Development (R&D). Usually when one thinks of R&D, one might envision the development of new technology, new drug, equipment or software.
I would suggest that mineral exploration should be viewed through the R&D lens. Exploration (or acquisition of explorers) is the most significant way that the industry can self-manage to grow revenues. If exploration is R&D, that then leads to the observation that Junior Miners are the precursors for today’s Silicon Valley startups.
Before venture capital and “startup culture” became a phenomenon, junior mining companies were already operating on the startup core principles. Small, capital driven explorcos were based on unproven assets, led by specialized technical teams. They were funded by investors accepting risk in the hopes for 10 bagger or 100 bagger upsides. This is effectively the same business model that Silicon Valley would build upon.
This blog post examines whether the junior mining industry was a leader in Tech Startup culture. Even things like the Lassonde Curve and the PEA have their comparables in the current tech world.

Are Junior Miners precursors to Tech Startups

Junior mining companies and Tech Startups share numerous similarities, although they operate in very different worlds. The following comments should recognize that junior mining ecosystem has been around for generations, long before the birth of tech ecosystems.
Junior mining companies and Tech Startups are both high-risk, high-reward ventures. Junior Miners and Tech Startups are early-stage companies where the vast majority fail. Investors accept enormous risk in exchange for the possibility of enormous returns if a discovery or product is a resounding success. Lets look at some of the similarities.
  • A startup spends years (and millions of dollars) building an MVP (Minimum Viable Product). If the market doesn’t want it or the tech fails to scale, the company goes to zero. Similarly if holes don’t hit or the metallurgy is too complex, the mining asset can face significant headwinds.
  • Both mining and tech are essentially “concept” or “pre-revenue” gambles. A Junior Miner typically has no producing mine, just exploration assets and the dream of an economic mineral deposit. Similarly, many Tech Startups have no revenue, just a product idea or some early traction. Investors in both cases are betting on the team and its future value, not on the non-existing cash flow.
  • Both burn through cash (lots of it) before generating revenue. Mining juniors need constant financing rounds (placements) to fund exploration; startups need financing rounds for R&D and growth. Neither can easily self-fund, although bootstrapping is more common in tech than in mining. Both may rely on exit strategies consisting of acquisition from larger industry players.
  • Both generate proprietary data. A Junior Miner’s most valuable asset is often its geological data (drill results, resource estimates, land tenure). A Tech Startup’s asset is its IP, code, or trade secrets. In both cases, the assets are largely intangible until proven economic.
  • Both rely on quality founders and management. A small, skilled team can make or break the company. A geologist or executive with a great track record (“the Midas touch”) is analogous to a serial tech founder. Often the investors are backing the person more than the project.
  • Both sectors are heavily sentiment-driven (mining likes 2025, tech not so much). A hot commodity cycle floods junior mining with capital. A hot tech cycle (AI, crypto, SaaS) floods startups. When investor sentiment reverses, funding dries up fast and many companies are left to die, possibly to rise again in the next cycle.
  • Both sectors can follow the “Lassonde Curve” (mining) or the “Hype Cycle” (tech). There is an initial surge of excitement during discovery/launch, followed by a “boring” period of technical de-risking (development/user acquisition), and finally a re-rating once they reach production or profitability. (More on the Lassonde Curve later in this blog post).
  • Both sectors require pitching their story to investors. The Tech Startups rely on pitching to angel investor via shows like Shark Tank, pitch summits (t) using 5 minute elevator pitches (“get to the point” pitches). The Junior Miners rely on the numerous mining conferences like PDAC, Mines & Money, Beaver Creek, Zurich, again relying on the PowerPoint pitch to gather eyeballs.
Obviously we should also point out there some differences between juniors and Tech Startups.
  • Juniors work with physical geological reality. You either find the ore body or you don’t. Startups can pivot; geology can’t.
  • Mining has far longer timelines; discovery to production can take 10–20 years vs. a startup’s typical 5–7 year VC cycle. Any longer than that, and a Tech Startups technology can become obsolete.
  • Regulatory, environmental permitting, and social license is a constraint for miners with no real startup equivalent. Viable exploration projects can get blocked through no fault of the miner itself.
  • Junior Miners are more commodity-price dependent. Even a great deposit can be uneconomic at the wrong metal price. Conversely a miner’s asset could become more valuable over time based on metal prices. Tech startup do not rely on a commodity price outside their control.
  • Junior Miners tend to rely on public capital markets for financing right from the start, although the trend toward private equity mining investment may be increasing. Conversely, at early stages, Tech Startups tend to be bootstrapped and financed via private equity, venture capital, and angel investors. Junior Miner investments can provide more liquidity and exit opportunities due to their public listing. Tech investors may be locked in until a liquidity event occurs.
  • The startup world will label their financing rounds (seed, Series A, Series B,..) with the hope that future investors provide financing at higher valuations than earlier investors.   The mining industry does not label their placement rounds – perhaps they should.
In conclusion, an analogy between Junior Miners and Tech Startups can help outsiders understand the risk, capital structure, and investor behavior of both industries. One might conclude that Junior Miners were the Tech Startups of decades prior, and are still functioning that way today.

Should exploration expenses be considered R&D

Exploration spending shares some of the same characteristics of more commonly R&D.
R&D is uncertain in outcome, generates intellectual property (geological data, resource models), and is expensed before any revenue is realized. A pharma company doesn’t know if a new drug will be a win, similarly a Junior Miner doesn’t know if a drill program will yield an economic deposit. Both activities are investments in discovering something of future value, hopefully.
R&D is about de-risking a concept, and de-risking is a term commonly used by Junior Miners. Every drill hole, soil sample, and geophysical survey is a data point that builds knowledge, and even uneconomic drill holes provide value by focusing the search area.
Much like our drug development example, exploration has a high-failure, high-reward path. Early-stage “lab work” (geochemistry/geophysics) leads to “clinical trials” (core drilling) and eventually “commercialization” (feasibility and production).
There are also some differences between exploration and conventional R&D. R&D will typically create proprietary intellectual property, like a new drug or software platform that can be replicated and marketed globally. A mineral discovery is a unique, non-replicable physical asset in a given location. R&D in tech is about creating something from nothing (innovation), while exploration is about finding something that already exists (discovery).
Exploration also tends to be more binary since it is geologically constrained. You either find an ore body or you don’t. You can’t modify or pivot with an orebody. On the other hand, drug and software R&D can yield partial successes or new technologies, that may have other applications.
Although there are both similarities and differences, the analogy is interesting. Exploration may be considered as a hybrid since it has the uncertainty and knowledge-creation aspect of R&D, but the result is a unique physical asset and not IP. In my view exploration is equivalent to R&D.

Lassonde Curve vs Hype Cycle Curve

As mentioned previously, junior mining and Tech Startups will follow a cyclic path of hype and despair. In mining it is known as the “Lassonde Curve” and in tech its called the “Gartner Hype Cycle”. Let’s look at the similarities. Which came first?
The Lassonde Curve is the “elder” of the two models, predating the Gartner Hype Cycle by about a decade. I had written a previous blog post on this at Mining’s Lassonde Curve – A Wild Ride.
The image below shows them side by side, and they do look similar. While both charts effectively track the “rollercoaster” of investor psychology and technical de-risking, they emerged from different eras and industries. Both charts have a x-axis that represents time and both have a y-axis that represents expectation ( stock price can be viewed as a measure of expectation).

1. The Lassonde Curve (developed in late 1980s)
Created by Pierre Lassonde, the legendary mining financier and co-founder of Franco-Nevada. The model explains the life cycle of junior mining stocks to investors, explaining why sometimes investors get burned after a discovery even if the project is technically sound.
2. The Gartner Hype Cycle (developed in 1995)
Created by analyst Jackie Fenn at the technology research firm Gartner to help clients distinguish between the “hype” of a new technology and its actual commercial maturity. The model guides corporate IT departments on when to invest in new technologies (e.g., AI, Cloud, VR) without getting burned by the “Peak of Inflated Expectations.”
Does the Gartner HC model use the earlier Lassonde Model as a template? Both models show that humans tend to over-speculate on “newness” (whether it’s a drill hole hit or a new technology) and then lose interest when the hard work begins. It seems that Pierre Lassonde mapped that human behavior a few years before the tech world did. In this aspect, the understanding of investor behavior in junior mining was leading the way for Tech Startup behavior.

