Articles tagged with: 43-101

Junior Mining Shams and Scams – Part 2

Date: June 3, 2024 Author: Ken Kuchling Comments: Leave a reply

This is Part 2 of the blog post discussing junior mining scams and the sanctioning of those responsible. Part 1 can be found at this link “Junior Mining Shams and Scams – Part 1” and can be read first to get some background.

Part 2 provides examples involving professional Qualified Persons (QPs). We may have the feeling that QP’s are never held accountable for their work, but that is not always the case. There are numerous instances of QP’s being hauled off in front of their professional organizations for unprofessionalism. This blog will highlight some of those cases.

The lesson is that QP’s signing off on technical information for clients should be proficient in the nature of their work and need to know the reporting rules very well. Some of these incidents involve error and poor judgment, not outright fraud.

These examples involve in-house QP’s that work for a company while others involve independent QP’s that have been contracted by the company.

In most of these cases, any sanctions, if applied, were mainly doled out by the professional engineering or geological associations. The legal courts are often not involved.

Examples (Part 2)

Inaccurate QP Resource Estimate: This example relates to the Barkerville Gold Mines resource estimate complete in 2012. The mineral resource estimate had numerous errors and issues related to assays, capping, cutoff grades, etc. The allegation was the QP had demonstrated incompetence, unprofessional conduct, and negligence. The sanctions on the QP included a $15,000 fine, $20,000 legal costs, re-training, and license suspension.

Link 1:

Link 2:

False QP Statements: Here is an example from 2011. The QP / company Director was charged with multiple allegations, including stating the mine was in commercial production (when it wasn’t), leaving the impression there were mineral resource (which there weren’t any), and generally approving information that was not accurate. Ultimately the allegation was demonstrating incompetence, unprofessional conduct, and negligence. The resulting sanctions included 2 year license suspension, re-training, payment of $80,000 to the professional association.

Link 1:

False QP Statements: This is case were a resource QP failed to comply with the NI43-101, Form 43-101F1, CIM Standards, and CIM Guidelines. The Panel concluded that the Member was guilty of non-compliance with the standards and hence guilty of professional misconduct. Its not clear what specifically was not complied with, but this illustrates that QP’s will be held accountable for their work. The two reports in question were either amended or withdrawn to address the concerns of the regulator in British Columbia, although there had been no intentional non-compliance and no economic impact. The penalty was 2 months suspension (deferred), and the QP had to work under a mentor for 9 months and pay a maximum $10,000 for the mentor’s fees.

Link 1:

False QP Statements: Here is another example of sanctioning a QP in 2018. The person was charged with unprofessional conduct and incompetence. He stated that he was responsible for the preparation of the technical report, had no prior involvement in the project, and was independent of the issuer. This was false. Sanctions included three month license suspension, taking some re-training, require peer review of the report. In 2022, further sanctions consisted of a $75,000 penalty, further sanctioned along with an executive in the company for insider trading issues (see Link 3 below).

Link 1:

Link 2:

Link 3:

False QP Statements: This is an example for 2017 when an independent QP took responsibility for the resource estimation work in section 14 of the report, yet they did not have the experience to take responsibility. They also misrepresented that the Report complied with 2014 CIM standards, yet it didn’t, resulting in an overestimation of the mineral resource in both confidence and magnitude. Other claims include relying on non-QP experts but not stating that, failing to adequately discuss the nature of sample quality control procedures as required. The sanctions included license suspension of 3 months, must work with a technical supervisor, re-training, and $7,500 in legal fees.

Link 1:

False QP Statements: This is another example from 2019, when the QP / Director permitted the disclosure of information to the public in multiple news releases where they should have known that that information was misleading. An example is the disclosure of inferred reserves when there were no reserves and “inferred” is not even a classification of reserves. The sanctions were a license suspension of 4 months, $5,000 legal costs, re-training, and requirement not to act as a QP again.

