Articles tagged with: Mine Engineering

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?

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.
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.
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.
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.
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.
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.
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.
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.

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“.

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/

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.

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:

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.
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.
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.
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.

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The Anatomy of 43-101 Chapter 16 – Mining (Part 2)

Date: March 22, 2024 Author: Ken Kuchling Comments: Leave a reply

Part 2 of this blog post will focus on the remaining engineering work to finish Chapter 16 of the Technical Report. We only wrote about half of it in Part 1. The mining engineer can generally handle the rest of these tasks without requiring a lot of external input. You can read Part 1 at this link “The Anatomy of 43-101 Chapter 16 – Mining (Part 1)”.

The pit design and phases were completed at the end of Part 1, and we can move on to scheduling.

4. Production Scheduling

Once the pit design is complete, everyone will be calling for the production schedule as soon as possible. Others on the team are waiting for it. The tailings engineers need the production schedule for the tailings stage design. The process engineers need the scheduled head grades to finalize sizing the plant components. The client wants the schedule to plug into their internal cashflow model for a quick peek at the economics.

However, before the mine engineer can start scheduling, the dilution approach needs to be selected. Dilution is waste that is mixed in with ore during mining. A high amount of dilution can dramatically lower the processed head grades. There may be a desire to “low ball” the dilution to make the grades look better, but the engineer should base the dilution on what they would expect to see.

Two dilution approaches are common. One can either construct a diluted block model; or one can apply dilution afterwards in the production schedule. I have used both approaches at different times.

The production schedule must be on a diluted basis, since that represents what the processing plant will actually see.

Generally, two different production schedules must be created: (i) a Mining schedule, and (ii) a Processing schedule. In some instances, they may be one and the same schedule. However, if any ore stockpiling is done, then the Mining schedule will be separate from the Processing schedule.

The Mining schedule shows ore going directly to the plant and ore going into the stockpiles. The Processing schedule will show ore delivered directly from the mine and ore reclaimed from stockpiles. Building stockpiles and pulling ore from stockpiles are two independent activities.

Sometimes lower grade stockpiles are built up by the mine each year but only processed at the end of the mine life. Periodically the ore mining rate may exceed the processing rate and other times it may be less. This is where the stockpile provides its service, smoothing the ore delivery to the plant.

Scheduling can be done with variable time periods. Perhaps the schedule is generated using monthly time periods, or quarters, or years.

The 43-101 report will normally show the annual production schedule, but that does not mean it was generated that way. I prefer to use short time periods (monthly or quarterly) for the entire mine life, to ensure ore is always available to feed the plant. A 10 year mine life would result in 120 monthly time periods, so output spreadsheets can get large.

Scheduling can be done manually (in Excel) or by using commercial software, like Datamine’s NPVS. The commercial software is better in that it allows one to run different scenarios more quickly, and it does a lot of the thinking for the engineer. It also does a good job of stockpile tracking. It also decides when it is necessary to transition to mining in satellite pits.

Once the schedules are finalized, they are normally reviewed by the client for approval. The strip ratio and ore grade profile by date are of interest. One may then be asked to look to at different stockpiling approaches to see if an NPV (i.e. head grade) improvement is possible.

One can stockpile lower grade ore and feed the plant with better grade by mining at a higher rate with more equipment. One might need to examine iterative schedules of that type.

Sometimes one must take two steps backwards and re-design some of the initial pit phases to reduce waste stripping or improve grades. Then one would run the schedules again until getting one that satisfies everyone.

Now that the schedule is complete, we can write up the Chapter 16 text up to page 15. We’re getting closer to the end.

5. Site Layout Design

With the pit tonnages and mining sequence from the schedule, the mine engineers can start to look at the site layout (waste dumps and haul roads). Normally the tailings engineers will be responsible for the tailings layout. However, if there is no tailings engineer on the PEA team, the mining engineer may look after this too.

First there is a need for a waste balance. This defines how much mined overburden or waste rock will be needed to build haulroads, laydown pads, and tailings dams. Then the remaining waste volume must be placed into waste dumps.

