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/

Mine Builders vs Mine Vendors

Date: October 15, 2023 Author: Ken Kuchling Comments: Leave a reply

Normally when Major or Intermediate miners advance their projects through the study stages, they usually have the intent to build the mine at some time. Sometimes they may decide to sell the project if it no longer fits in their corporate vision or if they desperately need some cash. However, selling the project was likely not their initial intent.

On the other hand, Junior miners tend to follow one of two paths. They are either on (a) the Mine Builder path, or (b) the Mine Vendor path (i.e. sell the project). In this article, I will present some examples of companies on each path. There will also be some discussion on whether the engineers undertaking the early stage studies (e.g., PEA’s) should be considering the path being followed.

The Mine Builder Path

The Mine Builder generally follows a systematic approach, as sketched out in the image below. The project advances from drilling to Mineral Resource Estimate (MRE), scoping study (PEA), then through the Pre-Feasibility Study (PFS) and/or Feasibility Study (FS) stages. Environmental permitting is normally proceeding in conjunction with the engineering. Once the FS is complete, the next hurdles for the Mine Builder are financing and construction. The path is fairly orderly.

The amount of the exploration drilling is only needed to define an economic resource to the Measured and Indicated classifications. There is no requirement to delineate the mineral resource on the entire property since there will be time to do that during production. Demonstrating an economic resource, with some upside potential, is often sufficient for the Mine Builder.

Three examples of companies on the Builder path are shown below; Orla Camino Rojo gold project (in operation), SilverCrest Las Chispas gold project (in operation), and Nexgen Rook uranium project (financing stage). Although the duration of each timeline is different due to different project complexities, the development paths are consistent. Most junior miners would not consider themselves on the Builder path.

The Mine Vendor Path

Mine Vendor type organizations have the primary goal of selling their project. These companies may consist of management teams that don’t have the desire, comfort, or capability to put a mine into production. For example, this is often the case with companies founded by exploration geologists, whereby their plan is to explore, grow, and sell all (or part) of the project. In other cases the Junior miner realizes their project is large with a high capital cost. That capital cost is beyond the financial capability of the company. Hence a deep-pocket partner is required or an outright sale is preferred.

The Mine Vendors tend to follow a different development path than the Mine Builders. They don’t have the same long term objectives. Vendors want out at some point.

The Vendor path can be more irregular, with multiple studies undertaken at different levels of detail, sometimes stepping back to lower level of studies as more information is acquired. Their object is to make the project look good to potential buyers, and look better than their junior miner competitors also for sale. Often this ongoing project improvement process is termed “de-risking”.

Not only must the Vendors demonstrate an economic resource, they must demonstrate a highly valuable resource to maximize the acquisition price for the shareholders. They will try to do this through multiple drill campaigns followed by multiple studies, each one looking better than the prior one.

Sometimes you will see a management team indicate that, if the project isn’t sold, they are going to put it into production themselves. This may be true in some cases, or simply part of the negotiating game to try to maximize the acquisition price.

Two quick examples of companies on the Vendor path are shown below: Western Copper Casino project and Seabridge KSM project. The durations of these development timelines are extensive and expensive, while waiting for an interested buyer. During these periods, the companies may continue to spend money de-risk the project further. The hope is that the company can eventually make the project attractive or that changing market conditions will make it attractive for them. Unfortunately, there is always the possibility that no buyer will ever come along.

Engineer’s Perspective

One question is whether the independent geologists and engineers working on the advanced studies should be aware of the path the company is following. Is the company a Builder or a Vendor?

Some may feel that the technical work should be independent of the path being followed. Based on my experience as both an owner’s representative and independent study QP, I have a somewhat different opinion. The technical work should be tailored to the intended path.

The Engineer on the Mine Builder Path:

If an engineer understands that a Mine Builder’s project will move from PEA to PFS to FS in rapid succession, then there is more incentive to ensure each study is somewhat integrated.