Link 1:

QP Resource Estimate Error: This occurred in 2012 when a QP and consulting firm delivered a incorrect resource estimate and reportedly withheld negative opinions on the project from the client. The company spent $3 million on a feasibility study during which the resource estimate error was discovered. The “corrected” resource made the project uneconomic, meaning the feasibility study should not have been done. The mining company sought compensation from the consulting firm, ultimately receiving $1.25 million. The Link 3 references is interesting in that it states “As this case demonstrates, it is critically important for professional service firms to be forthcoming about any reservations they may have regarding the work they are being employed to undertake.” Whatever that really means?

Link 1:

Link 2:

Link 3:

Disclaimers

Many QP’s realize the legal responsibility and liability they have. Hence in 43-101 reports QP’s sometimes attempt to mitigate this by putting in broad disclaimers to limited that liability. If the securities commission notices such disclaimers, they will require that they be removed.

For example, sometimes the QP of a chapter may have other geologists or engineers (i.e. experts) assisting them. They may then put in disclaimers saying “They disclaim responsibility for such expert content” for the work done by the others. A QP essentially has to sign off on the work of others in the sections they are responsible for. A recent example is a Generation Mining technical report prepared by G-Mining, that had to be amended from (March 31_2023 to May 31_2024) removing several QP liability limiting disclaimers.

43-101 regulations state that “An issuer must not file a technical report that contains a disclaimer by any qualified person responsible for preparing or supervising the preparation of all or part of the report that

(a) disclaims responsibility for, or limits reliance by another party on, any information in the part of the report the qualified person prepared or supervised the preparation of;

or (b) limits the use or publication of the report in a manner that interferes with the issuer’s obligation to reproduce the report by filing it on SEDAR.“

” These disclaimers are also potentially misleading disclosure because, in certain circumstances, securities legislation provides investors with a statutory right of action against a qualified person for a misrepresentation in disclosure that is based upon the qualified person’s technical report.

That right of action exists despite any disclaimer to the contrary that appears in the technical report. The securities regulatory authorities will generally require the issuer to have its qualified person remove any blanket disclaimers in a technical report that the issuer uses to support its public offering document.“

Conclusion

This ends Part 2 of this blog post. It hopefully highlights the importance of QP’s being knowledgably on the disclosure rules and the technical aspects of what they are hired to do.

Companies should always ensure that only qualified QP’s are used for their project work, even if some of the others might be less expensive. The potential headaches and costs afterwards may override the higher upfront cost.

It should be noted that this Sham and Scam blog does not discuss the other less than desirable junior mining traits seen from time to time. These relate to; insider trading; abuse of micro-penny founder shares; and the ever present “pump & dump” schemes.

In closing, if anyone is aware of other good examples of QP issues, please provide any links to any publicly disclosed information. I can add them to the blog post.

Note: You can sign up for the KJK mailing list to get notified when new blogs are posted. Follow me on Twitter at @KJKLtd for updates and other mining posts. The entire blog post library can be found at https://kuchling.com/library/

Junior Mining Shams and Scams – Part 1

Date: May 30, 2024 Author: Ken Kuchling Comments: Leave a reply

Recently (in April 2024) Red Pine Exploration issued several press releases highlighting that some assays in their geological database were found to have been manipulated. Numerous assays input into their database did not match the original lab certificates. Is this another mining scam?

The Red Pine event led me to ask some colleagues about similar situations that have occurred and whether the personnel responsible were ever sanctioned. Their feedback provided me with several past examples of such incidents, which I have attempted to summarize in this two-part blog post. Big thanks to my colleagues that took the time to provide these examples.

Raise the Red Flag

The focus of this blog is on the types of activities that raised the red flags in the past. I am less interested in naming the people responsible, although the associated web links do provide more detail on the events.

Not all of the examples listed in these two blogs are scams or deliberate falsification of results. Some may be incompetence, faulty reporting, or lack of diligence and care. Some of these involve company executives, in-house Qualified Persons (QPs), and independent QP’s working for the companies.