 

Is a PEA Study Like a Tech Product Market Fit (PMF) Study

Another similarity between junior mining and tech world is in the way early-stage viability is assessed. This is required to decide whether millions of dollars of further investment is warranted. Miners will complete a PEA. Startups will complete Product-Market Fit research.
A Preliminary Economic Assessment (PEA or scoping study) is an early-stage technical and economic evaluation of a mineral deposit. Its core purpose is to determine whether a project is potentially viable before committing significant capital to more advanced studies.
Product-Market Fit (PMF) research for a Tech Startup is a structured effort to determine whether a product satisfies a strong market demand. The goal isn’t just to confirm PMF exists; its to understand the who, why, and how it will work before committing to aggressive growth.
Comparing a Preliminary Economic Assessment (PEA) to a Tech Startup’s Product-Market Fit (PMF) stage is a great way to see how both industries similarly “de-risk” an idea before committing big money.
In both worlds, this is the moment where one stops saying “We have a cool idea or a nice deposit” and start saying “We have a viable business.”
1. The “Does This Thing Actually Work?” Test
– Tech (PMF): Once the team has built a beta, they can see if people are using it and are willing to pay for it. They need to prove there is a market for the tech.
– Mining (PEA): The team has found a deposit. The PEA is the first time they can put a dollar sign on it. It’s a conceptual study that predicts “If we build a mine here with these current economic inputs, it should make money.”
2. The Shift from “Geology” to “Economics”
Just as a Tech Startup shifts from coding to customer acquisition cost (CAC), a Junior Miner shifts from geology to metallurgy and CAPEX.
– Tech: It doesn’t matter how good the code is, if it costs >$50 to acquire a customer who only spends $5 it will not be a viable venture.
– Mining: It doesn’t matter if you have 2 million ounces of gold if the rock is difficult to process or if the project costs billions to build. The PEA is the first reality check on these costs.
3. Attracting the Investors
The PEA / PMF stage may be the ultimate gatekeeper for many institutional capitalists.
– Tech: Once you deliver a PMF, Venture Capital (VC) firms may be more willing to provide growth capital to scale the business.
– Mining: Once a positive PEA is released, the company may see a “re-rating.” Larger funds and mid-tier miners may start looking at the project as a real asset rather than just a speculation.
In closing, It is important to remember that both PEA / PMF stages are still early. A tech company with PMF can still be crushed by a competitor or a change in regulatory or platform privacy requirements. A mining project with a PEA can still fail if the Pre-Feasibility Study (PFS) reveals that the environmental permitting or economic factors are not as expected. Neither early stage study is a guarantee for future success, which is another similarity between the two sectors.

Conclusions

There are many parallels between Junior Miners and Tech Startups. The similarities are in how they are built, how they function, and how they acquire funding.
In that way, exploration expenditures can also be viewed through the lens of R&D spending. So it may be improper for some to suggest that the mining industry is not spending enough on R&D, when it actually is spending huge amounts on R&D.
The Junior Mining industry has been around much longer than the Tech Startup world, and hence have led the way in building an ecosystem for speculative investment.
Is it cool to work in the startup world? The answer is yes if its tech, and (unfortunately) no if its mining.

**end**

In case you missed it, the last blog post was “Beyond the Headline Grade: For or Against Assay Transparency?“.
You can sign up for the KJK mailing list to get notified when new blogs are posted. Follow me on Twitter at @KJKLtd for updates and other mining posts. The entire blog post library can be found at https://kuchling.com/library/
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What Does Ai Think of Toll Milling

Date: February 24, 2026 Author: Ken Kuchling Comments: Leave a reply
I recently noticed a few new mining studies that relied on toll milling as their base case operation. This made me wonder if this is a trend and if there are more examples of where this is happening.
If only there was a way to find out.
I have been tinkering with Ai (mainly ChatGPT and Gemini) to see what it can do, but I never really had a “project” for it to work on.
So I thought, lets see what Ai can tell us about toll milling. This would be an opportunity to test out Claude (AI assistant built by Anthropic) to see what it will deliver. I could ask it a few questions about the concept of toll milling to find out what it would say.
The following blog is the unedited responses that were given to my user prompts. The results, albeit lengthy, are interesting and informative. Let’s dive in.
By the way, this is the first blog post ever where I have applied Ai.

CLAUDE Ai CONVERSATION

USER PROMPT: Can you prepare a list of recent mining studies that used toll milling as the base case.

RESPONSE: Here is a summary of recent mining studies (primarily PEAs and PFS-level studies) that used toll milling as the base case or a key component, based on publicly available information from 2024-2026:
1. RPX GOLD – WAWA GOLD PROJECT (ONTARIO, CANADA) PEA – February 2026
The base case is built entirely around toll milling, with crushed ROM ore trucked to an off-site facility within 150 km for processing into gold dore. No on-site mill or tailings facility is planned, significantly reducing capital requirements. The project sits in the Michipicoten Greenstone Belt near Wesdome, Alamos, and Hemlo operations, all of which offer potential excess capacity.
2. AMEX EXPLORATION – PERRON GOLD PROJECT (QUEBEC, CANADA) Updated PEA – September 2025
Features a two-stage development strategy: a 4-year, 1,000 tpd contract mining and toll-milling operation in Phase 1, followed by construction of an on-site processing plant in Phase 2. The Abitibi region’s numerous operating mills make this approach practical. Initial capex is C$146M, partially offset by C$68.6M in pre-production revenues during the toll-milling phase.
3. CHALLENGER GOLD – HUALILAN PROJECT (ARGENTINA) PFS – 2024/2025
The PFS is structured around toll milling as the path to near-term production, with the study outlining forecast EBITDA of approximately A$221M over a 3-year tolling period at current metal prices. Challenger also executed a binding term sheet with Dolphin Real Assets/Elsztain Group to facilitate processing through a tolling agreement, with the arrangement expected to fund mining, transportation, and processing costs until initial gold revenue is received.
4. SCOTTIE RESOURCES – SCOTTIE GOLD MINE PROJECT (BRITISH COLUMBIA, CANADA) PEA – October 2025
The primary base case is a Direct-Ship Ore (DSO) scenario, but the study prominently presents toll milling at the nearby Premier mill as a significant upside scenario. Under the toll-milling arrangement, the after-tax NPV(5%) rises from C$215.8M to C$380.1M at US$2,600/oz gold – a meaningful enhancement. No formal toll-milling agreement was in place at the time of the study.
5. MAGNA MINING – CREAN HILL PROJECT (ONTARIO, CANADA) PEA – 2024
The PEA incorporates a definitive off-take agreement with Vale Base Metals to process Contact mineralization through Vale’s Clarabelle Mill in Sudbury. This is a firm, contracted toll-milling arrangement rather than a conceptual one, giving the study’s economics a higher degree of confidence in processing costs.
6. AURIC MINING – JEFFREYS FIND GOLD MINE (WESTERN AUSTRALIA) Operational toll-milling program – 2024
While not a formal feasibility study, Auric and joint venture partner BML Ventures executed a contract to toll mill a minimum of 300,000 tonnes of ore through the Greenfields Mill in Coolgardie during 2024. The first stage produced ~9,741 oz of gold at 1.86 g/t, demonstrating the model’s viability for small, high-grade open pit operations lacking on-site processing infrastructure.
GENERAL OBSERVATIONS:
Toll milling as a base case is most common in:
– Early-stage PEAs for junior developers in established mining districts (Abitibi, Michipicoten, Sudbury) where nearby mill capacity exists.
– High-grade, lower-tonnage projects where the capital cost of a dedicated mill is hard to justify at the outset.
– Projects pursuing a phased development path to generate near-term cash flow before committing to full plant construction.

 

USER PROMPT: What are the risks of toll milling plan.