Hopefully the tailings engineers have finished their tailings dam construction sequence by this time to provide their rockfill needs (although unlikely if you only gave them the production schedule two days ago).

The geotechnical engineers will provide the waste dump design criteria; for example, 3:1 overall side slope using 15m high dump lifts. Ideally it is nice to have soil and foundation information beneath the waste dump sites, but at PEA stage most often this isn’t available. The dump locations are only being defined now.

The mining engineers will size the various waste dumps to their required capacity. Then they can lay out the mine haulroads from the pit ramps exits to the ore crusher, the ore stockpiles, and to each waste dump.

That’s it for the site layout input. Add another 2 pages to Chapter 16. Now the mining engineers can look at the mining equipment fleet.

6. Fleet Sizing and Mining Manpower

The last task for the mine engineer in Chapter 16 is estimating the open pit equipment fleet and manpower needs. The capital and operating costs for the mining operation will also be calculated as part of this work, but the costs are only presented in Chapter 21.

The primary pieces of equipment are the haul trucks. They can range in size from 30 tonnes to 350 tonnes and anywhere in between.

Typically, the larger the equipment is, the lower the unit cost ($/t), especially in jurisdictions where labor costs are high. One doesn’t want a mine fleet with only 5 trucks nor one with 50 trucks. So where is the happy medium?

Once the schedule and site layout are complete, the mine engineers can run the truck haul cycles, in minutes. They need to estimate the time to drive from the pit face, up the ramp, to the waste dump, to the ore crusher, and return back into the mine. Cycle times determine the truck productivity, in tonnes per hour per truck and include the time to load the truck. Some destinations may have long cycle times (to a far off crusher) while others may be quick (to an adjacent waste dump).

The cycle time must be calculated for each material type going to each destination. As the pit deepens, the cycle times increase.

Very simplistically, if a 100 tonne truck has a 20 minute cycle time, it can do three cycles in an hour (300 tph). If one has to mine 10 million tonnes of ore per year, then that would require 33,300 truck hours. If a single truck provides 6500 operating hours per year, that activity would require a fleet of 5 trucks. The same calculation goes for waste.

The total trucking hours will vary year to year as waste stripping tonnages change or haul cycle times increase in deeper pits. The required truck fleet may vary year to year. Keeping haul distance short and haul cycles quick is the key to a lower cost mine.

The mine engineers undertake the productivity calculations for loading equipment to estimate annual operating hours, and the required shovel / loader fleet size.

The support equipment needs (dozers, graders, pickups, mechanics trucks, etc.) are typically fixed. For example, 2 graders per year regardless if the annual tonnages mined fluctuate.

The support equipment needs are normally based on the mining engineer’s experience. Hence the benefit of actually working at a mine at some point in your career.

Blasting includes both the blasthole drilling activity and hole charging. The mining engineer estimates drill productivity and specifications based on the bench height, the expected rock mass quality, and the power factor (kg/t) need to properly demolish the rock.

Finally, the mine operation manpower is estimated based on all the equipment operating hours as well as the fixed number of personnel to support and supervise the mine.

This essentially concludes the mining information presented in Chapter 16 of a typical 43-101 open pit report.

Conclusion

These two blog posts hopefully give an overview of some of the things that mining engineers do as part of their jobs. Hopefully the posts also shed light on the amount of work that goes into Chapter 16 of a 43-101 report. While that chapter may not seem that long compared to some of the others, a lot of the effort is behind the scenes.

Some will say PEA’s are not very accurate documents that should be taken with a grain of salt. One should understand that engineers are working with a limited amount of information at this early stage while forming the concept for the proposed operation.

The subsequent study stages are where more accurate costs are expected and can be demanded.

I don’t know if this overview makes one want to sign up to be a mining engineer or learn to code instead. None of this is rocket science; it just requires practical thinking.

If young people want to get into mining, but not sure into which aspect, I suggest go read through a 43-101 report. There are sections describing exploration, resource modelling, mine engineering, metallurgy, geotechnical engineering, environmental, and financial modelling. Its all in one document. See if any of these areas are of interest to you. Universities should use 43-101 reports as part of their mining engineering curriculum.