For example, a PEA will use Inferred resources in the economics. However, if the project will advance to the PFS stage, where Inferred cannot be used, then it is important for the PEA to understand the role that Inferred plays in the economics. How much drilling will be needed to upgrade Inferred resource to Indicated for the PFS, if needed at all?

Typically, capital costs tend to increase as advancing studies get more accurate due to greater levels of engineering. A Builder wants to avoid large cost increases when moving from PEA to PFS to FS. Therefore, when costing at the PEA stage, one may wish to increase contingency or use conservative design assumptions. After all, one is not trying to sell or promote the project internally, but rather move it towards production.

There is no value to the Mine Builder by fooling themselves with low-balled cost estimates. (Although some may argue there is still a desire to low ball costs to get management to approve the project). Conversely Mine Vendors do have some incentive to low ball the costs.

Perhaps some of the recent project capital cost over-runs we have seen is that the Vendor mentality was used at the PEA stage to optimistically set the capital cost baseline. Subsequent studies were then forced to conform to that initial baseline. Ultimately construction will be the arbiter on the true project cost. Hence there is no real value in underestimating costs, ultimately making management appear incompetent if costs do over-run.

The Mine Builder will also be advancing environmental permitting simultaneously with their advanced studies. Hence at the early stage (PEA) it is important to properly define the site layout, processing method, production rate, facility locations, etc. since they all feed into the permitting documents.

Changing significant design details in the future will set back the permitting and construction timelines. Hence, for the Mine Builder, the engineers should focus on getting the design criteria mostly correct at the PEA stage. For the Mine Vendor, this is not as important since multiple studies are being planned for in the future anyway.

The Engineer on the Mine Vendor Path:

The objective of the Mine Vendor is to make the project attractive to potential buyers. There is less urgency in fast tracking detailed engineering and permitting.

It is not uncommon to see multiple drilling programs, followed my multiple studies of scenarios with different size, production rate, and layout. The degree of engineering conservativeness in design and costing is less critical since future studies may be on substantially different sized projects.

The role that the Inferred resource plays in the economics is also less important at this time, since a lot more drilling may be coming. The Vendor’s objective tends to be on maximizing resource size not necessarily optimizing resource classification.

While the Mine Vendor may also be advancing environmental permitting as another way to de-risk the project, the project design may still be in flux as the resource size changes. Major modifications to the plan may cause permitting to stop and re-start, leading to an extended project timeline and wasted money.

There is also risk in starting the permitting with a project definition that isn’t of economic interest to future buyers. Sometimes the Vendor may be making regulatory commitments that constrain the operating flexibility of future mine operators. Its easy to commit to things when you aren’t the one having to live up to them.

The Mine Vendor will also de-risk the project by moving from PEA to PFS and even to FS. The caution with completing a FS is that it is a costly study and essentially brings one to the end of the study line. What does the company do next if there is still no buyer?

Feasibility studies also have a shelf life, with the cost estimates and economics becoming inaccurate after a few years. Some companies may re-examine the project, re-frame it, and jump back to the PEA or PFS stages. There can be an on-going study loop, requiring continued funding with no guarantee of a sale in sight. Often feasibility studies have the dual role of trying to boost the share price and market cap, as well as frame the project for potential buyers.

Conclusion

As an engineer, it is helpful to understand the objectives of the project owner and then tailor the technical studies to meet those objectives. This does not mean low balling costs to make the study a promotional tool. It means focusing on what is important. It means recognizing the path, and what doesn’t need to be engineered in detail at this time. This may save the client time, money, and improve credibility in the long run.

In many cases, the precise size of the deposit is less important than understanding the site, access, water supply, local community issues, the environmentally acceptable location for dumps and tailings, etc.. It can be more important to focus on these issues rather than having a detailed mine plan with multiple pit phases that immediately becomes obsolete in a few months after the next drilling campaign.

Potential buyers will have their own technical team that will develop their own opinions on what the project should be and what it should cost. Just because a Mine Vendor has a feasibility study in hand, doesn’t mean a potential buyer will believe it.

