Articles tagged with: Feasibility Study

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.

Blog 97 Charts

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.

Mining Financial Modeling – Make it Better!

Date: October 20, 2021 Author: Ken Kuchling Comments: Leave a reply

In my view one thing lacking in the mining industry today is a consistent approach to quantifying and presenting the risks associated with mining projects. In a blog written in 2015 titled “Mining Cashflow Sensitivity Analyses – Be Careful” I discussed the limitations of the standard “spider graph” sensitivity analysis often seen in Section 22 of 43-101 reports.

This blog post expands on that discussion by describing a better approach. A six-year time gap between the two articles – no need to rush I guess.

This blog summarizes excerpts from an article written by a colleague that specializes in probabilistic financial analysis. That article is a result of conversations we had about the current methods of addressing risk in mining. The full article can be found at this link, however selected excerpts and graphs have been reprinted here with permission from the author.

The author is Lachlan Hughson, the Founder of 4-D Resources Advisory LLC. He has a 30-year career in the mining/metals and oil gas industry as an investment banker and a corporate executive. His website is here 4-D Resources Advisory LLC.

Excerpts from the article

Mining can be risky

“The natural resources industry, especially the finance function, tends to use a static, or single data estimate, approach to its planning, valuation and M&A models. This often fails to capture the dynamic interrelationships between the strategic, operational and financial variables of the business, especially commodity price volatility, over time.”

“A comprehensive financial model should correctly reflect the dynamic interplay of these fundamental variables over the company life and commodity price cycles. This requires enhancing the quality of key input variables and quantitatively defining how they interrelate and change depending on the strategy, operational focus and capital structure utilized by the company.”

“Given these critical limitations, a static modeling approach fundamentally reduces the decision making power of the results generated leading to unbalanced views as to the actual probabilities associated with expected outcomes. Equally, it creates an over-confident belief as to outcomes and eliminates the potential optionality of different courses of action as real options cannot be fully evaluated.”

Monte Carlo can be risky

“Fortunately, there is another financial modeling method – using Monte Carlo simulation – which generates more meaningful output data to enhance the company’s decision making process.”

Monte Carlo simulation is not new. For example @RISK has been available as an easy to use Excel add-in for decades. Crystal Ball does much the same thing.

“Dynamic, or probabilistic, modeling allows for far greater flexibility of input variables and their correlation, so they better reflect the operating reality, while generating an output which provides more insight than single data estimates of the output variable.”

“The dynamic approach gives the user an understanding of the likely output range (presented as a normal distribution here) and the probabilities associated with a particular output value. The static approach is relatively “random” as it is based on input assumptions that are often subject to biases and a poor understanding of their potential range vs. reality (i.e. +/- 10%, 20% vs. historical or projected data range).”

“In the case of a dynamic model, there is less scope for the biases (compensation, optionality, historic perspective, desire for optimal transaction outcome) that often impact the static, single data estimates modeling process. Additionally, it imposes a fiscal discipline on management as there is less scope to manipulate input data for desired outcomes (i.e. strategic misrepresentation), especially where strong correlations to historical data exist.”

“It encourages management to consider the likely range of outcomes, and probabilities and options, rather than being bound to/driven by achieving a specific outcome with no known probability. Equally, it introduces an “option” mindset to recognize and value real options as a key way to maintain/enhance company momentum over time.”

Image from the 4-D Resources article

“In the simple example (to the right), the financial model was more real-world through using input variables and correlation assumptions that reflect historical and projected reality rather than single data estimates that tend towards the most expected value.”

“Additionally, the output data provide greater insight into the variability of outcomes than the static model Downside, Base and Upside cases’ single data estimates did.”

The tornado diagram, shown below the histogram, essentially is another representation of the spider diagram information. ie.e which factors have the biggest impact.

“The dynamic data also facilitated the real option value of the asset in a manner a static model cannot. And the model took less time to build, with less internal relationships to create to make the output trustworthy, given input variables and correlation were set using the @RISK software options. This dynamic modeling approach can be used for all types of financial models.”

To read the full article, follow this link.

Conclusion

image from 4-D Resources article

Improvements are needed in the way risks are evaluated and explained to mining stakeholders. Improvements are required given increasing complexity in the risks impacting on decision making.

The probabilistic risk evaluation approach described above isn’t new and isn’t that complicated. In fact, it can be very intuitive when undertaken properly.

Probabilistic risk analysis isn’t something that should only be done within the inner sanctums of large mining companies. The approach should filter down to all mining studies and 43-101 reports.