Part 1 has examples mainly involving company management or in-house QPs. Part 2 will provide other examples where QP’s have been held to account for their poor quality of their work.

Examples (Part 1)

The following are presented in no particular order. Some of these may still be at the allegation or investigation stage. This blog post can be updated when the issue is eventually resolved.

Tampering with Samples: Bre-X salting of samples is the number one example of a well orchestrated scam. I’m not sure if anyone was ever officially convicted of anything at Bre-X, but it warranted several books, recent podcasts, and even a loosely-based Hollywood movie (Gold). As an aside, I had spoken with the Bre-X team in 1995 about consulting work while I was living in Calgary. However, they were still far from needing mine engineering services at that time. That would have been a wild ride, although with my luck, I would have ended up being the only one in jail. For further information here is an interesting story from Warren Irwin on the Bre-x story. https://redcloudfs.com/25-years-after-bre-x-by-the-man-who-made-a-fortune-going-long-short-of-the-biggest-ever-mining-fraud/

Falsifying QP Signature: The B.C. Securities Commission (BCSC) is alleging that a B.C.-based mining company and its CEO made false or misleading statements about an Idaho mineral deposit in a report that it filed. In 2019, Multi-Metal filed a technical report which contained an electronic signature of a qualified person – a professional engineer – and listed him as an author. The BCSC alleges the qualified person did not review, sign, or consent to filing Multi-Metal’s report. At this time, the BCSC’s allegations have not yet been proven.
Link 1

Falsifying Assay Data: The Ontario Securities Commission approved a settlement agreement between a geologist with 30 years of experience and the Qualified Person for Bear Lake Gold Ltd. Between 2007 and 2009 the QP altered certain assay results and transferred these results into the company’s assay database; prepared draft press releases that contained incorrect and inflated data, then provided Independent QP’s with the altered data, and also replaced core and modified a drill core log. In the settlement, the QP agreed to a permanent ban from acting as a Director and Officer of any issuer, an administrative penalty of $750,000, $50,000 in costs, and a prohibition from trading.
Link 1
Link 2
Link 3

Falsifying Assay Data: In 2024 Red Pine Exploration Inc. reported that there were 382 assay inconsistencies out of a total of 60,000 assay results for the 2019-2024 Period, representing 95 intersections contained within 69 drill holes as follows. An independent investigation is underway, however at the time of this blog, the investigation is still on-going. A link will be provided here once their final report is disclosed publicly.
Link 1

Tampering with Samples: This example goes back to 1981, involving New Cinch Uranium. They published test results that showed significant gold and silver at their New Mexico property. After the stock jumped, third party tests showed that samples did not contain any significant amount of precious metals. The New Cinch samples were “salted”. The Vancouver Stock Exchange was sued for not verifying the company’s test results. In response, the VSE made it compulsory for companies to issue a disclaimer on each press release stating that the VSE “neither approves nor disapproves of their contents”. This case goes back 40 years, so limited information is available on it. A bit more discussion on this case and discussing the VSE is found at the link below. While the VSE no longer exists, the TSX has taken over.
Link 1

Falsifying Assay Data: This example involves Southwestern Resources, a company with the Boka Project in China. The former CEO and President, John Paterson, was the company’s QP. In 2007, a month after Paterson’s resignation, Southwestern announced there were errors in previously reported assay results. As a result, Southwestern withdrew all of its previously disclosed results for that project. Sounds familiar? An independent investigation by Snowden led to a revised resource estimate that was substantially less than previously reported and identified 433 discrepancies in gold grades reported in dozens of 2003 and 2007. The original assay certificates were sent to Paterson and he was the sole recipient. Instead of transferring the true assay certificate data, Paterson transferred data containing discrepancies into the database. There was 6 years of jail time involved with this case.
Link 1
Link 2
Link 3
Link 4