RESPONSE: Toll milling carries several meaningful risks that study authors and investors should consider carefully.
OPERATIONAL & LOGISTICS RISKS
The most fundamental risk is mill availability. A toll miller may prioritize its own ore or other clients during peak periods, leaving your project without processing capacity exactly when you need it. Scheduling conflicts can delay production and erode project economics significantly. Transportation of ore or concentrate over long distances also introduces costs that are sensitive to fuel prices, road conditions, and seasonal access – particularly in remote northern jurisdictions.
COMMERCIAL & CONTRACTUAL RISKS
Toll milling agreements are typically not long-term ironclad contracts, and terms can be renegotiated or terminated. The toll miller holds significant leverage, especially if there are few alternative processors nearby. Processing rates, payable metal terms, and penalty clauses for deleterious elements can all shift unfavorably over time. If no binding agreement exists at the study stage – as was the case with Scottie Resources – the entire economic base case rests on an assumption rather than a firm commitment.
METALLURGICAL RISKS
The toll miller’s circuit is optimized for their own ore, not yours. Differences in mineralogy, grind size requirements, or the presence of penalty elements like arsenic, bismuth, or mercury can result in lower recoveries than modeled, higher processing charges, or outright refusal to accept the ore. Blending your material with the host mill’s feed can also complicate settlement and metal accounting.
FINANCIAL & ROYALTY RISKS
Without ownership of the processing facility, you have limited control over costs. Any increase in the toll miller’s operating costs – energy, reagents, labor – can be passed through to you. Additionally, some royalty structures are calculated on net smelter returns, meaning toll milling charges directly reduce the royalty base and affect third-party obligations.
REGULATORY & PERMITTING RISKS
Transportation of ore across jurisdictions may require additional permits, environmental assessments, or spill containment plans. If the toll mill’s own permits are challenged or its tailings facility reaches capacity, your project could be indirectly affected by regulatory actions aimed at a third party.
STRATEGIC RISKS
Relying on toll milling can delay the development of on-site infrastructure and institutional processing knowledge, which matters if the long-term plan is to build a dedicated mill. It can also make the project harder to finance or sell, since acquirers typically prefer integrated operations with controlled processing costs. Finally, if the toll miller is acquired, restructured, or shuts down, continuity of the arrangement is immediately in question.
In short, toll milling is an elegant solution for reducing upfront capital, but it trades capex risk for a different set of operational, commercial, and strategic risks that need to be carefully managed and clearly disclosed in any technical study.

USER PROMPT: What responsibility does the Qualified Person have in signing off on a study with toll milling.

RESPONSE: The Qualified Person (QP) signing off on a technical study that uses toll milling as the base case carries significant professional and regulatory responsibility, particularly under NI 43-101 in Canada or JORC in Australia.
CORE RESPONSIBILITY UNDER REGULATION
Under NI 43-101, the QP must take responsibility for the technical report in its entirety, or for clearly delineated sections where multiple QPs are involved. The QP must have sufficient relevant experience not just in geology or engineering broadly, but specifically in the type of deposit and the technical aspects being certified – which in a toll milling scenario includes process engineering, metallurgy, and mine economics. A geologist signing off on processing assumptions they are not qualified to assess would be in breach of their obligations.
REASONABLENESS OF ASSUMPTIONS
The QP is required to certify that the study’s assumptions are reasonable and reflect industry best practice. For toll milling specifically, this means the QP must be satisfied that the processing costs used in the economic model are realistic and supportable. If the toll milling rate is based on a verbal understanding or a letter of intent rather than a binding agreement, the QP must disclose this clearly and assess whether the assumed rate is achievable in the current market. Using a stale or unsupported toll rate without disclosure would represent a failure of duty.
DISCLOSURE OF RISKS
The QP has an affirmative obligation to disclose material risks that could affect the project’s viability. A rigorous technical report should explicitly identify the risks associated with toll milling – mill availability, contract uncertainty, metallurgical compatibility, transportation costs – rather than burying them in boilerplate language. Superficial or generic risk disclosure that does not reflect the specific circumstances of the toll milling arrangement would fall short of professional standards.
METALLURGICAL COMPETENCE
If the study relies on recoveries and processing costs derived from testwork conducted on the toll miller’s circuit, the QP must evaluate whether that testwork is adequate, recent, and representative of the ore to be processed. If no testwork has been done on the specific mill to be used, the QP must justify why analogous data is sufficient, and must disclose the uncertainty this introduces. Blindly accepting a recovery assumption without interrogating its basis is a serious professional risk.
INDEPENDENCE AND CONFLICTS OF INTEREST
NI 43-101 requires the QP to be independent in certain circumstances, and to disclose any relationships with the issuer. If the toll miller is a related party or has a financial interest in the project, the QP must consider whether this creates a conflict that needs to be disclosed or whether it affects the reliability of commercial terms assumed in the study.
SITE VISIT REQUIREMENTS
The QP is generally required to have conducted a site visit. In a toll milling scenario, a thorough QP would arguably need to be familiar not just with the mine site but with the processing facility to be used – its condition, spare capacity, metallurgical compatibility, and operational track record. Signing off on processing assumptions for a facility that has never been visited or independently assessed is a professional vulnerability.
PRACTICAL AND PROFESSIONAL CONSEQUENCES
If a study proves materially misleading due to unsupported toll milling assumptions, the QP faces regulatory action from securities regulators, professional discipline from their engineering or geoscience association, civil liability to investors, and reputational damage. Canadian securities regulators have historically taken a dim view of QPs who rubber-stamp economic assumptions without genuine independent verification.
In summary, the QP’s responsibility in a toll milling study is not merely to sign a form – it is to genuinely interrogate the commercial, metallurgical, and logistical assumptions underpinning the arrangement, ensure they are adequately disclosed, and take personal professional accountability for their reasonableness. A QP who treats toll milling as a convenient shortcut to a positive economic outcome without doing this work is exposing themselves to considerable risk.
I asked Claude to create a QP checklist for factors that should be reviewed for a toll milling study.  You can download that file at this link  DOWNLOAD FILE.

CONCLUSION

The results given by Claude are quite thorough and insightful. It’s hard to argue with its observations and conclusions. This research took all of 30 seconds, so I can see it is no longer difficult to become a blog writer. Writing isn’t the challenge; finding interesting topics is.
One toll milling project that Claude did not list was the Galway Metals Estrades Project PEA published February 18, 2026. Perhaps that study was too recent to be familiar with it.
While Claude is not a mining specific Ai platform, there are some that are under development with a mining research focus. Some of these include MineGPT , SureOre.ai, ProspectorAi , and there are probably even more out there.
This area will continue to evolve, and may help mitigate the technical personnel shortage being experienced.
** END**
In case you missed it, the last blog post was “Mine Waste Risk Management – A Step Towards Consistency“.
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Mine Waste Risk Management – A Step Towards Consistency

Date: December 20, 2025 Author: Ken Kuchling Comments: 2 Replies
Every now and then I discover a new technology or platform that I feel can play a key role in the mining industry going forward. I also come across others that, in my opinion, will struggle to gain traction, knowing the industry as I do.
One intriguing platform that has caught my recent attention is related to mine waste risk management. This platform has been in development for a few years but recently reached the commercial launch milestone. The name of it  is the Critical Infrastructure Risk Decision Basis (CI-RiskDB).

It is being developed by a Saskatoon based team at Enviro Integration Strategies and is intending to help manage risks associated with tailings, water, waste rock and heap leach facilities at mining operations. A heap leach pile is not exactly waste, until the leaching process is complete, but these facilities operate under the same types of risk as the other facility types included.
The CI-RiskDB platform has been designed on the risk assessment framework used by Agnico Eagle Mines, and aligned with current global best practices and standards. Agnico has been a co-developer of the back-end processes, and collaborator and reviewer of the platform design all the way along. It certainly helps to have some mine operator input when developing anything new for the mining industry.
Mining industry standardization is something I have always been a big proponent of. My years of undertaking numerous mining due diligences has shown me that the industry has a knack for each company doing things their own way. However, some industry-wide standardization of risk processes might be warranted given the extremely critical nature of tailings dams and other mine site embankments.
Regarding the CI-RiskDB online platform, I was given free demo access. I was able to poke around, examine methodologies, capabilities, and hence get a feel for how the application works. After my brief period of using it, I am in no way an expert on it. However, I can see that likely in less than 8 hours of use (or training) one should become very comfortable with the system functionality.

