Articles tagged with: Mine Engineering

Google Earth – Keep it On Hand

Date: May 8, 2015 Author: Ken Kuchling Comments: 1 Reply
Mining studies
In a previous blog post “Mine Site Visit – What Is the Purpose?” I briefly discussed the requirements for a mine site visit to be completed by one or more Qualified Persons (“QP”) in a 43-101 compliant study.    Unfortunately normally the entire study team cannot participate in a site visit; however the next best thing may be Google Earth.

See the Mine Site with Google Earth

Gather your team around their computers and fire up screen sharing software like Teams, GoToMeeting, Skype, or Zoom.  Give control of the mouse to someone who knows the site well.  Here are some of the things you can do on your group tour.
  • You can fly-around the project site examining the topography.
  • You can view regional features, regional facilities, land access routes, and existing infrastructure.
  • You can measure distances (or areas), either in a straight line or along a zigzag path.
  • You can view historical aerial photos (if they exist) to show how the area may have changed over time.
  • You can import GPS tracks and survey waypoints.  If a member of the study team has visited the site with a GPS, they can illustrate their route and their observations.
My recommendation, at the start of a study, is to always have a Google Earth session with your technical team to examine the project site and the regional infrastructure.
A group session like this ensures that everyone sees and hears the same thing. It’s like taking a helicopter tour of the site with your entire study team at once.   A “helicopter tour” would be a good agenda item at the very first kickoff meeting.
Another option is to check the aerial photos and Bird’s Eye views on the Bing Maps website (www.bing.com/maps).  Sometimes those images will be different than what you will find in Google Maps or Google Earth.
As mentioned above, for those still interested the  previous blog post is at “Mine Site Visit – What Is the Purpose?“
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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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Mining PEA’s – Is it Worth Agonizing Over Details

Date: May 5, 2015 Author: Ken Kuchling Comments: 3 Replies
Mining PEA
As stated in a previous article (“PEA’s – Not All PEA’s Are Created Equal“) different PEA’s will consist of different levels of detail.  This is driven by the amount of technical data available and used in the study.    The same issue applies to a single PEA whereby different chapters of the same study can be based on different degrees of data quality.
I have seen PEA’s where some of the chapters were fairly high level based on limited data, while other parts of the same study went into great depth and detail. This may not be necessary nor wise.

Think about the level of detail justifiable

If the resource is largely inferred ore, then the mine production plan will have an inherent degree of uncertainty in  it.  So there is not a lot of justification for other engineers (for example) to prepare detailed tailings designs  associated with that mine plan.
Similarly there is little value in developing a very detailed operating cost model or cashflow model for a study that has many underlying key uncertainties.  Such technical exercises may be a waste of time and money, adding to the study duration, increasing engineering costs, and giving the unintended impression that the study is more accurate than it really is.
Different levels of detail in the same study can crop up when diverse teams are each working independently on their own aspect of the study.   Some teams may feel they are working with highly accurate data (e.g. production tonnage) when in reality the data they were provided is somewhat speculative.
The bottom line is that it is important for the Study Manager and project Owner to ensure the entire technical team is on the same page and understands the type of information they are working with.   The technical detail in the final study should be consistent throughout.
Experienced reviewers will recognize the key data gaps in the study and hence view the entire study in that light regardless of how detailed the other sections of the report appear to be.
You can read more on the subject of uncertainty in PEA’s in another blog post at this link “Mining PEA’s – Not All PEA’s Are Created Equal“.
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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Multi-Company Mining Studies Can Work Well…or Not

Date: May 4, 2015 Author: Ken Kuchling Comments: Leave a reply
Mining studies
These days most, if not all, economics mining studies rely on a engineering teams comprised of participants from different consulting firms or from different regional offices of the same firm.   This approach gives the opportunity to use specific experts for different aspects of the study.
My recollection is that many years ago larger consulting firms would offer to do an entire study in-house. They would have the in-house team to cover almost the entire study. That approach seems to have changed and now the multi-company path is the norm.
This approach is partly being driven by the clients who wish to use specific consultants they are familiar with and have existing relationships with.
In some instances, larger firms may still make the argument they can take on all of the project scope themselves.  However one must reflect on such offers.  The danger being a less qualified technical team seconded from offices that are not busy.  Possibly you won’t get the best team; you  get who is available.
In many multi-company studies, it is not uncommon that few of the team members have ever worked together before.  It may be a consultant’s team building exercise right from the start.
I have had both good and bad experiences with these types of engineering teams.  Some of them work very well while others floundered.  Even when working with different offices of the same firm, things may not go as planned.