Falsified Resource Estimate: This one goes back to 1997, although sanctioning of parties was only done in 2007. The company geologist was accused of several things, including not having adequate data to support the findings in his 1997 resource report; the methods used to calculate resources were not appropriate; the report portrayed the project as more advanced than it was; the $129 projected share value was based on “unsubstantiated tonnage and grade information and data.”. Exotic assaying methods and duping accredited investors was also part of this operation.
Link 1

Using Exploration Targets in Economic Analysis: This event goes back to 2012 and involves a company breaking the rules by disclosing the results of an economic analysis that included a target for further exploration (pie-in-the-sky) of the company’s gold mining operation. The economic analysis was not based on a current resource estimate. The punishment was the proponents had to pay to the commission $20,000 and complete a course of study on the requirements of Canadian mining rules.
Link 1

Conclusion

This ends Part 1 of this blog post. Part 2 will continue with a few more examples, specifically involving Qualified Persons, and can be found at this link Junior Mining Shams and Scams – Part 2

Discipline is typically rendered in two ways; the Security Commission may prosecute; or the professional associations will provide sanctions. Typically, the professional association penalties are more lenient, consisting of a temporary license suspension and the payment of legal fees.

If readers have any other examples of such junior mining stories, email them to me at kjkltd@rogers.com and I can add them to this blog.

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/

NPV a Disappointment? A Few Ways to Fix It

Date: April 5, 2024 Author: Ken Kuchling Comments: Leave a reply

So, you just completed your initial PEA cashflow model and the resulting NPV and IRR are a little disappointing. They are not what everyone was expecting. They don’t meet the ideal targets of an IRR greater than 30% and an NPV that is more than 2x the initial capital cost. The project could now be on life support in the eyes of some.

Now what to do? Its time to jump into NPV repair mode.

Hopefully this blog post isn’t too controversial but will lead to some discussion about how studies are done. Its based on observations I have made over the years as to what different studies will do to try to improve their economics.

The first thought typically is to lower (i.e. low ball) the capital and operating costs. We know that will certainly improve the economics. A risk with that is it might discredit the entire study if the costs are not in line with similar projects. Perhaps someone does a deep dive into the costing details or does some benchmarking against other projects. Also, advanced studies will develop more accurate costs, ultimately highlighting that the initial study was inaccurate and misleading. So overly optimistic, under-estimated costing is not a good approach.

What other things can help bump up the NPV? Let’s look at some of the ones I have seen, some of which I have applied in my work. I would expect (and hope) that some of these ideas will already have been adopted in the initial engineering and cashflow model.

Using the Time Value of Money

The discounting of cashflows in a cashflow model means that up-front revenues and costs have a bigger impact on the final economics than those far off in the future. This effect is amplified at higher discount rates.

Hence looking at ways to bring revenue forward or push costs backwards are typically the first options considered. Here are a few of the ways this will be done.

High Grading and Stockpiling: One can bring revenue forward by using a Low Grade Ore stockpiling strategy. Select an elevated cutoff grade to define High Grade Ore and send only that ore to the plant. The Low Grade Ore can be placed into a stockpile and processed gradually or all at once at the end of the mine life. One must mine more tonnes to undertake stockpiling and will eventually incur an ore rehandling cost. However, in my experience, the early revenue benefit from high grade normally outweighs the associated cost impacts.

Stockpiling Tramming: If using the stockpiling approach described above, many assume that all stockpile rehandling to the crusher will simply be done by tramming with a wheel loader. Having to re-load the ore into trucks will cost more than double the cost of tramming. So place the ore stockpiles close to the crusher to lower rehandling costs.

Milling Soft Ore: If the deposit has both an upper soft ore (oxide, saprolite) and a deeper hard ore, one can take advantage of the soft material and push more ore tonnage through the plant at start-up. This will increase the up-front revenue. It may also allow the cost deferral of some plant components that are only needed for processing the harder ore.