Benefits of the Platform

In my view, having a single industry platform for critical infrastructure risk management provides several benefits. These are:
• The CI-RiskDB platform provides consistency in the approach used to define and assess risk, which is important given the industry’s issue with employee turnover and lack of experienced technical personnel. A consistent platform will make it easier to accommodate personnel movement within companies and within supporting consultancies.
• The platform provides a complete risk story per site facility (i.e. tailings dam) by quantifying risk relative to other site facilities, and documenting actions to lower risks. This system is designed specifically for geo-infrastructure that rely on geotechnical stability analyses. It requires the users to identify all the ways that hazards, uncertainties, gaps in knowledge and poor quality of work can introduce risks to the facility.
• The CI-RiskDB platform provides a basis for both a risk assessment (risk ranking) and a Level of Practice (LOP) or maturity assessment. The LOP was something I personally had never heard of before. The LOP assessment represents a way to identify, quantify, and mitigate the numerous uncertainties one has in the design and operation of a mining facility.
• The platform can provide a repository for all documents pertaining to the facilities, linked directly to actions and risks they are related to, and other system knowledge such as actions status and progress, history of changes over time, and who made the changes and updates. It is then possible to find all relevant information in one place, including design reports, review board notes, construction records, performance and monitoring reports. This can be a time savings for all involved, and can support audits, training, onboarding.
• There will be a paper trail for the risk evaluation process, by documenting who provided input, rationale for the input, who did the review and final signoff on the risk scores.

Site Information Structure

The CI-RiskDB platform assesses risk management down to the level of the cross-sectional stability analysis. It subdivides a site down into various operational levels.
SITE ==> FACILITY ==> INFRASTRUCTURE ==> CROSS-SECTION
Each mine site is unique with its own set of “Facilities”. For example, the individual Facilities could include Tailing Management Area #1, TMA #2, the Heap Leach Pad, Waste Dump #1, Waste Dump #2, etc.
Each Facility can then be further subdivided into separate “Infrastructure”. For each Facility these could include (for example) a North Dam, a South Dam, an East Dam, etc.
Each Infrastructure item can be further classified into separate stability Cross-Sections. For example, the North Dam may have a section 10 metres high and another section at 50 metres high.  Perhaps some stability analysis is done at peak shear strength and others using residual shear strength. The stability analysis for each cross-section will be different with unique factors of safety, unique Level of Practice (LOP), and therefore resulting in a unique probability of failure.

Risk Quantification Criteria

The CI-RiskDB platform follows a typical, but adaptable, risk evaluation approach of:
Risk Score = (Probability of Failure) X (Consequence of Failure)
The Probability of Failure is derived from Factor of Safety calculations modified by a Level of Practice score. The Level of Practice (LOP) is a measure of the integrity and quality of data used to design and manage a mine facility. A dam with a Factor of Safety of 1.2 will have a different Annual Failure Probability depending if the design & operation are highly credible (a high LOP) versus a design & operation based on limited field data and technical rigor (low LOP).
For example, by improving operating management or monitoring systems, one may reduce the Probability of Failure without changing anything in the design of the dam itself.
The Consequence of Failure score is derived from scoring on the four factors listed below. Each is scored on a scale of 1 to 5. The overall Consequence Score for the risk evaluation is based on the maximum score of the four factors
  1. Health and Safety
  2. Material damage
  3. Environment
  4. Community
Note that the risk categories, definitions, and score settings are adaptable based on a company’s existing risk matrices. This way a company does not need to implement an entirely new system, other than using the CI-RiskDB platform to help manage their information and risk assessment workflow.

Level Of Practice (LOP) Evaluation

The Level of Practice (LOP) is a measure of the integrity and quality of data used to design and manage a mine facility. The CI-RiskDB platform currently uses 45 criteria to evaluate the LOP associated with a facility. For example, these quality criteria include items such as: current understanding of soil profile; testing & verification between lab and field investigations; stability analysis detail; construction QA/QC undertaken, monitoring programs, etc.
The 45 criteria used for the LOP are categorized into six main categories. They are:
  • Design – Investigation (9 criteria)
  • Design – Testing (6 criteria)
  • Design – Analysis & Documentation (8 criteria)
  • Construction (8 criteria)
  • Operation & Monitoring (10 criteria)
  • Performance (4 criteria)
While not all 45 criteria apply to every facility or Infrastructure, the fact that 45 criteria are defined helps ensure a consistent LOP evaluation process.
Each facility receives an overall LOP score based on 1 to 4 rating for each criteria. As well, the basis for each criteria score is documented, reviewed, and signed off by relevant persons. This provides a documented process that endures despite changes in technical or management personnel.
The LOP score is at a snapshot in time and will evolve as measures are implemented to address areas that were lacking in technical rigor.

Example Output

The following are some example outputs from the CI-RiskDB platform.

Path to Successful Implementation

Tailings ponds and waste rock dumps are mine facilities that can impact the public far beyond the boundaries of the mine property limit. These facilities need to be taken seriously. Adoption of a platform like CI-RiskDB would move towards enhancing mining industry consistency in risk management.
The selection of individual scores will still be of a subjective nature when deciding what practices are good or poor quality, or whether sufficient rigor was applied to controlling risks. There is also the possibility of people assigning low consequence ratings where high consequence impacts might be possible.
Over confidence of personnel is something that can unfortunately play a role in risk management. However, the more eyes involved with reviews and signoffs, as well as occasional third party audits, the less likely that this occurs (hopefully).
If a company wishes to successfully implement the CI-RiskDB platform, it will need to make certain time commitments.
1. The company should treat the platform like a collective “diary” about their facilities, ensuring a full onboarding of all past information and reports and a thorough set of evaluations to start.
2. They will need to infill any risk-based information already known, and to have team members add insights about their own knowledge and observations over time. At the least, those involved with the facility must gradually add their knowledge that would otherwise remain “in their heads” or on their personal computers.
3. Companies must then continue to use the platform to record observations, upload performance reports and inspections, other relevant reports, and to update progress on actions and changes in conditions or issues tied to risks. The idea is to move the team away from relying on personal folders and emails, giving everyone involved access to information.
4. Companies must use the built-in governance protocols by running reports to understand what updates and changes have been made over time. Compare the number of actions added versus closed out over a specified period. Is progress being made? Compare the status of performance and risk progression over time and use this to demonstrate action for external audiences.
The CI-RiskDB platform will not maximize its value if a company is unable to make these types of commitments.
Conclusion
In closing, as of this month December 2025, I understand the Critical Infrastructure Risk Decision Basis platform is currently being piloted and implemented at a number of mine sites in Canada, including Agnico Eagle at a corporate level. Additional pilots may be forthcoming in 2026.
Hence one can expect that with time the platform will incorporate even more industry feedback in its functionality.
If you are interested in taking a deeper dive on the CI-RiskDB, contact the Enviro Integration Strategies’ team at https://ci-riskdb.com.
I would like to thank Karen Chovan for allowing me access to the platform. Since I am not a risk management expert, the time spent poking around was also a good learning experience for me.

Date: Dec 20, 2025

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A Rookie in the Oilsands – Part 2

Date: June 2, 2025 Author: Ken Kuchling Comments: Leave a reply
The article is Part 2 of discussion on my experiences working in the oilsands at the Syncrude Mine in northern Alberta.   Part 1 can be read at this link https://kuchling.com/a-rookie-in-the-oilsands-part-1/
In Part 1, I described the great Engineer-in-Training rotational program that Syncrude had in place for new engineering graduates.   Initially I had rotated through the Overburden Geotechnical and Industrial Engineering departments.   I was then fortunate enough to go though the Mine Geotechnical department and Short Range Planning.  Here are some experiences from those assignments.