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The Anatomy of 43-101 Chapter 16 – Mining (Part 1)

Date: March 20, 2024 Author: Ken Kuchling Comments: 4 Replies

When people learn that I’m a mining engineer, I’ll normally get perplexed looks and asked what that job is about. Most never even knew the job existed.

So I thought what better way to explain the mining engineer role than by describing the anatomy of a typical Chapter 16 (MINING) in a 43-101 Technical Report. That chapter is a good example of the range of tasks typically undertaken by mining engineers.

Secondarily it also provides an opportunity to describe in detail all the steps that go into writing a Chapter 16, focusing on the PEA.

PEA’s tend to have a poor reputation for lack of accuracy, and this blog post may shed some light on why that is. To avoid running on too long, I have subdivided this into Part 1 and Part 2.

Generally, one will see a single QP sign off on Chapter 16. However, the chapter requires input from several people. Section 16 is generally prepared in the same way for a PEA or a feasibility study (FS). The main difference is related to the amount of hard supporting data in a FS versus a PEA.

The PEA will rely on many “reasonable assumptions” and it can be done in at least half the time of a FS. A FS will also build on previous study decisions, something a PEA doesn’t have access to since it is a first time snapshot of a project.

Normally preparing Chapter 16 is done under time pressure to deliver results as quickly as possible. Other study team members are waiting for its output to finalize their own engineering work.

1. Define the Mine

In a PEA, the first thing that must be conceptualized is whether this will be an open pit (OP) mine, underground (UG), or a combination of both.

There is always a mineral resource estimate available before doing a PEA. The way the resource is reported will indicate what type of mine this likely is. The geologists have already done some of the mining engineer’s work.

The mineral resource will suggest if this will be an OP or UG, a large or small operation, a long life or short life, and the likely processing method. The framework for the project is already set at the mineral resource estimate stage.

We can now write page 1 of Chapter 16.

2. Optimize the Pit Size and Shape

The first step for the mining engineer is a pit optimization analysis to define the approximate size and shape of the pit. The pit optimization step creates a series of nested economic pit shells for different metal prices. For example, the base case gold price may be $1800/oz, but we still want to see what size of pit would be economic at $1000/oz, $1200, $1300, etc. Normally one may run 50 different price scenario increments. The smaller shells may eventually be good starter pits to help improve NPV and payback time.

Before starting pit optimization, we require economic inputs from several people. The base case metal prices must be selected (normally with input from the client). The mining operating cost per tonne must be estimated (by the mining engineer). The processing engineers will provide the processing cost and recovery for each ore type.

The geotechnical engineers will provide approximate pit wall angles. All of these inputs have to be forecasted at a very early stage. We don’t yet know the size of the pit, the ore tonnage available, nor the actual plant throughput rate but one must still predict some costs. Hence these initial inputs might just be ballpark data.

In the final cashflow model you may eventually see slightly different metal prices, costs, or recoveries than used in pit optimization. That’s because that cashflow model inputs are generated by the study, while the optimization inputs are pre-study estimates.

The pit optimization step may also need to apply constraint boundaries. For example, if there is a nearby property limit or river, one may want to constrain the pit optimization to get no closer than 50 metres to the river or boundary. The pit shell optimizer may be free to expand the pit outwards in multiple directions, except that one direction.

Once the optimization is run, a series of nested pit shells are created, each with its own tonnes and grade. These shells are compared for incremental strip ratio, incremental head grade, total tonnes, and contained metal.

A decision must now be made on which shell to use for the mine design. Larger economic shells may have more tonnes, lower grade, and higher strip ratio. Smaller shells may have lower strip ratio and better grade.

For example, a smaller shell may have 10 year life containing 800,000 oz at a strip ratio of 2:1 while a larger shell may have 14 years, 1 million oz at a strip ratio of 3:1. Both are roughly the same economically. However, developing the larger shell may require more mining equipment capital yet have a lower average cost per tonne. Which shell do you choose?