It should ultimately become a best practice or standard part of all mining project economic analyses. The more often the approach is applied, the sooner people will become familiar (and comfortable) with it.

Mining projects can be risky, as demonstrated by the numerous ventures that have derailed. Yet recognition of this risk never seems to be brought to light beforehand.

Essentially all mining projects look the same to outsiders from a risk perspective, when in reality they are not. The mining industry should try to get better in explaining this.

Management understandably have a difficult task in making go/no-go decisions. Financial institutions have similar dilemmas when deciding on whether or not to finance a project. You can read that blog post at this link “Flawed Mining Projects – No Such Thing as Perfection“

UPDATE: For those interesting in this subject, there is a follow up article by the same author published in January 2022 titled “Using Dynamic Financial Modeling to Enhance Insights from Financial Reports!“.

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.

Pit Optimization – More Than Just a “NPV vs RF” Graph

Date: October 14, 2021 Author: Ken Kuchling Comments: 3 Replies

In this blog I wish to discuss some personal approaches used for interpreting pit optimization data. I’m not going to detail the basics of pit optimization, assuming the reader is already familiar with it .

Often in 43-101 technical reports, when it comes to pit optimization, one is presented with the basic “NPV vs Revenue Factor (RF)” curve. That’s it.

Revenue Factor represents the percent of the base case metal price(s) used to optimize for the pit. For example, if the base case gold price is $1600/oz (100% RF), then the 80% RF is $1280/oz.

The pit shell used for pit design is often selected based on the NPV vs RF curve, with a brief explanation of why the specific shell was selected. Typically it’s the 100% RF shell or something near the top of the NPV curve.

However the pit optimization algorithm generates more data than just shown in the NPV graph. An example of that data is shown in the table below. For each Revenue Factor increment, the data for ore and waste tonnes is typically provided, along with strip ratio, NPV, Profit, Mining cost, Processing, and Total Cost at a minimum.

Luckily it is quick and easy to examine more of the data than just the NPV curve.

In many 43-101 reports, limited optimization analysis is presented. Perhaps the engineers did drill down deeper into the data and only included the NPV graph in the report for simplicity purposes. I have sometimes done this to avoid creating five pages of text on pit optimization alone, which few may have interest in. However, in due diligence data rooms I have also seen many optimization summary files with very limited interpretation of the optimization data.

Pit optimization is a approximation process, as I outlined in a prior post titled “Pit Optimization–How I View It”. It is just a guide for pit design. One must not view it as a final and definitive answer to what is the best pit over the life of mine since optimization looks far into the future based on current information, .

The pit optimization analysis does yield a fair bit of information about the ore body configuration, the vertical grade distribution, and addresses how all of that impacts on the pit size. Therefore I normally examine a few other plots that help shed light on the economics of the orebody. Each orebody is different and can behave differently in optimization. While pit averages are useful, it is crucial to examine the incremental economic impacts between the Revenue Factor shells.

What Else Can We Look At?

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

Conclusion

It’s always a good idea to drill down deeper into the optimization output data, even if you don’t intend to present that analysis in a final report. It will help develop an understanding of the nature of the orebody.

It shows how changes in certain parameters can impact on a pit size and whether those impacts are significant or insignificant. It shows if economics are becoming very marginal at depth. You have the data, so use it.

This discussion presents my views about optimization and what things I tend to look at. I’m always learning so feel free to share ways that you use your optimization analysis to help in your pit design decision making process.

As referred to earlier, there is a lot of uncertainty in the input parameters used in open pit optimization. These might include costs, recoveries, slope angles and other factors. If you would like to read more, the link to that post is here. “Pit Optimization–How I View It”.

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.

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

Date: October 8, 2020 Author: Ken Kuchling Comments: Leave a reply

Over the years I have been involved in numerous mining tradeoff studies. These could involve throughput rate selection, site selection, processing options, tailings disposal methods, and equipment sizing. These are all relatively straightforward analyses. However, in my view, one of the more technically interesting tradeoffs is the optimization of the open pit to underground crossover point.

The majority of mining projects tend to consist of either open pit only or underground only operations. However there are instances where the orebody is such that eventually the mine must transition from open pit to underground. Open pit stripping ratios can reach uneconomic levels hence the need for the change in direction.

The evaluation of the cross-over point is interesting because one is essentially trying to fit two different mining projects together.

Transitioning isn’t easy

There are several reasons why open pit and underground can be considered as two different projects within the same project.

There is a tug of war between conflicting factors that can pull the cross-over point in one direction or the other. The following discussion will describe some of these factors.