Will the Draglines Be Safe

Syncrude had four large walking draglines, each with a 80 cubic metre bucket and 110 metre operating radius.   These were very big machines; you could sit one in the end zone of a football field and the bucket would be digging (or dumping) in the other end zone.   Two draglines were on the East side of the mine and two were on the West, mining the oilsand in 25 m wide strips.
Mining oilsand while from the top of a 50 metre high and 45 degree highwall had never been done before. The geotechnical conditions were new.  They were also dramatically different on the East and West sides of the mine, even though mining in the same orebody.
The East side was far more a greater geotechnical concern than the West side.   I happened to be the West side mine geotechnical engineer (lucky for me I guess).
The oil sands are sedimentary deposits, and consist of inter-layered sands, silts and clays. At the Syncrude mine, the clay layers were regionally dipping towards the west at 5 to 10 degrees (as shown in the sketch below). Hence they were dipping into the wall on the West side and dipping out of the wall on the East side.  The orebody also contained ancient creek scour channels, now infilled with clays and sands.
On the flanks of these scour zones, the thin clay layers could dip up to 25 degrees out of the wall.  This was a problem.   In university we learned rock slope failures generally require 30-35 deg dipping joint structures for sliding to occur; but here in the clays, sliding (block slides) could occur along 15 to 25 deg dips.
There were numerous instances of East mine block slides, where large portions of the upper slope would fail as large blocks, 50 metres long and up to 30 metres back from the crest.   The fear was that if a dragline happened to be sitting on one of these failing blocks, the entire machine would slide along into the pit.  Many block slides did occur over the years, but only a few came close to jeopardizing a machine.  The geotechnical monitoring programs in place were successful (described later).
The insitu clay structures were identified using oil and gas borehole logging technology, with tadpole dipmeter plots (see image) used to analyse the bedding (the tail on the tadpole shows the dip direction). The vertical axis is depth from surface or elevation.  The geotech engineers would use this information, combined with structural mapping of previously mined faces, to forecast potentially unstable areas.
In these problem areas, the geotech teams would install slope indicators that were monitored while the dragline was mining through the area. Dedicated 24 hour field engineers were assigned to each of the East side draglines and mining operations were closely monitored at all times.
It was not uncommon for the Syncrude geotechnical engineer to get a 2 am phone call at home saying movement has been detected and they walked the dragline back from the face and then get asked “What should we do now?”.
In the places that the engineers knew were going to be very risk, they could implement mitigation measures.  How would you deal with the steeper scour zones?   They had three main options.
  • mine through the area with intense geotechnical monitoring in place, using slope indicators, survey prisms, and visual ground inspections.
  • sub-excavate the zone; using the dragline to dig out the area and then backfill with the same material to destroy the clay bedding. Then they could safely mine through the area, although the days used to sub-excavate would remove the dragline from oilsand production.
  • another option was to blast the area ahead of time, to destroy the clay bedding and allow pore pressure dissipation.
All three options were available at the discretion of the geotechnical engineering team.  However they all cost money and/or loss in mining production, but safety was always the priority.
The four draglines are now mothballed and thankfully none were ever harmed.  All oilsand mining operations are now based on truck-shovel systems.

Basal Slope Failures

On the West side of the mine, the bedding was mainly into the highwall, so block slides were not a major concern.  In my brief time there, we never had a block slide on the West side although we did continually review dipmeter plots and face mapping results. One still couldn’t be too careful or get lazy.
The main geotechnical issue on the West side were basal slope failures, termed this due to sliding along weak clays and muds at the base of the highwall.   This photo shows a typical basal failure.  Basal failures also occured on the East side.
Generally, these slope failures did not jeopardize the dragline since they occurred on freshly cut highwalls away from the machine. Eventually the dragline would be required to operate next to existing basal failures when mining the next panel (as shown in the photo).
The dragline would sit 15-25 metres from the wall, the closer is better to maximize reach into the pit.
The main concern with basal failures was that the toe of the failed slope would move beyond the reach of the dragline and could not be mined.  As well, sometimes the dragline would need to cast waste layers back into the mined out pit while avoiding the burial of the oilsand toe. If the waste couldn’t be cast back inpit due to toe failure, it would be placed on the operating bench and trucked away later (at a cost).
The Alberta government focused on maximizing oilsand resource recovery.  If the dragline could not reach the ore due to a failure, we would need to send mobile equipment down to get it.  If we couldn’t do this due to access issues, we needed to prepare an Ore Loss Report that was tracked and submitted to the government agency (ERCB).   We hated to submit those reports, taking it as a personal disappointment that we couldn’t get to that ore.
In the basal failure photo, one can see a vertical scarp next to the dragline.  The oilsands were a “locked sand” in that the sand grains were tightly compacted or interlocked from the compressive weight of over a kilometre of glacial ice thickness in the past.   The vertical scarps would stand indefinitely, sometime spalling off in slabs. The oilsand itself was a very strong geotechnical unit (friction angles in excess of 50 degrees).

Conclusion

Hopefully the above narrative is informative about on mining in the oilsands in the 1980’s.  There are plenty more examples of technical issues that our engineering teams had to deal with, whether in the mining operation or tailings disposal area.   As a new graduate engineer, it was a great learning experience.
Once our engineer-in-training rotation program was complete, we were to be assigned to a more permanent position.  For me, that was going to be as an East side geotechnical engineer – ugh!.   It’s at that time I decided to look for greener pastures.   Three years was long enough from 1980 to 1983; given the amount of learning and responsibility I had undertaken.  Other colleagues left the same time, while many other friends stayed in Ft McMurray for their entire careers.
I enjoyed the mine planning and scheduling work more than geotechnical engineering. The stress of the East side geotechnical role was not really for me.  These days, I commend the tailings engineers that willingly accept the Engineer of Record role for tailings dams, knowing the risk, consequences, and potential legal ramifications of their work.
My next career move (after getting an M.Eng from UBC) was going to the Saskatchewan potash industry.  One thing common between open pit oil sand mining and the underground potash mining was the heavy reliance on conveyor usage at both.  I was getting very comfortable around conveyors.   If you found this oilsand narrative mildly interesting, you can read about potash experiences at the blog post “Potash Stories from 3000 Feet Down – Part 1”.  .
Note: You can sign up for the KJK mailing list to get notified when new blogs are posted. Follow me on Twitter at @KJKLtd for updates and other mining posts.   The entire blog post library can be found at https://kuchling.com/library/
Here is short cheesey video of what  the oilsands were about in the 1980’s and 1990’s.

Mining at Syncrude

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A Rookie in the Oilsands – Part 1

Date: May 22, 2025 Author: Ken Kuchling Comments: 2 Replies
Whenever I walk past a road repair crew laying down asphalt, I am taken back to my days working at Syncrude in the oilsands.  The smell of the road tar is the same as the smell in the open pit mine.    For three years that was my everyday experience.  It’s the same as when I get a whiff of diesel fumes, it often reminds me of my days working underground.  It seems that smell really can bring back memories, for me at least.
In Part 1 of this two part blog post I would like to share some stories from the early days of my career working in Fort McMurray.
Hopefully they will be interesting and help shed some light on what it can be like working in the mining industry.   Syncrude provided my first job out of engineering university and hence will always be special to me.
In the early 1980’s Syncrude was producing about 90,000 barrels of oil a day by processing oilsand at a rate of 180,000 t/day, so it was a big mining operation.

The Engineer in Training Program

I started at Syncrude in the winter of 1980. At that time, the two main places hiring mining engineers were the oilsands in northern Alberta and the iron ore mines in northern Quebec / Labrador.  A few mining graduates also went to work in Calgary in the conventional oil & gas industry, since they were looking for engineers and petroleum engineers were in scarcity.
At the time Syncrude had an excellent engineer-in-training program for new graduates.   Every six months they would rotate engineers into different technical areas.
These areas could consist of:   overburden stripping planning; overburden geotechnical; short range mine planning, mine geotechnical, industrial engineering, tailings planning, and tailings geotechnical.  Long range planning tended to be left to the more senior people.
Probably about 15 mining / geological engineers were hired at the same time as me.  We came from McGill, Queens, UBC, Laurentian, Univ of Alberta, and Nova Scotia.  All of us were in the same boat, rotating through various departments for the first few years.
I ended up in four of the areas listed above; I don’t think anyone actually went through all of them.  My first role was in Overburden Geotechnical department, where we had responsibility for waste dump stability, haulroad construction QA/QC, and dragline pad preparation.  Each of these tasks required a lot of on the job learning for me.