This post is just a brief discussion of mining project timelines. For those interested, there a few additional project timelines for curiosity purposes. Each path is unique because no two mining projects are the same. You can find these examples at this link “Mining Project Timelines”.

Let me know about other interesting projects that have interesting paths to learn from. I can add them to the list.

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.

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Mining Under Lakes – Part 2: Design Issues

Date: June 11, 2023 Author: Ken Kuchling Comments: 3 Replies

This is Part 2 of a blog post related to open pit mining within bodies of water. Part 1 can be found at this link “Mining Under Lakes – Part 1“, which provides a few examples where this has been done successfully. Part 2 focuses on some of the social and technical issues the need to be considered when faced with the challenge of open pit mining within a water body.

The primary question to be answered is whether one can mine safely and economically without creating significant impacts on the environment.

The answer to this question will depend on the project location and the design of the water retaining structure.

I have worked on several projects where dike structures were built. I have also undertaken due diligence reviews of projects where dikes would be required. Most recently I have participated in some scoping level studies where mining within a lake or very close to a river were part of the plan.

In some instances, the entire orebody is located in the lakebed. In others, the orebody is mainly on land but extends out into the water. Each situation will be unique. In northern Canada, given the number of lakes present, it would be surprising if a new mining project isn’t close to a river or lake somewhere.

Dike concepts consider many factors

Different mining projects may use different styles of dikes, depending on their site conditions. Some dikes may incorporate sheet piling walls, slurry cutoff walls, low permeability fill cores, or soil grouting. There are multiple options available, and one must choose the one best suited for the site.

The following is list of some of the key factors and issues that should be examined.

ESG Issues

One’s primary focus should be on whether building a dike would be socially and environmentally acceptable. If it is not, then there is no point in undertaking detailed geotechnical site investigations and engineering design. One must have the “social license” to proceed down this path.

Water Body Importance: Is there a public use of the water body? It could be a fresh water source for consumption, used for agricultural or fishery purposes, or used as a navigable waterway, etc. Would the presence of the dike impact on any of these uses? Does the water body have any historical or traditional significance that would prevent mining within it?

Lake Turbidity: Dike construction will need to be done through the water column. Works such as dredging or dumping rock fill will create sediment plumes that can extend far beyond the dike. Is the area particularly sensitive to such turbidity disturbances, is there water current flow to carry away sediments?

At Diavik, a floating sediment curtain surrounding the dike construction area was largely able to contain the sediment plume in the lake.

Regional Flow Regime: Will the dike be affecting the regional surface water flow patterns? If the dike is blocking a lake outflow point, can the natural flow regime be maintained during both wet and dry periods?

Location Issues

If there are no ESG issues preventing the use of a dike, the next item to address is the ideal location for it.

Water depth: normally as the dike moves further away from land, both the water depth and dike length will increase. The water depth at the deepest points along the dike are a concern due to the hydraulic head differential created once the interior water pool is pumped out. The seepage barrier must be able to withstand that pressure differential, without leaking or eroding. A low height dike in shallow water may be able to use a simpler seepage cutoff system than a dike in deep water.

Islands: Are there any islands located along the dike path that can be used to shorten the construction length and reduce the fill volumes? Is there a dike alignment path that can follow shallower water zones?

Pit wall setback: Given the size and depth of the open pit, how far must the dike be from the pit crest? Its nice to have 200 metre setback distance, but that may push the dike out into deeper water.

If the dike is too close to the pit, then pit slope failures or stress relaxation may result in fracture opening and increase the risk of seepage flows or catastrophic flooding. The pit wall rock mass quality will be the key determining factor in the setback distance.

Maximizing ore recovery: If the ore zone extends further out into the lake, maximizing ore recovery may require using a steep pit wall along the outer sections of the pit. This may require positioning haulroads with switchbacks along other sides of the pit rather than using a conventional spiral ramp layout.