The operating cut-off grade in an open pit mine (e.g. ~0.5 g/t Au) will be lower than that for the underground mine (~2-3 g/t Au). Hence the mineable ore zone configuration and continuity can be different for each. The mined head grades will be different, as well as the dilution and ore loss assumptions. The ore that the process plant will see can differ significantly between the two.

When ore tonnes are reallocated from open pit to underground, one will normally see an increased head grade, increased mining cost, and possibly a reduction in total metal recovered. How much these factors change for the reallocated ore will impact on the economics of the overall project and the decision being made.

A process plant designed for an open pit project may be too large for the subsequent underground project. For example a “small” 5,000 tpd open pit mill may have difficulty being kept at capacity by an underground mine. Ideally one would like to have some satellite open pits to help keep the plant at capacity. If these satellite deposits don’t exist, then a restricted plant throughput can occur. Perhaps there is a large ore stockpile created during the open pit phase that can be used to supplement underground ore feed. When in a restricted ore situation, it is possible to reduce plant operating hours or campaign the underground ore but that normally doesn’t help the overall economics.

Some investors (and companies) will view underground mines as having riskier tonnes from the perspective of defining mineable zones, dilution control, operating cost, and potential ore abandonment due to ground control issues. These risks must be considered when deciding whether to shift ore tonnes from the open pit to underground.

An underground mine that uses a backfilling method will be able to dispose of some tailings underground. Conversely moving towards a larger open pit will require a larger tailings pond, larger waste dumps and overall larger footprint. This helps make the case for underground mining, particularly where surface area is restricted or local communities are anti-open pit.

Another issue is whether the open pit and underground mines should operate sequentially or concurrently. There will need to be some degree of production overlap during the underground ramp up period. However the duration of this overlap is a subject of discussion. There are some safety issues in trying to mine beneath an operating open pit. Underground mine access could either be part way down the open pit or require an entirely separate access away from the pit.

Concurrent open pit and underground operations may impact upon the ability to backfill the open pit with either waste rock or tailings. Underground mining operations beneath a backfilled open pit may be a concern with respect to safety of the workers and ore lost in crown pillars used to separate the workings.

Open pit and underground operations will require different skill sets from the perspective of supervision, technical, and operations. Underground mining can be a highly specialized skill while open pit mining is similar to earthworks construction where skilled labour is more readily available globally. Do local people want to learn underground mining skills? Do management teams have the capability and desire to manage both these mining approaches at the same time?

In some instances if the open pit is pushed deep, the amount of underground resource remaining beneath the pit is limited. This could make the economics of the capital investment for underground development look unfavorable, resulting in the possible loss of that ore. Perhaps had the open pit been kept shallower, the investment in underground infrastructure may have been justifiable, leading to more total life-of-mine ore recovery.

The timing of the cross-over will also create another significant capital investment period. By selecting a smaller this underground investment is seen earlier in the project life. This would recreate some of the financing and execution risks the project just went through. Conversely increasing the open pit size would delay the underground mine and defer this investment and its mining risk.

Conclusion

As you can see from the foregoing discussion, there are a multitude of factors playing off one another when examining the open pit to underground cross-over point. It can be like trying to mesh two different projects together.

The general consensus seems to be to push the underground mine as far off into the future as possible. Maximize initial production based on the low risk open open pit before transitioning.

One way some groups will simplify the transition is to declare that the underground operation will be a block cave. That way they can maintain an open pit style low cutoff grade and high production rate. Unfortunately not many deposits are amenable to block caving. Extensive geotechnical investigations are required to determine if block caving is even applicable.

Optimization studies in general are often not well documented in 43-101 Technical Reports. In most mining studies some tradeoffs will have been done (or should have been done). There might be only brief mention of them in the 43-101 report. I don’t see a real problem with this since a Technical Report is to describe a project study, not provide all the technical data that went into it. The downside of not presenting these tradeoffs is that they cannot be scrutinized (without having data room access).

One of the features of any optimization study is that one never really knows if you got it wrong. Once the decision is made and the project moves forward, rarely will someone ever remember or question basic design decisions made years earlier. The project is now what it is.

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 insights.

Are Engineers Too Pessimistic

Date: September 16, 2020 Author: Ken Kuchling Comments: 1 Reply

Geological colleagues have often joked that engineers are a pessimistic lot; they are never technically satisfied. The engineers will fire back that geologists are an overly optimistic lot; every speck of mineralization makes them ecstatic. Together they make a great team since each cancels the other out.

In my opinion engineers are often pessimistic. This is mainly because they have been trained to be that way. Throughout my own engineering career I have been called upon many times to focus on the downsides, i.e. what can happen that we don’t want to happen.

