Mine Economics

Large or Small Mining Consulting Firms – Any Difference?

Date: May 7, 2015 Author: Ken Kuchling Comments: 2 Replies
Mining feasibility pre-feasibility
Some junior mining companies select their mining study consultant based on the assumption that they need a “big name” firm to give credibility to their study.   This creates an interesting dilemma for many smaller mining companies since they the larger firms can cost more.  Its also a dilemma for smaller engineering firms trying to win jobs.  While large consultants may cost more due to higher overheads; their brand name on a study may bring some value.
In my personal experience I find that larger consultants are best suited for managing the large scale feasibility studies.  This isn’t because they necessarily provide better technical expertise.  Its because they generally have the internal project management and costing systems to manage the complexities of such larger studies.
The larger firms are normally able to draw in more management resources; for example, project schedulers, cost estimators, and document control personnel.  Ultimately one will pay for all of these people, albeit they may be a critical part in successfully completing the study.
A feasibility study is more rigorous than a pre-feasibility study, which in turn is more rigorous than a PEA or scoping study.

Sub-contracting Parts

For certain aspects of a feasibility study, one may get better technical expertise by subcontracting to smaller highly specialized engineering firms.  However too much subcontracting may become an onerous task.  Often the larger firms may be better positioned to do this.
In my view, likely the best result will come from a combination of a large firm managing the feasibility study but undertaking only the technical aspects for which they are deemed to be experts.
The large lead firm would be supported by smaller firms for the specialized aspects, as per a previous article “Multi-Company Engineering Studies Can Work Well..Or Not”.

What about smaller studies?

For smaller studies, like scoping studies (i.e. PEA’s), which can be based on limited amounts of technical data, I  don’t see the need to award these studies to large engineering firms.  The credibility of such early studies will be linked to the amount of data used to support the study.  For example, there may be limited metallurgical testing, or limited geotechnical investigations; or the resource is largely inferred.
Not all PEA’s are equal (see “PEA’s – Not All PEA’s Are Created Equal”).  A large firm’s application of limited data may be no more accurate or defensible than a small firm’s use of the same data.
One of the purposes of an early stage study is to see if the project has economic merit and would therefore warrant further expenditures in the future.  An early stage study is (hopefully) not used to defend a production decision.  The objective of an early stage study is not necessarily to terminate a project (unless it is obviously highly uneconomic).
I have seen instances where larger firms, protecting themselves from  limited data, were only willing to use very conservative design assumptions in early stage mining studies. This may not be helpful to a small mining company trying to decide how to advance such a project.

Conclusion

The bottom line is that for early stage studies like a PEA, smaller engineering firms can do as good a job as larger firms.  However one must select the right firm.  Review some of their more recent 43-101 reports to gauge their quality of work.  Don’t hesitate to check with previous client references.
For the more advanced feasibility level studies, be wary if a smaller firm indicates they can do the entire study. Perhaps they can be responsible for some parts of the feasibility study as a sub-contractor to a larger firm. Managing these large study may be beyond their experience and internal capabilities.
Whether you are considering a small or large engineering firm, know their strengths and weaknesses as they will relate to the specific’s of your study.
In another blog post I have expanded the discussion about the importance of the study manager role. You can read that post at this link “Importance of a Study Manager – That’s the Key“.
Another blog post discusses undertaking studies using multiple engineering teams and the pitfalls to watch out for.  That blog post is at “Multi-Company Mining Studies Can Work Well…or Not“.
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Metal Equivalent Grade versus NSR for Poly-Metallics

Date: May 1, 2015 Author: Ken Kuchling Comments: 4 Replies
NSR for poly-metallics
Many of the mining studies that I have worked on were deposits containing multiple recoverable metals.  For example this might be Ag-Pb-Zn mineralization or Cu-Pb-Zn-Au-Ag mineralization.    Discussions were held regarding whether to use a “metal-equivalent grade” to quantify the deposit grade or to use a Net Smelter Return (“NSR”) dollar value.
This also becomes an issue since one must decide how to apply a cut-off grade for mine planning and reporting.  It can be applied to the major metal grade only, to the equivalent grade, or to an NSR dollar value.