A Fish Out of Water

At McGill, in the mining engineering program, we took some courses on rock mechanics, focusing on “rock”.  The mines in eastern Canada were mainly hardrock mines so that was the learning priority.    We leaned about joint mapping, stereonets, compressive and tensile strength testing and kinematic analysis.
Well, at Syncrude there was no rock.  All geotechnical work here was based on soil mechanics, something we learned little of at university. Perhaps the civil engineers did more of this.  Working in the oilsands, one had to learn about sands, silts, and clays, Atterberg limits, grain size curves, compaction methods, and limit equilibrium stability analysis.
I quickly realized that even after finishing university, the learning does not end.  In fact, the real learning starts.  Everything you do is now applied on the job site, not just submitted in a term paper for marks, so you better learn fast.
The following is one such learning experience.

A Powerline in Trouble

As mentioned above, my first role was in Overburden Geotechnical, where waste dump design, stability, and monitoring were part of my job responsibility.   We already had about three out of pit dumps underway and a few inpit backfill dumps.  The waste dumps were comprised of inter-mixed clay & sand built upon mainly clay foundations.   That’s not the same as building rock dumps on rock foundations.
A few months on the job while on my daily site inspection route I noticed that, next to one of our waste dumps, the main 240 kV powerline coming to site was starting to lean over (see sketch).  My first thought was “Fiddle sticks this isn’t good”.  Gradual creep of the waste dump slope was starting to push on the power line.  The guy wire anchors were holding tight but the base of the power poles were being moved.
I hurried back to the office to explain the situation to my supervisor and the issue quickly went up the chain of command.  We jumped into action, first by relocating waste dumping activity to another area.   Next, we started to investigate the cause to see if we could stop the creep.  The dump did not actually fail catastrophically; it was just moving slowly.  Generally, when slope creep starts, it is difficult to stop.
We drilled several hollow stem auger holes from the dump surface down into the foundation to see what was there.  We installed a few slope indicators to see at what depth the sliding was occurring. These pinched off within a day or two, but at least we knew at what depth (about 20m down the hole).
Next we sampled that depth carefully, revealing that frozen muskeg layers were present.  When we installed standpipe piezometers in these holes, we saw water flowing out of the top of the pipes.  This means the foundation pore pressure is high, way too high.
We concluded that a few years prior the waste dump was built in winter when the muskeg was frozen.  The dump insulated the muskeg from thawing and the frozen layer would not allow upward pore pressure dissipation from the dump surcharge.  The clay foundation didn’t allow downward dissipation. The muskeg layer was acting like a water bed, floating the waste dump on top of it.
Every day one could see the power poles leaning a little bit more, so time was of the essence. We tried to implement foundation depressurization measures, but drilling angle holes in soft clay was problematic, and targeting the over-pressured zones was difficult.  Management quickly made the decision to relocate a section of the powerline. Helicopters were brought in to help install a new powerline around this area.  The entire exercise probably cost several million of dollars, but a major plant outage was avoided.
Welcome to the real world.

Not All Jobs Were Exciting

The one rotation that the engineers generally tried to avoid was Industrial Engineering.  This is an area that looks at operational and cost efficiencies in the mine.  It tends to focus on smaller details rather than the big picture mining operation.  I had a 4 month stint in this department, which taught that me, that in life you don’t always get what you want.  The IE projects would vary depending on the mine’s needs.
For example, one project I had was to monitor the performance of different brands and styles of conveyor idlers.  We would track about 2,000 individual idlers; when they were installed on the conveyors; when they were removed, why they were removed (bearing failure, cover failure, something else).
The idea was to figure out which idler manufacturers were the best – important but not exciting work.  If you liked statistics, this was a good job, although around 1981 we didn’t have Excel (or even Lotus 123) at that time (1982), so it was a manual process.
Another project was to try to improve the time efficiency of mine conveyor belt splicing operations.   With steel cord belts, there are numerous steel cords in the interior of the belt that carry the tensile load. When it comes time to do a splice (to add in a new section of belt) each splice took about 2-3 days, which meant that mining area would be out of commission.
To splice, one must clean each steel cord individually then overlay the cords from the two belt section side by side, then cover the cords with rubber and vulcanize under heat and pressure.  It all took lots of time.  Naturally this time study project required spending long days out with the splice crews, watching them do this work while making notes on the actions and activities and durations.   Important .. but less than exciting.
One good thing about this job was that the Industrial Engineering supervisor loved to use the expression “That’s politically explosive” for stuff that really wasn’t.  That phrase made such an impression on me that I still try to use it today.

End of Part 1

This concludes Part 1.  In the next article I will discuss a few other engineering aspects unique to the oilsands and how the engineering teams dealt with them.
Dragline mining of oilsand was never done before, so engineers were learning on the fly.  Given the size of the operation, we could not afford to be wrong on the decisions made.  It was an interesting, and also stressful, time for many.
In the 1980’s both Syncrude and Suncor had mainly electrified oilsand mining systems, consisting of bucketwheel excavators & conveyors at Suncor and draglines, bucketwheel reclaimers, conveyors at Syncrude.  Years later both operations switched to diesel focused truck and shovel operations and mothballed the electric mega-excavators.  I’d be curious to know if in 2025 they would still make the same decision based on carbon emission issues and the push for electrification in mining.
Part 2 of this blog post series can be read at this link “A Rookie in the Oilsands – Part 2“
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Mine Reconciliation – Standardization Please

Date: May 7, 2025 Author: Ken Kuchling Comments: Leave a reply
Mine through mill reconciliation, in my view, is an under appreciated topic that could benefit from more conversation amongst industry members. Unfortunately, reconciliation is sometimes viewed as a time consuming frustrating activity, with what some consider less than verifiable results.  However given the ongoing innovation that we are seeing in mining, reconciliation may need to play a bigger role than ever.
The mining industry is implementing more and more technology in the mining cycle.
For example, this can range from AI assisted resource modelling, down hole logging, blast movement tracking, GPS controlled dig limits, MineSense bucket grade tracking, load scanning, truck dispatch control, smart mining and edge computing, online grade analyzers, belt weightometers, drone surveying of stockpiles, and real time process controls.
Lots of different innovations are continually being adopted by the mining industry, contrary to what some may say.
The question is does all this innovation improve the overall performance of a mining operation, and if so, by how much? It can cost a lot of money to implement the new technology, is there a payoff?
One cannot answer those questions if one doesn’t undertake proper mine reconciliation. A concern might be that mining is innovating faster than the ability to assess the results of that innovation.  To monitor it, you need to measure it.

What is Mine Reconciliation

Mine reconciliation is the process of comparing and aligning the estimated production with the actual production from mining and processing. It requires assessing the accuracy of pre-mining predictions against actual results to identify inconsistencies in the system and hopefully improve it, be it resource estimation, mine planning, or process efficiency. Comparisons can be made between multiple stages in the mining system, as shown in the image below.
  • Mine reconciliation requires information such as initial predictions from exploration data and geological models, actual measurement: data from mining sources, such as blast holes, stockpile samples, or mill feed. As well it will need data on the final product being shipped off site. Do the metal quantities balance out throughout the mining operation?
  • Mine reconciliation tends to aggregate over longer time periods (monthly, quarterly or annually) due to short term impacts of material handling in stockpiles and plant circuits and the labour time needed to collect the input data.
  • Mine reconciliation ultimately attempts to assess how well the delivery of the final metal product relates to the initial resource model (i.e. what the project decision was originally based on)? It is also tool to evaluate the impact of any innovation implementation on the operation.
  • Reconciliation will help mine operators highlight issues and optimize extraction, manage costs, and ensure compliance with regulatory or investor expectations. Factors such as poor resource estimation, excessive dilution and ore loss, inaccurate sampling, etc. can cause discrepancies, making reconciliation an important part of any operation.
  • The reconciliation process is also used to derive Mine Call Factors. These factors are used to modify the forecasts from long range models, short range models, and grade control models to better represent the actual performance the operation will likely see. Large call factors suggest something is amiss in the “forecast to actual” progression. The first problem is to identify the causes. The list of the common sources of error can be lengthy. Then, once identified, the second problem is how to fix them.
Harry Parker initially suggested various reconciliation parametrics and labelled them F1, F2, F3. In a 2009 paper by Fouet titled “Standardising the Reconciliation Factors Required in Governance Reporting”, indicates that Rio Tinto had decided upon fifteen  (15) different possible reconciliation correlations (see image below). Each one provides an insight on the efficiency of the operation in one way or another. I have seen modified versions of the reconciliation relationships, so it appears there may be no industry standard at this time. Fouet was asking about industry standardization in 2009 (an excellent paper to read by the way).