It starts early and continues on

This pessimism training started early in my career while working as a geotechnical engineer. Geotechnical engineers were always looking at failure modes and the potential causes of failure when assessing factors of safety.

Slope failure could be due to the water table, excess pore pressures, seismic or blast vibrations, liquefaction, unknown weak layers, overly steepen slopes, or operating error. As part of our job we had to come up with our list of negatives and consider them all. The more pessimistic view you had, the better job you did.

This training continued through the other stages of a career. The focus on negatives continues in mine planning and costing.

For example, there are 8,760 hours in a year, but how many productive hours will each piece of equipment provide? There will delays due to weather conditions, planned maintenance, unplanned breakdowns, inter-equipment delays, operator efficiency, and other unforeseen events. The more pessimistic a view of equipment productivity, the larger the required fleet. Geotechnical engineers would call this the factor of safety.

In the more recent past, I have been involved in numerous due diligences. Some of these were done for major mining companies looking at acquisitions. Others were on behalf of JV partners, project financiers, and juniors looking at acquisitions.

When undertaking a due diligence, particularly for a major company or financier, we are not hired to tell them how great the project is. We are hired to look for fatal flaws, identify poorly based design assumptions or errors and omissions in the technical work. We are mainly looking for negatives or red flags.

Often we get asked to participate in a Risk Analysis or SWOT analysis (Strengths-Weaknesses-Opportunities-Threats) where we are tasked with identifying strengths and weaknesses in a project.

Typically at the end of these SWOT exercises, one will see many pages of project risks with few pages of opportunities.

The opportunities will usually consist of the following cliches (feel free to use them in your own risk session); metal prices may be higher than predicted; operating costs will be lower than estimated; dilution will be better than estimated; and grind size optimization will improve process recoveries.

The project’s risk list will be long and have a broad range. The longer the list of risks, the smarter the review team appears to be.

Investing isn’t easy

After decades of the training described above, it becomes a challenge for me to invest in junior miners. My skewed view of projects carries over into my investing approach, whereby I tend to see the negatives in a project fairly quickly. These may consist of overly optimistic design assumptions or key technical aspects not understood in sufficient depth.

Most 43-101 technical reports provide a lot of technical detail; however some of them will still leave me wanting more. Most times some red flags will appear when first reviewing these reports. Some of the red flags may be relatively inconsequential or can be mitigated. However the fact that they exist can create concern. I don’t know if management knows they exists or knows how they can mitigate them.

It has been my experience that digging in a data room or speaking with the engineering consultants can reveal issues not identifiable in a 43-101 report. Possibly some of these issues were mentioned or glossed over in the report, but you won’t understand the full extent of the issues until digging deeper.

43-101 reports generally tell you what was done, but not why it was done. The fact I cannot dig into the data room or speak with the technical experts is what has me on the fence. What facts might I be missing?

Statistics show that few deposits or advanced projects become real mines. However every advanced study will say that this will be an operating mine. Many projects have positive feasibility studies but these studies are still sitting on the shelf. Is the project owner a tough bargainer or do potential acquirers / financiers see something from their due diligence review that we are not aware of? You don’t get to see these third party reviews unless you have access to the data room.

My hesitance in investing in some companies unfortunately can be penalizing. I may end up sitting on the sidelines while watching the rising stock price. Junior mining investors tend to be a positive bunch, when combined with good promotion can result in investors piling into a stock.

Possibly I would benefit by putting my negatives aside and instead ask whether anyone else sees these negatives. If they don’t, then it might be worth taking a chance, albeit making sure to bail out at the right time.

Often newsletter writers will recommend that you “Do your own due diligence”. Undertaking a deep dive in a company takes time. In addition I’m not sure one can even do a proper due diligence without accessing a data room or the consulting team. In my opinion speaking with the engineering consultants that did the study is the best way to figure things out. That’s one reason why “hostile” due diligences can be difficult, while “friendly” DD’s allow access to a lot more information.

Conclusion

Sometimes studies that I have been involved with have undergone third party due diligence. Most times one can predict ahead of time which issues will be raised in the review. One knows how their engineers are going to think and what they are going to highlight as concerns.

Most times the issue is something we couldn’t fully address given the level of study. We might have been forced to make best guess assumptions to move forward. The review engineers will have their opinions about what assumptions they would have used. Typically the common comment is that our assumption is too optimistic and their assumption would have been more conservative or realistic (in their view).