The NSR represents a $/tonne recovered

I have found that the geologists tend to prefer using a metal-equivalent grade approach.  This is likely due to the simpler logic and calculation required for an equivalent grade formula.  At an early stage it’s also simpler to select a reporting cutoff grade based on similar projects.
Generally I have no major concerns with the metal-equivalent approach at the resource estimate stage.   However from an engineer’s view, an equivalent grade does not provide a meaningful representation of the ore quality.
It is more difficult to relate an equivalent grade to an operating scenario that may rely on different mining or processing methods generating different final products (e.g. dore versus concentrates).  The NSR approach makes it easier to understand the actual quality of the ore.
On the downside, the NSR calculation will require more input data.  Assumptions needed relate to metallurgical recoveries, concentrate characteristics and costs, and smelter payables.  However the end result is an NSR block value that can be related directly to the site operating costs.
For example if a certain ore type has an on-site processing cost of $20/tonne and G&A cost of $5/tonne, then in order to breakeven the ore block NSR value must exceed $25/tonne.   If one decides to include mining costs and sustaining capital costs, then the NSR cutoff value would be higher.   In all cases one can directly relate the ore block value to the operating cost and use that to determine if it is ore or waste.  This is more difficult to do using equivalent grades.
Where the equivalent grade can become a problem is when one cosiders the impact of metal prices.  For example, the rock grades can be aggregated to, say, an Ag- equivalent.  However this does not mean that if the silver price goes up by 20% that the rock value also goes up by 20%.  The other metal prices may not have changed, and hence only the equivalent formula would change.   The rock value would go up, but not by 20%.

Using the NSR approach, the operating margin per block is evident.

One drawback to the NSR block value approach is that the calculation will be based on specific metal prices.  If one changes the metal prices, then one must recalculate all of the NSR block values and re-populate the model.
In some studies, I have seen higher metal prices used for resource reporting and then lower metal prices for mine planning or reserves.  In such cases, one can generate two different NSR values for each block.  One can use the same NSR cutoff value for reporting tonnages.   This two NSR approach is reasonable in my view since Resources and Reserves are different entities.

Pit Optimization

Pit optimization can also be undertaken using the block NSR values rather than ore grade values, so the application of NSR’s should not create any additional problems in this area.
For projects that involve metal concentrates, the cashflow model usually incorporates detailed net smelter return calculations, which include penalties, deductions, different transport costs, etc.  The formula used for the calculation of NSR block values can be simpler than the cashflow NSR calculation.   For example, one could try to build in penalties for arsenic content thereby lowering the NSR block value; however in actuality such ore blocks may be blended and the overall arsenic content in the concentrate may be low enough not to trigger the penalty.
Since the NSR block value is mainly used for the ore/waste cutoff, I don’t feel it is necessary to get overly detailed in its calculation.  The cashflow model should always calculate revenues from individual metals rather than using the block NSR value.
The bottom line is that from an engineering standpoint and to improve project clarity, I always prefer to use NSR values rather than equivalent grades.   Geologists may feel differently.
The cutoff grade is an important parameter in mine planning.  In another blog post I discuss whether in times of high metal prices, should the cutoff grade be lowered, raised, or kept the same.  You can read that at “Higher Metal Prices – Should We Lower the Cut-Off Grade?“
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Early Stage “What-if” Mine Economic Analysis – Its Valuable

Date: April 27, 2015 Author: Ken Kuchling Comments: Leave a reply
Mining study economics
Over my career I have worked with large and small mining companies and seen how they studied projects and potential acquisitions.
Large mining companies have their in-house evaluation teams that will jump on a potential opportunity that comes around and start examining it quickly.  These evaluation teams may consist of a specialized head office group supported by people temporarily pulled in from their mining operations.
They are experienced at what they do and can provide management with solid advice even if working with only limited data.  This help management decide very early on whether to further pursue the opportunity or walk away immediately.
Early stage economics are normally part of this evaluation approach.   Although they are not correct all of the time, more than often they save their company from wasting money on projects unlikely to fly.
However if you are a small mining company, what are your options?
You don’t have an in-house technical team sitting around ready to go.  Management still needs to know if this project has a chance.  If the project is early stage, sometimes management thinks its fine to take a gamble, acquire the project, and then put money into the ground rather than spending on early studies.

It is possible to do both

Management and the exploration team usually have a vision for their projects, even those projects with only limited information.   Each person may have a different opinion on the potential size and scope of what may ultimately exist there.  However the question is whether any of those visions have sufficient accuracy to warrant spending more shareholder money on the project.
Some of the junior mining management teams that I have worked with have found it beneficial early on to have a basic internal cashflow model on hand.   If properly constructed, these are simple to tweak to examine “what-if’s” scenarios.  Input the potential deposit size and mine life, potential head grades, expected metallurgy, and typical costs to see what the economic outcome is.  Does this project have a chance and, if not, what tonnage, head grade, recovery, or metal price is required to make it work?   The simple cashflow model can tell you all of this.

Early stage modelling adds value

The tangible benefits to very early financial modelling are:
  • It helps management to conceptualize and understand their project.  If done honestly, it will reveal both the opportunities and threats to success.
  • It helps management to understand what technical parameters will be most important for them to resolve and what technical factors can be viewed as secondary. This helps guide the on-going exploration and data collection efforts.
  • Periodically refreshing the economic model with new information will reveal if the economic trends are getting better or worse.