Mining Codes Getting Involved

It appears that the JORC Code may be recognizing the importance of reconciliation. In an August 2024 Exposure Draft JORC is suggesting the following text: “Where an Ore Reserve has been publicly reported for an operating mine, the results of both production reconciliation and any prior estimate comparison must also be included in the annual Mineral Resources and Ore Reserves statement. Refer to Clause 2.36. The relationships and variables being reconciled must be described in plain language or depicted graphically and must include reconciliations of both the Mineral Resources and Ore Reserves.”
Interestingly, it appears that NI43-101 has not yet jumped on the bandwagon about the importance of disclosing reconciliation results. However, it may just be a matter of time before it becomes one of their disclosure requirements.
If more regulatory focus will be put on mine reconciliation disclosure, then perhaps more industry standardization is warranted. This would help better define some of the terminology and “F factors” shown in the diagrams above to ensure consistency and help avoid each mine doing reconciliation in their own way.

Excel versus Cloud Based Reconciliation

Each mine site may be unique with respect to; ore sources; terminology; ore types; mining methods; stockpiling philosophy; processing methods; technology availability; and personnel capability. So often the easiest approach for mine reconciliation is based on the Excel spreadsheet. (Reconciliation is generally not an easy undertaking).
Spreadsheets can be built site specific, based on an operation’s unique characteristics.
Spreadsheets are often built by a user for that user. They are tailored for the tailor. In my experience, typically the modeler is the only one comfortable with an Excel model’s logic, since all of us may think differently. Unfortunately, with the spreadsheet approach, it becomes more difficult to standardize an industry wide reconciliation process.
An alternate solution to spreadsheets is to use a cloud based standardized software package. Toronto based Minebright has one option, called Pit Info (see link for more info). There are a few other reconciliation software applications available. They tend to be cloud based, hence multiple people can have access to the input modules or output modules.  (I would like to thank the Minebright people for steering me towards some of the technical papers on this subject).

The cloud based approach may help make reconciliation a group effort instead of a tightly controlled internal function. It may also help standardize reporting from a company’s multiple operations, reporting from the mining industry globally, or simply for consistent JORC reporting.
The downside to the cloud approach is the mine site teams must learn the software and tailor it to their operation. However, once that hurdle is passed, personnel changes become less onerous due to the model consistency. I have seen cases where a person doing the Excel reconciliation task has left their job, and hence forward the reconciliation effort came to a halt. The people remaining may be too busy or simply don’t want to have to figure out the Excel logic of someone else.
The other nice thing about a cloud software approach is that when improvements are rolled out, every user gets the same update. The “wisdom of crowds” will result in learnings and suggestions that will tend to improve the application functionality over time. There are a lot of smart people out there, and it would be nice to see them working together rather than individually, as the open source software community has demonstrated.
With AI, we also may get to the point where cloud based mine reconciliation platforms can use learnings from other projects, and help identify where the likely technical shortfalls are at a mine site and why production is not reconciling. Let’s ask AI do some of the thinking for us to get to the bottom of a problem.

Conclusion

Mine reconciliation is becoming more and more important, but it can be a forgotten aspect. Sometimes this is because it is difficult to do properly. However, that doesn’t mean it shouldn’t be attempted. The more one can learn about one’s operation, the more likely it can stay efficient, relevant, and in business. The more one knows whether technology improvements are making a difference, the more one may be willing to take on even more new technology.
Shifting some people (like me) away from Excel based solutions can be a challenge, but this is an area where it makes sense. Years ago, many engineers did mine production scheduling using Excel, but we have gradually moved away from that, thankfully.   Reconciliation should maybe follow that path.
Disclaimer: Mining is a global business, and perhaps more progress is being made on reconciliation standardization than I am aware of sitting here in my Toronto office. Mine operations around the world are at the forefront of developing new systems. Perhaps we are seeing great things being done in the area of mine reconciliation, or maybe we are not. Please share your experiences if you’re comfortable doing that.
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Spying on Tailings Using Satellites

Date: June 28, 2024 Author: Ken Kuchling Comments: 1 Reply
There have been recent heap leach pad failures in the Yukon and Turkey and tailings dam failures in Chile and the Philippines.  As a result I have been seeing more posts on LinkedIn about the application of satellite based InSAR deformation monitoring.  Prior to that I had never heard of InSAR, so thought a little bit of background study might be worthwhile.
The following are my observations on what InSAR is and where it may be going.  I am by no means an expert in this technology.  I am merely viewing it from the perspective of a mine design engineer.

What is InSAR

InSAR is satellite-based “Interferometric Synthetic Aperture Radar”.    It can measure the distance from a satellite to a ground feature.  With repeated imaging it is used to detect changes in distance and measure displacements to within 5-10 millimetre accuracy.  Hence it can be used as a potentially cost-effective slope monitoring tool, albeit it cannot be the only tool, as discussed later.
The relevant satellite images have been available for years.  Currently the availability of analytical software to interpret the satellite data is improving.   It can detect millimeter-scale displacements, however only in the line-of-sight (LOS) direction of the satellite.   Using two or more satellites in different orbits, displacements in horizontal and vertical directions can be defined.
An example of a satellite being used is the Sentinel-1, launched in mid-2015 by the European Space Agency. This satellite information is open-source data.  It will have a 6 to 12 day revisit cycle in many locations.
The results of an InSAR displacement survey are typically shown as a series of colored data points, typically coloured green for the stable points, trending to yellow and red for points that are moving.
This blog has some example images.

Some Limitations With InSAR

There are some limitations with InSAR, so it can only be part of a monitoring program.  These limitations are:
  • The displacement direction is only measured in the direction of the satellite.  Hence one may not know in which direction the movement is occurring.  The magnitude of displacement could be underestimated depending on the apparent angle of measurement.
  • The movement being measured could consist of vertical settlement due to material consolidation and may not be horizontal and related to impending failure.
  • The displacement magnitude measured on opposite sides of a facility may have different accuracy, depending on the slope orientation versus the line-of-sight.
  • Areas with heavy vegetation may be difficult to monitor
  • Areas with heavy or persistent cloud cover can be difficult to monitor.
  • Areas with snow cover will be difficult to monitor.
  • The satellite return period may be weekly or every two weeks, so one is not able to analyze daily movements if a situation is critical.  If the return visit day has cloud cover, there will be no new satellite data collected.
  • Areas with on-going construction or tailings deposition will lead to erroneous results.
  • Due to the line of sight, not all slope failure modes may be detectible (for example piping failure).
Regardless of these limitations, InSAR can still play a role in any monitoring program since it is able to monitor large areas quickly.   Consider it as a pre-screening tool, being aware that not all failure modes may be detectible with it.

Discussion

On LinkedIn, one can see numerous posts where independent experts are examining historical InSAR data for recent failures to see whether early movement should have been detected.  The results seem to be quite positive in that areas that have failed might have been red-flagged prior to failure.
There are also zones that showed critical displacements but have not failed.
Typically, there are four ways to monitor displacement in pit slopes, tailings dams, heap leach pads, and waste dumps.   They are:
  1. Insitu monitoring using embedded instruments, for example slope indicators, extensometers, and settlement gauges.  These instruments provide information on what is happening internally within a slope, where actual movement is occurring, and they can be used in warning alert systems.
  2. Surface monitoring using radar (ground based InSAR) systems and survey prisms.  These tools measure only surface movements in selected areas, can be monitored as frequently as needed on an automated basis, and integrated into warning alert systems.
  3. Drone or aerial surveys can be used to measure topography and monitor movements over large areas.   This method requires a data processing delay (not real time) to derive the movement information, but such surveys can be done as frequently as needed.
  4. InSAR from satellite can be used over very large regions to highlight areas with movement.  That should trigger the implementation of one or more of the other monitoring approaches (if not already in place).