Defer Stripping Tonnages: Delaying some waste stripping costs from pre-production (Y-1) to Year 1 or Year 2 will help improve the NPV. However, care must be taken that increasing mining tonnages in Year 1 or 2 doesn’t trigger the purchase of additional loaders and trucks. The deferred tonnes need to be small enough not to trigger a fleet size increase or could negate the impact of the cost deferral.

Capitalize Waste Stripping: It may be possible to capitalize waste stripping for satellite pits and pit wall pushbacks to better align stripping costs with the timing of ore mining. Capitalizing waste stripping may result in lower short term taxable income since the entire expense is not immediately deducted. This can reduce tax liabilities and improve cash flow. Each situation may be unique.

Accelerate Depreciation: In some jurisdictions, tax laws permit accelerated depreciation rates. This will help to lower or eliminate taxable income in the early years. This boosts the after-tax cashflow in those years, bumping up the NPV. If accelerated depreciation is the case, enhancing revenue (by high grading) at the same time, gives an even bigger nudge to the NPV. Maximize the revenue during tax free periods.

Apply Tax Losses: On some projects there are historical corporate tax loss carry-overs. These losses allow one to offset future taxes payable in the early years. This help bump up the initial after-tax cashflows.

Leasing of Equipment: One can look at equipment leasing to defer some of the initial capital costs. Leasing will distribute the purchase cost over several years (typically 60 months). Although the lease interest will increase the total cost of the machine, the capital cost deferral likely results in an NPV benefit.

Use Contract Mining: To avoid the entire cost of purchasing major mining equipment, many will look to contract mining. In studies, sometimes contract mining costs are estimated or they can be derived from budgetary contractor quotes. At an early stage these contractor quotes might be quite “favorable” as the contractor tries to stay in the good books of the mining company. Contract mining will greatly reduce the mining equipment capital cost and can help the NPV, even if the unit mining costs may be slightly higher with a contractor.

Using Other Cashflow Tweaks

There are other tweaks that one can make to the cashflow model. Sometimes several of the small ones, when compounded together, will result in a significant impact. Here are some of the other cashflow model adjustments that I have seen.

Increase Metal Prices: Normally when selecting metal prices for the cashflow model one looks at; trailing averages; analyst consensus forecasts; marketing study forecasts; and prices being used in other current studies. It is usually simple to defend whatever price you wish to use. In a rising price environment, one can see what other recent studies have used and escalate those prices by 5%-10%. That likely won’t be viewed as unreasonable. After all, someone has to be the trailblazer in raising modelling metal prices.

Improve metal recoveries: At an early study stage, one may have limited number of metallurgical tests upon which to base the process recoveries. I have seen some bump up the recoveries slightly and add the statement “Further metallurgical testing, grind size optimization, and reagent optimization should improve the recovery above those shown by the current test work”. This can gain a bit of revenue at no extra cost.

Optimistic Dilution: It can be very difficult to predict ore mining dilution at an early stage. Two different engineers looking at he same mining method, may come up with different dilution assumptions. Hence one may have the opportunity to select an optimistic dilution. Lower dilution will increase the head grade to the mill and hence increase the revenue at no extra cost. Even a modest reduction in dilution will play its role in nudging up the NPV.

Reduction in Working Capital: Some cashflow models do not include the cost for working capital, while others will include it. Working capital is the money needed on hand to pay the monthly operating cost in Year 1 before payable revenue is generated. If difficulties arise in achieving commercial production, one wishes to have more working capital on hand. Working capital typical is 2-4 months of operating cost. To bump up NPV, some will use the lower range of 2 months working capital. Some will just omit working capital entirely. Take a look at the working capital needs and decide what is reasonable.

Buy the Royalty: Some projects may have the option for a company to buy out the royalty from the royalty holder. Although doing this may result in an upfront cost, the payable royalty saving may offset that up-front buy-out cost. At high metal prices, the royalty saving could be significant.