Ultimately if the roles were reversed and I were reviewing the project I may have had the same comments. After all, the third party reviewers aren’t being hired to say everything is perfect with a project.

The odd time one hears that our assumption was too pessimistic. You usually hear this comment when the reviewing consultant wants to do the next study for the client. They would be a much more optimistic and accommodating team.

To close off this rambling blog, the next time you feel that your engineers are too negative just remember that they are trained to be that way. If you want more positivity, hang out with a geologist (or hire a new grad).

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 insights.

Vertical Conveyors Give Mining a Lift

Date: August 24, 2020 Author: Ken Kuchling Comments: 3 Replies

There are not many things that are novel to me after having worked in the mining industry for almost 40 years. However recently I came across a mining technology that I had heard very little about. It’s actually not something new, but it has never been mentioned as a materials handling option on any project that I am aware of.

That innovative technology is vertical conveying. Not long ago I read about a vertical conveyor being used at the Fresnillo underground mine, hoisting 200 tph up from a depth of 400 metres and had a capital cost of $12.7 million.

I was aware of steep angle conveyors being used in process plants. However they tended to be of limited height and have idlers and hardware along their entire length. Vertical conveyors are different from that.

After doing a bit of research, I discovered that vertical conveyors have been used since the 1970’s. Their application was mainly in civil projects; for example in subway construction where one must elevate rock from the excavation level up to street level. The mining industry is taking vertical conveyors to the next level.

I have never personally worked with vertical conveyors. Therefore I am providing this discussion based on vendor information. My goal is to create awareness to readers so that they might consider its application for their own projects.

How vertical conveying works

The background information on vertical conveying was provided to me by FKC-Lake Shore, a construction contractor that installs these systems. FKC itself does not fabricate the conveyor hardware. A link to their website is here.

The head station and tail station assemblies are installed at the top and bottom of a shaft. The conveyor belt simply hangs in the shaft between these two points. There is no need for internal guides or hardware down the shaft. The conveyor belting relies on embedded steel cables for tensile strength and pockets (or cells) to carry the material.

The Pocketlift conveyor system is based on the Flexowell technology. This has been advanced for deep underground applications with a theoretical lift height of 700 metres in one stage. The power transfer is achieved by two steel cord belts that are connected with rigid cross bars. The ore is fed into rubber pockets, which are bolted onto the cross bars. The standard Pocketlift can reaches capacities up to 1,500 m3/h and lift heights up to 700 m, while new generations of the technology may achieve capacities up to 4,000 m3/h.

The FLEXOWELL®-conveyor system is capable of running both horizontally and vertically, or any angle in between. These conveyors consist of FLEXOWELL®-conveyor belts comprised of 3 components: (i) Cross-rigid belt with steel cord reinforcement; (ii) Corrugated rubber sidewalls; (iii) transverse cleats to prevent material from sliding backwards. They can handle lump sizes varying from powdery material up to 400 mm (16 inch). Material can be raised over 500 metres with reported capacities up to 6,000 tph.

The benefits of vertical conveying

Vendors have evaluated the use of vertical conveying against the use of a conventional vertical shaft hoisting. They report the economic benefits for vertical conveying will be in both capital and operating costs.

Reduced initial capital cost due to:

Smaller shaft excavation diameter,
Reduced cost of structural supports vs a typical shaft headframe,
Structural supports are necessary only in the loading and unloading zones and no support structures in the shaft itself since the belt hangs free.

Lower operating costs due to:

Significantly reduced power consumption and peak power demand,
Lower overall maintenance costs,
No shaft inspections required,
The belt is replaced every 8 – 10 years.

Conclusion

I consider vertical conveying as another innovation in the mining industry. There may be significant energy and cost benefits associated with it when compared to conventional shaft hoisting or truck haulage up a decline.

With raise boring, one can develop relatively low cost shafts for the vertical conveyor. Hardware installation would be required only at the top and bottom of the shaft, not inside it.

The vendors indicate the conveying system should be able to achieve heights of 700 metres. This may facilitate the use of internal shafts (winzes) to hoist ore from even greater depths in an expanding underground mine. It may be worth a look at your mine.

As stated earlier, I have no personal experience with vertical conveying. Undoubtedly there may be some negative issues associated with the system that I am currently unaware of.

I would appreciate anyone sharing their experience with these conveyors either in a civil application or a mining environment. I will gladly update this blog article with additional observations or comments.

Update: for those interested in open pit applications for high angle conveyors, here is a recent article. This is a 37 degree angle 3,000 tph sandwich belt, which is different than the vertical conveyors discussed above.

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 insights.