Its not 43-101 compliant

I must caution that this type of early stage economic analysis is not 43-101 compliant and hence can not be shared externally, no matter how much one might wish to.
Another caution is that in some cases these early stage un-engineered projections become “cast in stone”, with management treating them as if they are accurate estimates.  Then suddenly all subsequent advanced studies must somehow agree with the original cost guesses, thereby placing unreasonable expectations on the project and the people doing the work.
The early stage economic models can consist of simple one-dimensional tables using life-of-mine tonnages or two-dimensional tables showing assumed annual production by year.  Building simple cashflow models may take only 2-3 days of effort.  That is not an onerous exercise compared to the overall benefit they can provide.
The bottom line is that it is useful to take a few days to develop a simple cashflow model.  “Simple” also means that management themselves can tweak the models and don’t need to be modeling expert on hand at all times.  “Simple” means the model should be well.  In another block post I discuss why to avoid demonstrating one’s Excel skills in building models. Read more on that at this link  Financial Spreadsheet Modelling – Think of Others.
Most companies have a CFO that can easily undertake this type  of modelling, with the help of some technical input.  Be careful though, often CFO’s take the simple cashflow model to an unwarranted level of complexity.
The simplest of all models is the one-dimensional approach.  To learn more about the concept behind a simple 1D financial models, read the blog post “Project Economics – Simple 1D Model” .
The entire blog post library can be found at this LINK with topics ranging from geotechnical, financial modelling, and junior mining investing.
Note: If you would like to get notified when new blogs are posted, then sign up on the KJK mailing list on the website.  Otherwise I post notices on LinkedIn, so follow me at: https://www.linkedin.com/in/kenkuchling/.
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Mine Financial Modelling – Please Think of Others

Author: Ken Kuchling Comments: Leave a reply
Mining Cashflow modeling
In my role as a mining consultant I am often required to review spreadsheet cost models or cashflow models built by others.  Some of these spreadsheets can be monsters, incorporating multiple worksheets, cross-linking between worksheet cells, and having hard wired numbers inside cell formulas.
Some of the models I have reviewed will build the entire operating cost (mining, processing, G&A) in one grand file.  They will build in the capital cost too and finally provide the economic model… all in one spreadsheet!
This makes the model very complex to audit and it becomes difficult to follow the logic.  Sometimes gut feel says there are formula or linkage errors in there somewhere but you just can’t find them.  In these types of models my focus is on trying to figure out the formula logic than actually looking at the validity of the inputs and output.
It seems that only the model developer can really work with these spreadsheets and the rest of us can just hope that they have created everything correctly.

Don’t be too clever

Over the years, I have learned that there is an art to creating a clear, concise, and auditable cashflow model (or cost model). Once in awhile you come across one that is well crafted and isn’t an example of someone trying to show how clever they are.
In building the spreadsheet models I have learned to not do too much within the same model, especially if different people are involved in its foundation.  My other suggestions are:
  • Color coded input cells differently than formula cells.
  • Carry over values rather than linking to other worksheets.
  • Highlight cells that are carried over from other worksheets.
  • Never hardwire numbers into a formula.
  • Use named cells for key fixed inputs (like exchange rate, fuel price, etc.)
  • Use conditional formatting when possible to help identify errors.
  • Put your “Totals” column along the left side of the worksheet so you can add columns if needed.
I won’t go into detail on good spreadsheet practices, but you can check out the instructional presentations prepared by Peter Card at Economic Evaluations (http://economicevaluation.com.au).
He has some excellent practical recommendations that all financial modellers should consider.  It doesn’t take long to review his online courses and it’s worth your time to do it.  His recommendations can generally apply to any Excel modelling exercise, whether its costing, scheduling, or economic analysis.

Try to help by building in clarity.

The bottom line is that you must build your spreadsheet models compatible with the way you think.  However not everyone thinks the same way so try to keep all aspects easily identifiable and traceable.  Be consistent in the model format from worksheet to worksheet. Be consistent in methodologies on all worksheets and with all your models.   Your client, colleagues, and reviewers will thank you.
Another aspect of due diligences that can be taxing is figuring out the structure of a data room.   Simply throwing all of your files into an unstructured data room helps no one.   I have written another blog about this annoyance at “Mining Due Diligence Data Rooms – Help!“

 

Note: If you would like to get notified when new blogs are posted, then sign up on the KJK mailing list on the website.  Otherwise I post notices on LinkedIn, so follow me at: https://www.linkedin.com/in/kenkuchling/.
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