Reclamation Cost Equals Salvage Value: At the end of the mine life, the final closure and reclamation cost will be in the tens of millions of dollars. Although this cost is heavily discounted back to the start of the cashflow model, I have seen cases where it is assumed that salvage value of the mine and plant equipment is sufficient to pay the entire closure cost. I don’t know how realistic this is, but I have seen that assumption used.

Lower The Discount Rate: A few years ago, it seems the benchmark discount rate was 5% used in most studies. In 2024, the cost of capital has gone up. Hence many studies seem to be using 8%-10% as their base case. A project at the PEA stage today isn’t going to be built for a few years. Some can argue that interest rates will likely be lower in a few years, and so using 5% discount rate today is still reasonable. Conversely some will maintain that is is best to use what others are using so that current projects are all comparable.

Conclusion

Don’t let a disappointing NPV get you down. There may be a few ways to boost the NPV by applying some common practices. However, if after applying all of these adjustments, the NPV still isn’t great, something bigger may be required. That could be an entire project scope re-think.

Or go drill for more ore higher grade ore.

Or low-ball the cost estimates (just kidding).

I have heard that if the project requires fancy tax manipulation to make it work, then it isn’t a good project to begin with. If taxes are critical, the economics may be too marginal.

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/

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.

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/

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)“.

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/

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.

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/

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.

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/

Polymetallic Drill Results – Interesting or Not?

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

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

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

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

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

What can drill intercepts show

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

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

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

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

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

Economic Parameters

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

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

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

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

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

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

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

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

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

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

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

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

Drill Hole Assays Examples

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

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

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

Intervals of Interest Example

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

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

Insitu Rock Value vs Depth:

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

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

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

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

Insitu Rock Value vs Interval Length:

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

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

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

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

Conclusion

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

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

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

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

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

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

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

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/

Resources, Resources, and Mineral Reserves

Date: March 7, 2022 Author: Ken Kuchling Comments: 1 Reply

Every so often I like to comment on issues related to the way the mining industry does things. This is one of those posts.

Currently the mining industry reports their exploration results as either Mineral Resources or Mineral Reserves. In my opinion, these two categories do not adequately reflect the reality of the current mining environment. I would suggest using a three category approach, as will be described below.

The implementation of this approach would not result in any more technical effort. However, it would provide clarity for stakeholders and investors and compare companies on a more equitable basis.

The issue

In today’s world, it is an onerous task to permit, finance, build, and operate a new mine. This is a significant achievement.

An operating company will be generating revenue and should be recognized for that big step. Hence does it make sense for an operating company to report Mineral Reserves while a junior company that has simply completed a pre-feasibility study to also report Mineral Reserves?

Both companies could report identical Reserves, but those reserves would not be the same thing. One company has built a mine while the other may have spent a few months doing a paper study. One company’s reserves will actually be mined in the foreseeable future while the other company’s project may never see the light of day. Yet both companies are allowed to present the same Mineral Reserves.

As a mine operates, the remaining ore reserves will deplete over time. However, a company can add to their reserves by finding satellite ore bodies or converting inferred material into a higher classification. The net of these adjustments will be reflected in the corporate Mineral Reserve Statement for all their operations.

A company can also increase the corporate Mineral Reserves simply by completing a pre-feasibility or feasibility study on a new project. However, is this a true reflection of the Reserves upon which the company should be evaluated?

Suggestion

I would suggest that the three reporting categories be used instead of two, described as follows:

1 – Mineral Resources (insitu): This category is the same as the current Mineral Resources being reported according to NI43-101. It is based on reasonable prospects for economic extraction. Hence open pit resources would be reported within an optimized shell and underground reserves within approximate stope shapes. No external dilution or mining criteria would be applied, as is the current approach.

2 – Economic Resources: This would be a new category that would simply be the outcome from a pre-feasibility or feasibility study, which is currently being labelled a “Mineral Reserve”. This Economic Resource would incorporate mining criteria, Measured & Indicated classes only, a mine plan, and an economic analysis. The differentiation from Reserves is because the mine is not built yet.