Heap Leach or CIL or Maybe Both

Date: July 14, 2020 Author: Ken Kuchling Comments: 1 Reply

Typically gold mines consist of either a heap leach (HL) operation or a CIL type plant. There are a few projects that operate (or are considering) concurrent heap leach and CIL operations. Ultimately the mineral resource distribution determines if it makes economic sense to have both. This blog discusses this concept based on past experience.

A CIL operation has higher capital and operating costs than a heap leach. However that higher cost is offset by achieving improved gold recovery, perhaps 20-30% higher. At higher gold prices or head grades, the economic benefit from improved CIL recovery can exceed the additional cost incurred to achieve that recovery.

Some background

Several years ago I was VP Engineering for a Vancouver based junior miner (Oromin Expl) who had a gold project in Senegal. We were in the doldrums of Stage 3 of the Lassonde Curve (read this blog to learn what I mean) having completed our advanced studies. Our timeline was as follows.

Initially in August 2009 we completed a Pre-Feasibility Study for a standalone CIL operation. Subsequently in June 2010 we completed a Feasibility Study. The technical aspects of Stage 2 were done and we were entering Stage 3. Now what do we do? Build or wait for a sale?

The property’s next door neighbor was the Teranga Sabodala operation. It made sense for Teranga to acquire our project to increase their long term reserves. It also made sense for a third party to acquire both of us. The Feasibility Study also made the economic case to go it alone and build a mine.

While waiting for various third-party due diligences to be completed, the company continue to do exploration drilling. There were still a lot of untested showings on the property and geologists need to stay busy.

Two years later in 2013 we completed an update to the CIL Feasibility Study based on an updated resource model. Concurrently our geologists had identified seven lower grade deposits that were not considered in the Feasibility Study.

These deposits had gold grades in the range of 0.5 to 0.7 g/t compared to 2.0 g/t for the deposits in the CIL Feasibility Study. We therefore decided to also complete a Heap Leach PEA in 2013, looking solely on the lower grade deposits.

These HL deposits were 2-8 km from the proposed CIL plant so their ore could be shipped to the CIL plant if it made economic sense. Test work had indicated that heap leach recoveries could be in the range of 70% versus >90% with a CIL circuit. The gold price at that time was about $ 1,100/oz.

Ultimately our project was acquired by Teranga in the middle of 2013.

Where should the ore go?

With regards to the Heap Leach PEA, we did not wish to complicate the Feasibility Study by adding a new feed supply to that plant from mixed CIL/HL pits. The heap leach project was therefore considered as a separate satellite operation.

The assumption was that all of the low grade pit ore would go only to the heap leach facility. However, in the back of our minds we knew that perhaps higher grade portions of those deposits might warrant trucking to the CIL plant.

For internal purposes, we started to look at some destination trade-off analyses. We considered both hard (fresh rock) and soft ore (saprolite) separately. CIL operating costs associated with soft ore would be lower than for hard ore. Blasting wasn’t required and less grinding energy is needed. The CIL plant throughput rate could be 30-50% higher with soft ore than with hard ore, depending on the blend.

I have updated and simplified the trade-off analysis for this blog. Table 1 provides the costs and recoveries used herein, including increasing the gold price to $1500/oz.

The graph shows the profit per tonne for CIL versus HL processing methods for different head grades.

The cross-over point is the head grade where profit is better for CIL than Heap Leach. For soft ore, this cross-over point is 0.53 g/t. For hard ore, this cross over point is at 0.74 g/t.

The cross-over point will be contingent on the gold price used, so a series of sensitivity analyses were run.

The typical result, for hard ore, is shown in Table 2. As the gold price increases, the HL to CIL cross-over grade decreases.

These cross-over points described in Table 2 are relevant only for the costs shown in Table 1 and will be different for each project.

Conclusion

It may make sense for some deposits to have both CIL and heap leach facilities. However one should first examine the trade-off for the CIL versus HL to determine the cross-over points.

Then confirm the size of the heap leach tonnage below that cross-over point. Don’t automatically assume that all lower grade ore is optimal for the heap leach.

If some of the lower grade deposits are further away from the CIL plant, the extra haul distance costs will tend to raise their cross-over point. Hence each satellite pit would have its own unique cross-over criteria and should be examined individually.

Since Teranga complete the takeover in mid 2013, we were never able to pursue these trade-offs any further.

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 insights.

Mining’s Lassonde Curve – A Wild Ride

Date: June 24, 2020 Author: Ken Kuchling Comments: 11 Replies

Normally I don’t write about mining stock markets, preferring instead to focus on technical matters. However I have seen some recent discussions on Twitter about stock price trends. For every stock there are a wide range of price expectations. Ultimately some of the expectations and realizations can be linked back to the Lassonde Curve.