The Study Manager is Key

To have a successful mining study team, in my experience the two key factors are;
  1. The competency of the Study Manager;
  2. The amount (and style) of team communication.
The Study Manager is vital to keeping everyone working on the same page and ensuring timelines are met.   A single team member delaying their deliverables will delay others on the team.
Some consulting firms have multiple projects underway at the same time.  Unexpected delays in one study may cause them to shift idle personnel onto other studies.  Unfortunately sometimes it is difficult to bring the team back together on the original study at a moment’s notice.
The Study Manager must ensure that everyone understands what their deliverables are.   Generally this is done using a “Responsibility Matrix”, but these can sometimes be too general.
Where cost estimation is involved, the Responsibility Matrix should be supported by a Work Breakdown Structure (“WBS”) assigning the costing responsibilities.  Given that the contentious parts of many studies are the capital and operating cost estimates, I personally view the WBS equally as important as the Responsibility Matrix.
Team communication is vital and there are different ways to do it.   Weekly or bi-weekly conference calls work well but these need to be carefully managed.  With a large team on a conference call, there is a fine line between getting too much technical detail versus not enough detail.
On some studies I have seen a weekly call restricted to one-hour long and then everyone flees until next week’s call.  At the end of these conference calls, one might have an uneasy feeling of it being incomplete. Perhaps people were not clear on something but hesitated to ask become the one-hour time limit is up.   In such cases it is important for the relevant parties to continue on or to have a separate call.

Make it important to  speak up

The bottom line is that multi-company teams will work fine as long as the study manager is capable.  Its not a simple task, and not everyone can do it well.  However everyone (client and the other team members) appreciate working under a really good study manager.
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“.
In another blog post I have gone into a bit more depth on the role a Work Breakdown Structure plays.   You can read that post at this link “Work Breakdown Structures – Don’t Forget About The WBS“.
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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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Mining PEA’s – Not All PEA’s Are Equal

Date: April 30, 2015 Author: Ken Kuchling Comments: Leave a reply
Mining Preliminary Assessments
A Preliminary Economic Assessment (“PEA”) is defined in NI 43-101 as “…a study, other than a pre-feasibility or feasibility study, that includes an economic analysis of the potential viability of mineral resources”.  This is a fairly broad definition that provides for plenty of flexibility.  While there are generally accepted industry norms for a pre-feasibility or feasibility study, the mining PEA can have a broad scope.
Some PEA’s might be based on a large database of test work and site information while others may rely on very preliminary data and require design projections based on that data.
Some PEA’s may have production schedules consisting largely on Inferred resources while other schedules may be based on higher proportion of Indicated resource.
Some PEA’s are able to incorporate information from advanced socio-environmental work while other PEA’s may not have access to advanced information.
Therefore one should not view all PEA’s are being created equal. Perhaps that is what investors are doing it seems, in many cases ignoring the results of newly issued PEA’s.
The PEA is normally developed at a fairly early stage in the project life.  The initial PEA may then be superseded with a series of updated PEA’s as more data is acquired.  Typically one would expect to see changes in project size or scope in these updates and hopefully improved economics.  Shareholders appreciate being updated on positive growth trends.

Sequential PEA’s

The sequential PEA approach is a convenient way to continue advancement of the project without making the step to a Pre-Feasibility study or bigger step to a Feasibility study.  Maybe the project is still growing in size and a feasibility study at this stage would not be presenting the true potential, hence the updated PEA.
On the downside of the sequential PEA approach is that investors may get tired of hearing about PEA after PEA.  They may want to see a bigger advance towards a production decision.  They ask “How long can they keep studying this project?”.

 

There is no right or wrong as to what constitutes a PEA.

The securities commissions consider that the cautionary language an important component of the PEA Technical Report and may red-flag it if it’s not in all the right places.   However this cautionary language is generally focused on the resource.
For example the typical “The reader is cautioned that Inferred Resources are considered too speculative geologically to have the economic considerations applied to them that would enable them to be categorized as Mineral Reserves, and there is no certainty that value from such Resources will be realized either in whole or in part.”
In that cautionary statement there is no mention of all the other speculative assumptions that may have been used in the study.
For example, the Inferred resource may not be that significant however the amount of metallurgical test work might be a more significant uncertainty.  The previous cautionary language doesn’t address this issue.  Therefore it is important to consider the chapters in the Report pertaining to risks and recommendations for a more complete picture of the entire report.

Conclusion

The bottom line is that when reviewing a PEA report, be aware of all the uncertainties and assumptions that have been incorporated into the study.   The report may be well founded or built on a shaky foundation.  No two PEA’s are the same and this must be clearly understood by the reviewer.
Currently it seems that share prices do not move much with the issuance of a PEA.  It seems there is a lack of confidence in them.  On the other hand, I have also heard that it is better for future financings if a project has at least reached the PEA stage.
Develop your own personal PEA “checklist” to identify the amount and quality of data used for the different parts of the study to help understand where data gaps may exist.
In another blog post I discuss how it is important for the Study Manager and project Owner to ensure the entire technical team is on the same page and understands the type of information they are working with.   The technical detail in the final study should be consistent throughout.   You can read that blog at “PEA’s – Is it Worth Agonizing Over Details“.
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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4 Mining Study Types (Concept to Feasibility)