3 – Mineral Reserves: This highest-level category could be reported only once a mine has reached commercial production. The Economic Resources would automatically convert to Mineral Reserves once production is achieved. As the mine continues to operate, and as new ore sources are identified, the Mineral Reserves would increase / decrease. The Mineral Reserves would represent the remaining ore tonnage at operating mines and only that.

This three-category approach would help separate mine operators from junior development companies. The industry should recognize the difference between companies and projects at different life-cycle stages and that they are not all directly comparable. A junior explorer could be reporting huge reserves, but without a mine being there, should that company be compared to a mine operator that has similar reserves?

This approach would identify situations whereby a company suddenly reports a sizeable increase in Reserves. Is it because they found more ore at an existing operation (a great event) or because they did a paper study on a new project?

As a clarification, if a mine gets placed onto care & maintenance, likely due to poor economics, then the remaining tonnes at the mine would no longer be considered Mineral Reserves and may have to revert to Economic Resources, although even that would be questionable.

Examples

Out of curiosity I randomly selected three companies (Yamana Gold, Eldorado Gold, Alamos Gold) to compare their total Mineral Reserve tonnages based on their operations versus study stage development projects. The results are show in the images below. The percentage of Reserves provided by their producing (P) mines varied and ranged from 14% to 51%. A significant proportion of their Reserves (49% to 86%) are still at the development (D) stage. One or two large study-stage projects can boost the corporate reserves significantly. This is not immediately evident when looking at the total Mineral Reserves being reported.

For most junior miners 100% of their Reserves are still at the study-stage. They should not be able to declare Mineral Reserves and appear on an equal footing with mine operators. Their company should only be comparable to other companies with advanced study-stage projects.

Conclusion

The foregoing discussion is a suggestion as to how the mining industry can recognize the achievement and economic reality of building a mine, i.e. by being allowed to report Mineral Reserves. All others only get to report Resources. This would help clarify what long term tonnages are actually being mined versus simply being studied on paper.

The suggested approach does not create additional work for the mining companies. However, it provides a much fairer and transparent comparison between companies.

Interestingly, NI43-101 specifies that one cannot mathematically add together Indicated and Inferred resources because they are view as materially different. However, in a corporate Mineral Reserve Statement one is allowed to combine Reserves at an operating mine with Reserves from a study. These two reserves, in my view, are even more materially different than Indicated and Inferred resources are.

Its great for a company to report Mineral Reserves from a pre-feasibility study. However if for some reason that mine never gets built, then those Reserves are valueless. Maybe years ago it was foregone conclusion that a positive feasibility study would result in the construction of a mine, so the risk was less. That is no longer the case and this fact should be recognized when defining and reporting Mineral Reserves.

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.

Let A.I. Help Target Your Infill Drilling

Date: November 8, 2021 Author: Ken Kuchling Comments: Leave a reply

From time to time I come across interesting new tech that I like to share with colleagues. The topic of this blog relates to solving the problem of defining an optimal infill drill program.

In the past I have worked on some PEA’s whose economics were largely based on Inferred ore. The company wanted to advance to the Pre-Feasibility (PFS) stage. However, before the PFS could start they would need additional drilling to convert much of the Inferred resource into Measured and Indicated resources.

I’ve seen similar experience with projects that are advance from PFS to FS where management has a requirement that the ore mined during the payback period consist of Measured classification.

The Problem

In both cases described above, it is necessary for someone to outline an infill drill program to upgrade the resource classification while also meeting other project priorities. The goal is to design an infill drill program with minimal time and cost yet maximize resource conversion. Possibly some resource expansion drilling, metallurgical sampling, and geotechnical investigations may be required at the same time.

I’m not certain how various resource geologists go about designing an infill drill plan. However, I have seen instances where dummy holes were inserted into the block model and then the classification algorithm was re-run to determine the new block model tonnage classification. If it didn’t meet the corporate objectives, then the dummy holes may be moved or new ones added, and the process repeated.