The Lassonde Curve has been touted by many as a realistic representation of the life stages of a junior mining company. The curve can sometimes be a roller coaster ride for company management.

Pierre Lassonde, was one of the founders of Franco-Nevada, the first gold royalty company. Thirty years ago he created his curve, that has now become a foundation in the junior mining business. The Lassonde Curve outlines the company life stages, beginning at exploration and ending at production. It shows the perceived value (i.e. stock value) that investors may assign at each life stage.

The stock price trend illustrated by the curve can, knowingly or unknowingly, impact on a company’s decision making process. So in effect, there are some technical ramifications from it.

People may have differing opinions on what factors are driving the curve. Take a look at it and decide for yourself. Typically people define the curve into four life stages, but I tend to view it in five stages.

Mining Company Stages 1 to 5

Stage 1 Climb

Stage 1 is the earliest stage, consisting of exploration. This period generates rising anticipation from promotion and exciting press releases. The stock value climbs as the perceived value of the insitu geology increases. Great Bear is an example of company currently in Stage 1 (as of June 2020), and appears to be in no hurry to exit from Stage 1.

Stage 2 is when the prospect moves into technical evaluation. In other words, the engineers now climb aboard the ride. This stage encompasses the PEA, PFS, and FS studies. Each of these can take months to complete, meantime new information releases may be lacking.

If the stock value declines, perhaps its because the engineers bring reality into the picture. Investors may see that the project isn’t as easy or great as they anticipated during Stage 1.

Companies can also lose some presence in the market with no new news. Investors may begin looking at other companies that are still in Stage 1 and hence sell their shares.

Some companies may try to shorten Stage 2 and even skip over Stage 3 by going from a PEA directly into Stage 4 construction.

Stage 3 is the period when the studies have largely been completed and a production decision is pending. At this time the company will be seeking strategic partners and project funding. Permitting is also underway. Unfortunately a lack of financing or poor permitting efforts will extend the time in Stage 3, which can extend for decades or even perpetuity. It’s easy to rattle off the names of companies sitting in Stage 3; for example Donlin Creek, Casino, KSM, and Galore Creek. It seems that once locked in a prolonged Stage 3, it can be difficult to get out of it. Company promotion and marketing can be difficult.

Stage 4 begins when the financing is done and construction begins. This is a sign that the project has been figured out, permits approved, and third-party due diligence found no fatal flaws. The stock value may increase on this positive news, especially if construction is on time and on budget. Its even better news if it’s a period of rising commodity prices.

Stage 5 is the start-up and commercial production period, possibly nerve-racking for some investors. This is where the rubber hits the road. The stock price can fall if milled grades, operating costs, or production rates are not as expected.

Investors may need to decipher press releases to figure out if things are going well or not. Some investors may now bail out at this time to companies in Stage 1 for greater upside (the 10 bagger).

Companies Staying front and center

Companies know that investors can move elsewhere at any time, so they will try to address the Stage 2 and Stage 3 doldrums in different ways. They can:

Find new exploration prospects elsewhere while the engineering work is underway.
Undertake a series of optimization studies on the same project to keep up the news flow.
Continue step out drilling on the same property to expand resources and generate new excitement.
Have management appear regularly on podcasts, webinars, conferences, and keep promoting on LinkedIn, Twitter, and with newsletter writers.

Ideally one would like to stagger multiple prospects at different stages of the Curve. While this makes sense, it also takes a fair bit of funding to do it. It also may bring criticism that the company is losing focus on their flagship project. Generally if the stock price is improving, you don’t see this complaint.

Conclusion

In closing, I just wanted to present the Lassonde Curve for those who may not have seen it before. For those playing the junior stocks, it may help explain why their prices fluctuate for essentially the same project. For some companies, the curve can be a wild ride.

Some corporate presentations will highlight the Lassonde Curve, particularly when they are rising in Stage 1. You are less likely to see the curve presented when they are rolling along in Stages 2 or 3.

Some say the Curve relates to the de-risking of a project as it advances, with risks shifting from exploration related to development related. That may be true, but I suggest the curve is simply based on investor perception and impatience.

The ability to promote oneself and stay relevant in the market plays a key role in defining the shape of a company’s curve.

As a final note, people looking at the Lassonde curve often focus on the rise and dip in the middle part. There is less focus on what happens on the far right side of the graph as it trends into the future. There is an often (but forgotten) dip there too.