There can be dozens of such shell to shell trade-offs and typically one doesn’t run schedules and cost models on all of them. The client will have input on whether they wish to move forward with 10 years 800,000 oz or the 14 years with 1 million oz. Sometimes selection is driven by investors having size expectations that need to be met.

Some people may say ‘Well… just run cashflow models for each case to see which is best”. The problem with doing too much analysis at this stage is that if you re-do the pit optimization with different recovery, operating costs, pit wall angles, you will get a different optimization result. It becomes a question of how much detail work to do on something that is based on very preliminary input parameters.

Assuming the mining engineers have now selected the preferred shell for mine design, they can move on to mine design. We can now write more of Chapter 16 to page 5.

3. Open Pit Design.

The mining engineer is now ready to undertake the pit design. The pit design step introduces a benched slope profile, smooths out the pit shape, and adds haulroads. Hence a couple of key input parameters are required at this time. The mining engineer will need to know the geotechnical pit slope criteria and the truck size & haul road widths. Let’s look at both of these.

Pit Slopes: Geotechnical engineers are responsible for providing the slope angle criteria to the mining engineers. The geotech engineers may have a lot or little information to work with. Perhaps they have geotechnical oriented core holes and they have undertaken some rock strength testing.

Perhaps the only information for the geotechnical engineers is rock quality data from exploration drilling. I have seen both situations at the PEA stage; the latter is more typical. In the feasibility study they would have geotechnical core hole data available. At the PEA stage, that is less likely, since no one yet knows the size and depth of the pit. We are only getting to that now.

Pit wall schematic

The geotechnical engineers will provide the inter-ramp slope angles, specified by catch bench widths and bench face angles. The engineers may subdivide slopes by rock type.

For example: the overburden wall is to be at 30 degrees, the underlying oxide rock at 40 degrees and the deeper fresh rock wall at 55 degrees. Additionally, the pit may be subdivided into pie shaped sectors, with differing slope criteria.

For example, the fresh rock on the west wall might have a 55 degree angle, but the east wall fresh rock may only allow 50 degrees and the south wall is 45 deg.

The more sectors and differing slope criteria, the more complex it is to do the pit design. Normally you don’t see geotechnical engineers signing off as QP’s for Chapter 16, although they had key input into the pit design.

Ramps: Next the mining engineer needs to select the truck size, even though the production schedule has not yet been created.

Trucks sizes can vary between 30t up to 350t. A double lane ramp width is approximately 4.5 times the truck width, including space for a ditch and an outer safety berm. A 90 tonne truck is 6.7 metres wide (haulroad of 30m) while a 350 tonne truck is 9.8 m wide (haulroad of 44 m wide). That’s a 14m width difference.

The haul road gradient is normally 10%, which means a 200 metre deep pit requires a ramp length of 2000 metres to get to the bottom. It can be difficult to fit a 2 kilometre ramp in a small pit without pushing the walls out to provide enough circumference to get to depth.

Ramps can spiral around the pit, or they can zigzag back and forth on one side of the pit (switchbacks). The mine engineer will decide this once they see the topography, pit size, and ore body orientation. Adding ramps in a pit design pushes the crest outwards and adds waste to be stripped.

Pit Phases: After the pit design is complete, the mine engineer will design multiple interior phases to distribute the waste and ore tonnages in the mining schedule. These phases are sometimes referred to as pushbacks, laybacks, or stages. At mine start-up, one doesn’t want to strip the entire top off of a large pit. A smaller pit within the large pit will allow faster access to ore.

This completes the open pit design and now allows one to write to page 10 of Chapter 16. However, the mining engineer is not done yet.

Conclusion

This ends Part 1. In Part 2 we will discuss the mining engineer’s next tasks; production scheduling; waste dump design; and equipment selection. The mining engineer QP will sign off and take responsibility for all the mine design work done so far. You can read Part 2 at this link “The Anatomy of 43-101 Chapter 16 – Mining (Part 2)“.