At Diavik (see image), the A154 north open pit wall was pushed to about 60 metres of the dike to access as much of the A154N kimberlite ore as possible. Haulroads were kept to the south side of the pit.

It may be possible to recover even more ore by pushing out the dike even further. However, this may result in a larger and costlier dike or even require a different style of dike. There will be a tradeoff between how much additional ore is recovered versus the additional cost to achieve that. There will be a happy medium between what makes both technical sense and economic sense.

Design Issues

Once the approximate location of the dike has been identified, the next step is to examine the design of the dike itself. Most of the issues to be considered relate to the geotechnical site conditions.

Lakebed foundation sediments: What does the lakebed consist of with respect to soft sediments? Soft sediments can cause dike settlement and cracking, or mud-waving of fill material.

Will the soft sediments need to be dredged prior to construction, and if so, where do you dispose of this dredge slurry, and what impact will dredging have on the lake turbidity?

Lakebed foundation gravels: Are there any foundation gravel layers that can act as seepage conduits beneath the dike? If so, will these need to be sub-excavated, or grouted, or cut off with some type of barrier wall? Sonic drilling, rather than core drilling, is a better way to identify the presence of open gravel beds.

Upper bedrock fracturing: Is the upper bedrock highly fractured, thereby creating leakage paths? If so, then rock grouting may be required all along the dike path to seal off these fractures.

Major faults: Are there any major faults or regional structures that could connect the open pit with the lake, acting as a source of large water inflow?. At Diavik, we attempted to characterize such structures with geotechnical drilling before construction. Upon review, I understand there was one such structure not identified, which did result in higher pit inflows until it was eventually grouted off.

Water level fluctuations: In a lake or river one may see seasonal water level fluctuations as well as storm event fluctuations. The height of the dike above the maximum water level (i.e. freeboard) must be considered when sizing the dike.

Ice scouring: In a lake or river that freezes over, ice loads can be an important consideration. During spring breakup as the ice melts, large sheets of ice can be pushed around and may scour or damage the crest of the dike. The dike must be robust enough to withstand these forces.

Construction materials available on site: Is there an abundance of competent rock for dike fill? Is there any low permeability glacial till or clay that can be used in dike construction? If these materials are available on site, the dike design may be able to incorporate them. If such materials are not available, then a alternate dike design may be more appropriate, albeit at a cost.

Conclusion

Each mine site is different, and that is what makes mining into water bodies a unique challenge. However many mine operators have done this successfully using various approaches to tackle the challenge.

Even at the exploration stage, while you are still core drilling the orebody through the ice, you can start to collect some of this information to help figure it all out.

The bottom line is that while mining into a water body is not a preferred situation, it doesn’t mean the project is dead in the water. It will add capital cost and environmental permitting complexity, but there are proven ways to address it.

On the opposite side, I have also seen situations where a dike solution was not feasible, so ultimately there are no guarantees that engineers can successfully address every situation. Lets hope your project isn’t one of them.

There could be a 3rd part to this post that discusses issues associated with underground mining beneath bodies of water; however that is not my area of expertise. I would be more than happy to collaborate on a article with someone willing to share their knowledge and experience on that subject.

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NPV One – Cashflow Modelling Without Excel

Date: May 21, 2023 Author: Ken Kuchling Comments: Leave a reply

From time to time, I encounter interesting software applications related to the mining industry. I recently became aware of NPV One, an Australian based, cloud hosted application used to calculate mineral project economics. Their website is https://npvone.com/npvone/

NPV One is targeting to replace the typical Excel based cashflow model with an online cloud model. It reminds me of personal income tax software, where one simply inputs the income and expense information, and then the software takes over doing all the calculations and outputting the result.

NPV One may be well suited for those not comfortable with Excel modelling, or not comfortable building Excel logic for depreciation, income tax, or financing calculations. These calculations are already built in the NPV One application.