Another interesting aspect of the junior mining industry is how the herd mentality and fear of missing out is standard operating policy. Companies will rush into areas, acquire whatever ground they can, as long they can tout it as being a certain commodity project. And its not only commodities that generate excitement; its also locations and technologies. Read more at the blog post “Mining Fads and the Herd Mentality“.

The entire blog post library can be found at this LINK with topics ranging from geotechnical, financial modelling, and junior mining investing.

Note: You can sign up for the KJK mailing list to get notified when new blogs are posted. Follow us on Twitter at @KJKLtd for updates and insights.

Pre-Concentration – Maybe Good, Maybe Not

Date: June 2, 2020 Author: Ken Kuchling Comments: Leave a reply

A while back I wrote a blog titled “Pre-Concentration – Savior or Not?”. That blog was touting the benefits of pre-concentration. More recently I attended a webinar where the presenter stated that the economics of pre-concentration may not necessarily be as good as we think they are.

My first thought was “this is blasphemy”. However upon further reflection I wondered if it’s true. To answer that question, I modified one of my old cashflow models from a Zn, Pb project using pre-concentration. I adjusted the model to enable running a trade-off, with and without pre-con by varying cost and recovery parameters.

Main input parameters

The trade-off model and some of the parameters are shown in the graphic below. The numbers used in the example are illustrative only, since I am mainly interested in seeing what factors have the greatest influence on the outcome.

The term “mass pull” is used to define the quantity of material that the pre-con plant pulls and sends to the grinding circuit. Unfortunately some metal may be lost with the pre-con rejects. The main benefit of a pre-con plant is to allow the use of a smaller grinding/flotation circuit by scalping away waste. This will lower the grinding circuit capital cost, albeit slightly increase its unit operating cost.

Concentrate handling systems may not differ much between model options since roughly the same amount of final concentrate is (hopefully) generated.

Another one of the cost differences is tailings handling. The pre-con rejects likely must be trucked to a final disposal location while flotation tails can be pumped. I assumed a low pumping cost, i.e to a nearby pit.

The pre-con plant doesn’t eliminate a tailings pond, but may make it smaller based on the mass pull factor. The most efficient pre-concentration plant from a tailings handling perspective is shown on the right.

The outcome

The findings of the trade-off surprised me a little bit. There is an obvious link between pre-con mass pull and overall metal recovery. A high mass pull will increase metal recovery but also results in more tonnage sent to grinding. At some point a high mass pull will cause one to ask what’s the point of pre-con if you are still sending a high percentage of material to the grinding circuit.

The table below presents the NPV for different mass pull and recovery combinations. The column on the far right represents the NPV for the base case without any pre-con plant. The lower left corner of the table shows the recovery and mass pull combinations where the NPV exceeds the base case. The upper right are the combinations with a reduction in NPV value.

The width of this range surprised me showing that the value generated by pre-con isn’t automatic. The NPV table shown is unique to the input assumptions I used and will be different for every project.

The economic analysis of pre-concentration does not include the possible benefits related to reduced water and energy consumption. These may be important factors for social license and permitting purposes, even if unsupported by the economics. Here’s an article from ThermoFisher on this “How Bulk Ore Sorting Can Reduce Water and Energy Consumption in Mining Operations“.

Conclusion

The objective of this analysis isn’t to demonstrate the NPV of pre-concentration. The objective is to show that pre-concentration might or might not make sense depending on a project’s unique parameters. The following are some suggestions:

1. Every project should at least take a cursory look at pre-concentration to see if it is viable. This should be done on all projects, even if it’s only a cursory mineralogical assessment level.

2. Make certain to verify that all ore types in the deposit are amenable to the same pre-concentration circuit. This means one needs to have a good understanding of the ore types that will be encountered.

3. Anytime one is doing a study using pre-concentration, one should also examine the economics without it. This helps to understand the economic drivers and the risks. You can then decide whether it is worth adding another operating circuit in the process flowsheet that has its own cost and performance risk. The more processing components added to a flow sheet, the more overall plant availability may be effected.

4. The head grade of the deposit also determines how economically risky pre-concentration might be. In higher grade ore bodies, the negative impact of any metal loss in pre-concentration may be offset by accepting higher cost for grinding (see chart on the right).

5. In my opinion, the best time to decide on pre-con would be at the PEA stage. Although the amount of testing data available may be limited, it may be sufficient to assess whether pre-con warrants further study.

6. Don’t fall in love with or over promote pre-concentration until you have run the economics. It can make it harder to retract the concept if the economics aren’t there.