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Don’t Cut Corners, Cut Cross-Sections Instead

Date: October 4, 2023 Author: Ken Kuchling Comments: Leave a reply

This article is about the benefit of preparing (cutting) more geological cross-sections and the value they bring.

Geological sections are one of the easiest ways to explain the character of an orebody. They have an inherent simplicity yet provide more information than any other mining related graphic.

Some sections can be simple cartoon-like images while others can be technically complicated, presenting detailed geological data.

Cartoon-stylized sections are typically used to describe the general nature of the orebody. The detailed sections can present technical data such as drill hole traces, color coded assays intervals, ore block grades, ore zone interpretations, mineral classifications, etc.

Sections provide a level of clarity to everyone, including to those new to the mining industry as well as those with decades of experience.

This article briefly describes what story I (as an engineer) am looking for in sections. Geologists may have a different view on what they conclude when reviewing geological sections.

I will describe the three types of geological sections that one can cut and what each may be describing. The three types are: (1) longitudinal (long) sections; (2) cross-sections; (3) bench (level) plans. Each plays a different role in helping to understand the orebody and mining environment.

There is also another way to share simple geological images via3D PDF files. I will provide an example later.

Longitudinal (Long) Sections

Long sections are aligned along the long axis of the deposit. They can be vertically oriented, although sometimes they may be tilted to follow the dip angle of an ore zone.

Long sections are typically shown for narrow structure style deposits (e.g. gold veins) and are typically less relevant for bulk deposits (e.g. porphyry).

The information garnered from long sections includes:

The lateral extent of the mineralized structure, which can be in hundred of metres or even kilometers. This provides a sense for how large the entire system is. Sometimes these sections may show geophysics, drilling to defend the basis for the regional interpretation.
Long sections will often highlight the drill hole pierce points to illustrate how well the mineralized zone is drilled off. Is the ore zone defined with a good drill density or are there only widely spaced holes? As well, long sections can show how deep ore zone has been defined by drilling. On some projects, a few widely spaced deep holes, although insufficient for resource estimation purposes, may confirm that the ore zone extends to great depth. This bodes well for potential development in that a long life deposit may exist.
Sometimes the long section drill intercept pierce points can be contoured on grade, thickness, or grade-thickness. This information provides a sense for the uniformity (or variability) of the ore zone. It also shows the elevations of the higher grade zones, if the deposit is more likely an open pit mine, an underground mine, or a combination of both.

Cross-Sections

Cross-sections are generally the most popular geological sections seen in presentations. These are vertical slices aligned perpendicular to the strike of the orebody. They can show the ore zone interpretation, drill holes traces, assays, rock types, and/or color-coded resource block grades.

As an engineer, my greatest interest is in seeing the resource blocks, color coded by grade. Sometimes open pit shells may be included on the section to define the potential mining volume. The engineering information garnered from block model cross-sections includes:

Where are the higher-grade areas located; at depth or near surface?
If a pit shell profile is included, what will the relative strip ratio look like? Are the ore zones relatively narrow compared to the size of the pit?
How will the topography impact on the pit shape? In mountainous terrain, will a push-back on pit wall result in the need to climb up a hillside and create a very high pit slope? This can result in high stripping ratios or difficult mining conditions.
Does the ore zone extend deeper and if one wants to push the pit a bit deeper, is there a high incremental strip ratio to do this? Does one need to strip a lot of waste to gain a bit more ore?
Are the widths of the mineable ore zones narrow or wide, or are there multiple ore zones separated by internal waste zones? This may indicate if lower-cost bulk mining is possible, or if higher cost selective mining is required to minimize waste dilution.
How difficult will it be to maintain grade control? For example, narrow veins being mined using a 10 metre bench height and 7 metre blast pattern will have difficulty in defining the ore /waste contacts.
Cross-sections that show the ore blocks color coded by classification (Measured, Indicated, Inferred), illustrate where the less reliable (Inferred) resources are located and how much relative tonnage may be in the more certain Measured and Indicated categories.