One would not consider such a trial & error solution as optimal. It may not necessarily meet the cost and time objectives although it may meet the resource conversion goals.

The Solution

The DRX Drill Hole and Reporting algorithm developed by Objectivity.ca uses artificial intelligence to optimize the infill drilling layout. It intends to match the QP/CP constraints with corporate/project objectives.

For example, does company management require 70% of the resource in M&I classifications or do they require 90% in M&I? Each goal can be achieved with a different drill plan.

The following description of DRX is based on discussions with the Objectivity staff as well as a review of some case studies. The company is willing to share these studies if you contact them.

The DRX algorithm relies on the resource classification criteria specified by the company QP. For example, the criteria could be something like “For a block to qualify as Measured, the average distance to the nearest three drill holes must be 30 m or less of the block centroid. For a block to qualify as Indicated, the average distance from the block centroid to the nearest three holes must be 50 m or less. For a block to qualify as Inferred it will generally be within 100 m laterally and 50 m vertically of a single drill hole.”

The DRX algorithm will use these criteria to optimize drill hole placement three dimensionally to deliver the biggest bang for the buck. Whatever the corporate objective, DRX will attempt to find an optimal layout to achieve it. The idea being that fewer well targeted holes may deliver a better value than a large manually developed drill program.

The DRX outcome will prioritize the hole drilling sequence in case the drill program gets cut short due to poor weather, lack of funding, or the arrival of the PDAC news cycle.

The DRX approach can also be used to optimally site metallurgical holes and/or geotechnical holes in combination with resource drilling if there are defined criteria that must be met (by location, ore type, rock type, etc.). The algorithm will rely on rules and search criteria developed by experts in those disciplines. It does not develop the rules, it only applies them.

DRX can also help optimize step-out drilling, such that the step-out distance will not be beyond the range that negates the use of the hole in a resource estimate. It can also consider geological structure in defining drill targets.

By optimizing the number of drill holes and their orientation, the company may see savings in drill pad prep, drilling costs, field support costs, and sample assaying.

One can even request drilling multiple holes from the same drill pad to minimize drill relocation costs and safety issues in difficult terrain.

A large benefit of DRX is to be able to examine what-ifs. For example, one may desire 85% of the resource to be M&I. However, if one is willing to accept 80%, then one may be able to save multiple holes and associated costs. Perhaps with the addition of just a few extra holes one could get to 90% M&I. These are optimizations that can be evaluated with DRX.

An Example

In the one case study provided to me, a $758,000 manually developed drill program would convert 96.6% of the Inferred resource to Indicated. DMX suggested that they could achieve 96.7% for $465,000. Alternatively they could achieve 94% conversion for $210,000. These are large reductions in drilling cost for small reductions in conversion rate. This may allow the drill-metres saved to be used for other purposes.

For that same project, a subsequent study was done to convert Indicated to Measured in a starter pit area. DRX concluded that a 5000-metre program could convert 62% of Indicated into Measured. A 12,000-metre program would convert 86%, A 16,000-metre program would achieve 92%.

So now company management can make an informed decision on either how much money they wish to spend or how much Measure Resource they want to have.

Conclusion

Although I have not yet worked with DRX, I can see the value in it. I look forward to one day applying it on a project I’m involved with to develop a better understanding of what goes in and what comes out. DRX hopes to become to resource drilling what Whittle has become to pit design – an industry standard.

The use of the DRX algorithm may help mitigate situations where, moving from a PEA to PFS, one finds that the infill program did not deliver as hoped on the resource conversion. Unfortunately, this leaves the PFS with less mineable ore than anticipated and sub-optimal economics.

New tech is continually being developed in the mining industry. Hopefully this is one we continue to see forward advancement. It makes sense to me and DRX could be another tool in the geologist toolbox. Check out their website at objectivity.ca

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.