Date: April 29, 2015 Author: Ken Kuchling Comments: 2 Replies
Over my career I have been involved in various types of mine studies, ranging from desktop conceptual to definitive feasibility.    Each type of study has a different purpose and therefore requires a different level of input and effort, and can have hugely different costs.
I have sat in on a few junior mining management discussions regarding whether they should be doing a PEA or a Pre-Feasibility Study, or a Feasibility instead of a Pre-Feasibility Study.    Everyone had their opinion on how to proceed based on their own reasoning.   Ultimately there is no absolute correct answer but there likely is one path that is better than the others.  It depends on the short term and long term objectives of the company, the quality and quantity of data on hand, and the funding available.

4 types of mining studies

In general there are 4 basic levels of study, which are listed below.  In this blog I am simply providing an overview of them.  On the web there are detailed comparison tables, but anyone can contact me at KJKLTD@rogers.com for an a full copy of my table (an excerpt is shown below).

Four Studies Table

1. Desktop or Conceptual Mining Study
This would likely be an in-house study, non-43-101 compliant, and simply used to test the potential economics of the project.  It lets management know where the project may go (see a previous blog at the link “Early Stage “What-if” Economic Analysis – How Useful Is It?”.    I always recommend doing a desktop study, and preparing some type of small internal document to summarize it.  It doesn’t take much time and is not made public so the inputs can be high level or simply guesses.  This type of early stage study helps to frame the project for management and lets one test different scenarios.
2. Preliminary Economic Assessment (“PEA”)
The PEA (or scoping study) can be 43-101 compliant and present the first snapshot of the project scope, size, and potential economics to investors.  Generally the resource may still be uncertain (inferred classification), capital and operating costs are approximate (+/- 40%) since not all the operational or environmental issues are known at this time.   Avoid promoting the PEA as an “almost” feasibility level study.

Don’t Announce a PEA Until You Know the Outcome

I recommend not announcing the start of a PEA until you are confident in what the outcome of that PEA will be.   A reasonable desktop study done beforehand will let a company know if the economics for the PEA will be favorable.  I have seen situations where companies have announced the start of a PEA and then during the course of the study, things not working out economically as well as envisioned.  The economics were poorer than hoped and so a lot of re-scoping of the project was required.  The PEA was delayed, and shareholders & analysts negative suspicions were raised in the meantime.
The PEA can be used to evaluate different development scenarios for the project (i.e. open pit, underground, small capacity, large capacity, heap leach, CIL, etc.).  However the accuracy of the PEA is limited and therefore I suggest that the PEA scenario analysis only be used to discard obvious sub-optimal cases.  Scenarios that are economically within a +/-30% range of each other many be too similar to discard at this PEA stage.  This is where the PFS comes into play.
3. Pre-Feasibility Study (“PFS”)
The PFS will be developed using only measured and indicated resources (no inferred resource used) so the available ore tonnage may decrease from a previous PEA study.  The PFS costing accuracy will be greater than a PEA.  Therefore the PFS is the proper time to evaluate the remaining mine development scenarios.  Make a decision on the single path forward going into the Feasibility study.

Use the PFS to determine the FS case

More data will be required for the FS, possibly a comprehensive infill drilling program to upgrade more of the the resource classification from inferred to indicated.  Many companies, especially those with smaller projects might skip the PFS stage  entirely and move directly to Feasibility.  I don’t disagree with this approach if the project is fairly simple and had a well defined scope at the PEA stage.
4. Feasibility Study (“FS”)
The Feasibility Study is the final stage study prior to making a production decision.  The feasibility study should preferably be done on a single project scope.  Try to avoid more scenario option analysis at this stage.
Smaller companies should be careful when entering the FS stage.  Once the FS is complete, shareholders will be expecting a production decision.  If the company only intends to sell the project with no construction intention, they have now hit a wall.  What to do next?

Sometimes management feel that a FS may help sell the  project.

I don’t feel that a FS is needed to attract buyers and sell a project.  Many potential buyers will do their own in-house due diligence, and possibly some alternate design and economic studies.   Likely information from a PFS would be sufficient to give them what they need.  A well advanced Environmental-Socio Impact Assessment may provide more comfort than a completed Feasibility Study would.

Conclusion

executive meetingMy final recommendation is that there is no right answer as to what study is required at any point in time.  Different paths can be followed but consideration must be given to future plans for the company after the study is completed.   Also consider what is the best use of shareholder money?
Company management may see pressure from retail shareholders, major shareholders, financial analysts, and the board of directors to “do a study”.  Management must decide which mining study path is in the best longer term interests of the company.  Maybe no study is warranted.
Note: If you would like to get notified when new blogs are posted, then sign up on the KJK mailing list on the website. Follow us on Twitter at @KJKLtd for updates and insights.
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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!“

 

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