I had a quick review of NPV One, being given free access to test it out. I spent a bit of time looking at the input menus and outputs, but by no means am I proficient in the software after this short review.

Like everything, I saw some very good aspects and some possible limitations. However, my observations may be a bit skewed since I do a lot of Excel modelling and have a strong comfort level with it. Nevertheless, Excel cashflow modelling has its own pro’s and con’s, some of which have been irritants for years.

NPV One – Pros and Cons

Pros

NPV One develops financial models that are in a standardized format. Models will be very similar to one another regardless of who creates it. We are familiar with Excel “artists” that have their own modelling style that can make sharing working models difficult. NPV One might be a good standard solution for large collaborative teams looking at multiple projects while working in multiple offices.
NPV One, I have been assured, is error free. A drawback with Excel modelling is the possibility of formula errors in a model, either during the initial model build or by a collaborator overwriting a cell on purpose (or inadvertently).
With NPV One, a user doesn’t need to be an Excel or tax modelling expert to run an economic analysis since it handles all the calculations internally.
NPV One allows the uploading of large input data sets; for example life-of-mine production schedules with multiple ore grades per year. This means technical teams can still generate their output (production schedules, annual cost summaries, etc.) in Excel. They can then simply import the relevant rows of data into NPV One using user-created templates in CSV format.
As NPV One evolves over time with more client input, functionality and usability may improve as new features are added or modified.

Cons

Like anything, nothing is perfect and NPV may have a few issues for me.

Since I live and breathe with Excel, working with an input-based model can be uncomfortable and take time to get accustomed to. Unlike Excel, in NPV One, one cannot see the entire model at once and scroll down a specific year to see production, processing, revenue, costs, and cashflow. With NPV jump to. If you’re not an avid Excel user, this issue may not be a big deal.
In Excel one can see the individual formulas as to how a value is being calculated. Excel allows one to follow a mathematical trail if one is uncertain which parameters are being used. With NPV One the calculations are built in. I have been assured there are no errors in NPV One, so accuracy is not the issue for me. It’s more the lack of ability to dissect a calculation to learn how it is done.
With NPV One, a team of people may be involved in using it. That’s the benefit of collaborative cloud software. However that means there will be a learning curve or training sessions that would be required before giving anyone access to the NPV One model. Although much of NPV One is intuitive, one still needs to be shown how to input and adjust certain parameters.
Currently NPV One does not have the functionality to run Monte Carlo simulations, like Excel does with @Risk. I understand NPV One can introduce this functionality if there is user demand for it. There will likely be ongoing conflict to try to keep the software simple to use versus accommodating the requests of customers to tailor the software to their specific needs.

Conclusion

The NPV One software is an option for those wishing to standardize or simplify their financial modelling.

Whether using Excel or NPV One, I would recommend that a single person is still responsible for the initial development and maintenance of a financial model. The evaluation of alternate scenarios must be managed to avoid it becoming a modelling team free for all.

Regarding the cost for NPV One, I understand they are moving away from a fixed purchase price arrangement to a subscription based model. I don’t have the details for their new pricing strategy as of May 2023. Contact Christian Kunze (ck@npvone.com) who can explain more, give you a demo, and maybe even provide a trial access period to test drive the software.

To clarify I received no compensation for writing this blog post, it is solely my personal opinion.

Regarding Excel model complexity mentioned earlier, I have written a previous blog about the desire to keep cashflow models simple and not works of art. You can read that blog at “Mine Financial Modelling – Please Think of Others”.

As with any new mining software, I had also posted some concerns with QP responsibilities as pertaining to new software and 43-101. You can read that post at the appropriately titled “New Mining Software and 43-101 Legal Issues”.

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/

Steeper Pit Slopes Can Save Money

Date: April 14, 2023 Author: Ken Kuchling Comments: Leave a reply

We likely have all heard the statement that increasing pit wall angles will result in significant cost savings to the mining operation.

What is the potential cost saving?

The steeper wall angles reduce waste stripping volumes, which also provide other less obvious benefits.