Conclusion

A mining site consists of numerous constructed embankments and slopes of all types and heights.  Many of these slopes may be creeping and moving all the time – it’s a living beast.
The operator’s awareness about their site will be better the more monitoring tools they use.  This awareness is important given the critical role that slope stability plays.  We will see if InSAR technology achieves much wider adoption in the mining industry as a first phase of a stability monitoring programs.
Since InSAR monitoring is done from space, it does not require access to a property.  Hence it can be used by third parties or NGO’s to “spy” on facilities of concern anywhere.
Possibly over the next few years we will see independent donor-funded organizations monitoring tailings facilities around the globe.  They will be able to notify the public and mine operators “Hey, there is some movement on this mine site that needs to be addressed”.    An organization called World Mine Tailings Failures has started some discussions on this concept.   Check it out.
Finally, it is great for a mine site to collect a lot of displacement data, hopefully to forewarn of movement, displacement acceleration, and imminent failure.  However, this assumes that someone experienced is interpreting the data and its not just generating graphs for the file cabinet.   Perhaps AI can play a role here in the future, if the technical personnel to do this are lacking.
Note: You can sign up for the KJK mailing list to get notified when new blogs are posted. Follow me on Twitter at @KJKLtd for updates and other mining posts.   The entire blog post library can be found at https://kuchling.com/library/
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Junior Mining Shams and Scams – Part 2

Date: June 3, 2024 Author: Ken Kuchling Comments: Leave a reply
This is Part 2 of the blog post discussing junior mining scams and the sanctioning of those responsible.  Part 1 can be found at this link “Junior Mining Shams and Scams – Part 1” and can be read first to get some background.
Part 2 provides examples involving professional Qualified Persons (QPs).  We may have the feeling that QP’s are never held accountable for their work, but that is not always the case.  There are numerous instances of QP’s being hauled off in front of their professional organizations for unprofessionalism.   This blog will highlight some of those cases.
The lesson is that QP’s signing off on technical information for clients should be proficient in the nature of their work and need to know the reporting rules very well.  Some of these incidents involve error and poor judgment, not outright fraud.
These examples involve in-house QP’s that work for a company while others involve independent QP’s that have been contracted by the company.
In most of these cases, any sanctions, if applied, were mainly doled out by the professional engineering or geological associations.  The legal courts are often not involved.

Examples (Part 2)

Inaccurate QP Resource Estimate:  This example relates to the Barkerville Gold Mines resource estimate complete in 2012.  The mineral resource estimate had numerous errors and issues related to assays, capping, cutoff grades, etc.   The allegation was the QP had demonstrated incompetence, unprofessional conduct, and negligence.   The sanctions on the QP included a $15,000 fine, $20,000 legal costs, re-training, and license suspension.
Link 1:   
Link 2:
False QP Statements:  Here is an example from 2011.  The QP / company Director was charged with multiple allegations, including stating the mine was in commercial production (when it wasn’t), leaving the impression there were mineral resource (which there weren’t any), and generally approving information that was not accurate.  Ultimately the allegation was demonstrating incompetence, unprofessional conduct, and negligence.   The resulting sanctions included 2 year license suspension, re-training, payment of $80,000 to the professional association.
Link 1: 
False QP Statements: This is case were a resource QP failed to comply with the NI43-101, Form 43-101F1, CIM Standards, and CIM Guidelines. The Panel concluded that the Member was guilty of non-compliance with the standards and hence guilty of professional misconduct. Its not clear what specifically was not complied with, but this illustrates that QP’s will be held accountable for their work.  The two reports in question were either amended or withdrawn to address the concerns of the regulator in British Columbia, although there had been no intentional non-compliance and no economic impact.   The penalty was 2 months suspension (deferred), and the QP had to work under a mentor for 9 months and pay a maximum $10,000 for the mentor’s fees.
Link 1: 
False QP Statements:  Here is another example of sanctioning a QP in 2018.  The person was charged with unprofessional conduct and incompetence.  He stated that he was responsible for the preparation of the technical report, had no prior involvement in the project, and was independent of the issuer.  This was false.   Sanctions included three month license suspension, taking some re-training, require peer review of the report.   In 2022, further sanctions consisted of a $75,000 penalty, further sanctioned along with an executive in the company for insider trading issues (see Link 3 below).
Link 1:
Link 2: 
Link 3:
False QP Statements:  This is an example for 2017 when an independent QP took responsibility for the resource estimation work in section 14 of the report, yet they did not have the experience to take responsibility.   They also misrepresented that the Report complied with 2014 CIM standards, yet it didn’t, resulting in an overestimation of the mineral resource in both confidence and magnitude.    Other claims include relying on non-QP experts but not stating that, failing to adequately discuss the nature of sample quality control procedures as required.    The sanctions included license suspension of 3 months, must work with a technical supervisor, re-training, and $7,500 in legal fees.
Link 1:
False QP Statements:  This is another example from 2019, when the QP / Director permitted the disclosure of information to the public in multiple news releases where they should have known that that information was misleading.  An example is the disclosure of inferred reserves when there were no reserves and “inferred” is not even a classification of reserves.   The sanctions were a license suspension of 4 months, $5,000 legal costs, re-training, and requirement not to act as a QP again.
Link 1: 
QP Resource Estimate Error:  This occurred in 2012 when a QP and consulting firm delivered a incorrect resource estimate and reportedly withheld negative opinions on the project from the client.  The company spent $3 million on a feasibility study during which the resource estimate error was discovered.  The “corrected” resource made the project uneconomic, meaning the feasibility study should not have been done.  The mining company sought compensation from the consulting firm, ultimately receiving $1.25 million.  The Link 3 references is interesting in that it states “As this case demonstrates, it is critically important for professional service firms to be forthcoming about any reservations they may have regarding the work they are being employed to undertake.”     Whatever  that really means?
Link 1: 
Link 2:
Link 3: 

Disclaimers

Many QP’s realize the legal responsibility and liability they have.  Hence in 43-101 reports QP’s sometimes attempt to mitigate this by putting in broad disclaimers to limited that liability.  If the securities commission notices such disclaimers, they will require that they be removed.
For example, sometimes the QP of a chapter may have other geologists or engineers (i.e. experts) assisting them.  They may then put in disclaimers saying “They disclaim responsibility for such expert content” for the work done by the others.   A QP essentially has to sign off on the work of others in the sections they are responsible for.   A recent example is a Generation Mining technical report prepared by G-Mining, that had to be amended from (March 31_2023 to May 31_2024) removing several QP liability limiting disclaimers.
43-101 regulations state that “An issuer must not file a technical report that contains a disclaimer by any qualified person responsible for preparing or supervising the preparation of all or part of the report that
(a) disclaims responsibility for, or limits reliance by another party on, any information in the part of the report the qualified person prepared or supervised the preparation of;
or (b) limits the use or publication of the report in a manner that interferes with the issuer’s obligation to reproduce the report by filing it on SEDAR.“
” These disclaimers are also potentially misleading disclosure because, in certain circumstances, securities legislation provides investors with a statutory right of action against a qualified person for a misrepresentation in disclosure that is based upon the qualified person’s technical report.
That right of action exists despite any disclaimer to the contrary that appears in the technical report. The securities regulatory authorities will generally require the issuer to have its qualified person remove any blanket disclaimers in a technical report that the issuer uses to support its public offering document.“

Conclusion

This ends Part 2 of this blog post. It hopefully highlights the importance of QP’s being knowledgably on the disclosure rules and the technical aspects of what they are hired to do.
Companies should always ensure that only qualified QP’s are used for their project work, even if some of the others might be less expensive.   The potential headaches and costs afterwards may override the higher upfront cost.
It should be noted that this Sham and Scam blog does not discuss the other less than desirable junior mining traits seen from time to time.  These relate to; insider trading; abuse of micro-penny founder shares; and the ever present “pump & dump” schemes.
In closing, if anyone is aware of other good examples of QP issues, please provide any links to any publicly disclosed information. I can add them to the blog post.
Note: You can sign up for the KJK mailing list to get notified when new blogs are posted. Follow me on Twitter at @KJKLtd for updates and other mining posts.   The entire blog post library can be found at https://kuchling.com/library/
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