When looking at cross-sections, it is always important to look at multiple cross-sections across the orebody. Too often in reports one may be presented with the widest and juiciest ore zone, as if that was typical for the entire orebody. It likely is not typical.

Stepping away from that one section to look at others is important. Possibly the character of the ore zones changes and hence its important to cut multiple sections along the orebody.

Bench (Level) Plans

Bench plans (or level plans) are horizontal slices across the ore body at various elevations. In these sections one is looking down on the orebody from above.

Level plans are typically less common to see in presentations, although they are very useful. The level plans may show geological detail, rock types, ore zone interpretations, ore block grades, and underground workings.

The bench plan represents what the open pit mining crews would see as they are working along a bench in the pit. The information garnered from bench plans that include the block model grades includes:

Where are the higher-grade areas found on a level? Are these higher grade areas continuous or do they consist of higher grade pockets scattered amongst lower grade blocks?
Do the ore zones swell or pinch out on a bench? A vertical cross-section may give a false sense the ore zones are uniform. The bench plan gives an indication on how complicated mining, grade control, and dilution control might be for operators.
Do the ore zones on a bench level extend out beyond the pit walls and is there potential to expand the pit to capture that ore?
On a given bench what will the strip ratio be? Are the ore zones small compared to the total area of the bench?

As recommended with cross-sections, when looking at bench plans, one should try to look at multiple elevations. The mineability of the ore zones may change as one moves vertically upwards or downwards through a deposit.

Never mind cross-sections – give me 3D

While geological sections are great, another way to present the orebody is with 3D PDF files to allow users to view the deposit in three-dimensions. Web platforms like VRIFY are great, but I have been told they sometimes can be slow to use.

3D PDF files can be created by some of the geological software packages. They can export specific data of interest; for example topography, ore zone wireframes, underground workings, and block model information. These 3D files allows anyone to rotate an image, zoom in as needed and turn layers off and on.

You can also create your own simplistic cross-sections through the pdf menus (see image).

A simple example of such a 3D PDF file can be downloaded at this link (3D DPF File Example). It only includes two pit designs and some ore blocks to keep it simple.

The nice thing about these PDF files is that one doesn’t need a standalone viewer program (e.g. Leapfrog viewer) to view them. They are also not huge in size. As far as I know 3D PDF files only work with Adobe Reader, which most everyone already has. It would be good if companies made such 3D PDF files downloadable along with their corporate PowerPoint presentations.

Conclusion

The different types of geological sections all provide useful information. Don’t focus only on cross-sections, and don’t focus only on one typical section. Create more sections at different orientations to help everyone understand better.

In 2019 I wrote an article describing the lack of geological cross-sections in many 43-101 technical reports. The link to that article is her “43-101 Reports – What Sections Are Missing?”

Geological sections are some of the first items I look for in a report. Sometimes they can be hidden away in the appendices at the back of the report. If they are available, take the time to actually study them since they can explain more than you realize.

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Grade-Tonnage Curves – Worthy of a Good Look

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

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

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

Typical Grade-Tonnage Information

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

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

Useful Grade-Tonnage Curve Information

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

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

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

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

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

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

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

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

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

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

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

Reporting Waste Within a Shell

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

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

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

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

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

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

Spider Diagram Downsides

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

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

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

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

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

Conclusion

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

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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 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

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

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.

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.

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)

The Path to Resiliency

If one decides to pursue the path of operational flexibility, what are the things that help make it happen?

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.

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.

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.

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.

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:

GENERAL OBSERVATIONS:

Toll milling as a base case is most common in:

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

COMMERCIAL & CONTRACTUAL RISKS

METALLURGICAL RISKS

FINANCIAL & ROYALTY RISKS

REGULATORY & PERMITTING RISKS

STRATEGIC RISKS

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

REASONABLENESS OF ASSUMPTIONS

DISCLOSURE OF RISKS

METALLURGICAL COMPETENCE

INDEPENDENCE AND CONFLICTS OF INTEREST

SITE VISIT REQUIREMENTS

PRACTICAL AND PROFESSIONAL CONSEQUENCES

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.

end

END