I was recently in a situation where we undertook some comparative open pit designs using both 45 and 50 degree inter-ramp angles (“IRA”). I would like to share some of those results and discuss where all the benefits may lay.

Comparative Pit Designs

In this project, four separate open pits were designed with 45 and 50 degree IRA’s in an area with hilly topography. Some of the pits had high walls that extended up the valley hillsides. Its not hard to envision that waste stripping reductions would be seen along those areas with steepened walls.

The results of applying the increased inter-ramp angle to each of the four pits is shown in the Bar Chart. Note that the waste reduction is not necessarily the same for each pit. It depends on the specific topography around each pit.

However, on average, there was an overall 15% reduction in waste tonnage.

The Table shown below presents the cumulative tonnage for all four pits. The 50 degree wall results in a waste decrease of 25.4 million tonnes (15%), with a strip ratio reduction from 5.8:1 to 5.0:1.

There is also a very minor decrease in ore tonnage. This is because the 50 degree slopes did lose some ore behind the walls that is being recovered by the 45 degree slope.

In both scenarios the project life would be about 10 years at an assumed ore processing rate of 3 Mtpa.

4 Positive Impacts of Steeper Walls

In general one can typically see four positive outcomes from adopting steeper pit walls. They are as follows:

1. Cost Savings: The waste tonnage reduction over the 10 year life would be about 25.4 million tonnes. At a mining cost of $2.00/tonne, this equates to $50.8 million tonnes spent less on stripping. This could move the project NPV from marginal to profitable, since most waste is normally stripped towards the front part of the mining schedule with less discounting.

The next time you are looking at the NPV from an open pit project, take a quick look to see if the pit slope assumptions are conservative or optimistic. That decision can play a significant role in the final NPV.

2. Equipment Fleet Size: Over the 10 year life, the average annual mining rate would range from 20.5 Mtpa (45 deg) to 18.1 Mtpa (50 deg). On a daily basis, the average would range from 56,100 tpd (45 deg) versus 49,700 tpd (50 deg). While this mining rate reduction is not likely sufficient to eliminate a loader, it could result in the elimination of a truck or two. This would have some capital cost saving.

3. Waste Dump Size: The 15% reduction in the waste tonnage means external waste dumps could be 15% smaller. This may not have a huge impact but could be of interest if waste storage sites are limited on the property. It could have a more significant impact if local closure regulations require open pit backfilling.

4. Pit Crest Location: The steeper wall angles result in a shift in the final pit crest location. The Image shows the impact that the 5 degree steepening had on the crest location for one of the pits in this scenario.

Although in this project the crest location wasn’t critical, there are situations where rivers, lakes, roads, mine facilities, or public infrastructure are close to the pit. A steeper wall could improve ore recovery at depth while maintaining the same buffer setback distance.

Conclusion

Steeper pit walls can have multiple benefits at an open pit mining operation. However, these benefits can all be negated if the rock mass cannot tolerate those steeper walls. Pit wall failures could be minor or they could have major impacts. There are the obvious worker safety issues, as well as equipment damage and production curtailment concerns with slope failures. Public perception of the mining operation also comes into play with dangerously unstable slopes.

Steepening of the pit walls is great in theory, but always ensure that geotechnical engineers have confirmed it is reasonable.

It is relatively easy to justify spending additional time and money on proper geotechnical investigations and geotechnical monitoring given the potential slope steepening benefits.

When designing pits, there is some value in looking at alternate designs with varying slope angles to help the team understand if there are potential gains and how large they might be.

In closing, I previously wrote a related blog post about how pit walls are configured to ensure safe catch bench widths and decisions as to whether one should use single, double, or triple benching. That earlier post can be read at this link. Pit Wall Angles and Bench Widths – How Do They Relate?

Feel free to share your personal experiences if you are aware of other benefits (or even downsides) to steeper pit walls that I did not mention.

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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.

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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!“.

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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”.

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