Articles tagged with: Mine Engineering

Large Consulting Firms or Small Firms – Any Difference?

Date: May 7, 2015 Author: Ken Kuchling Comments: 2 Replies
Mining feasibility pre-feasibility
Some junior mining companies have selected their engineering consultant on the assumption that they need a “big name” firm to give credibility to their feasibility study.   This creates an interesting dilemma for many smaller mining companies.  Its also a dilemma for smaller engineering firms trying to win jobs.  While large consultants may be higher cost due to their overheads; their name on a study may bring some intangible 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 project management and costing systems to manage the inherent 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 does pay for all of these people, albeit they may be a critical part in successfully completing a study.  However there is a cost to this.

Sub-contracting

For certain aspects of a feasibility study, one may get better technical expertise from smaller specialized engineering firms.  However the overall coordination of heavily sub-contracted studies can be 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 uneconomic).
I have seen instances where larger firms protecting themselves from  limited data, were only willing to use very conservative design assumptions. This may not be helpful to a small mining company trying to decide how to advance an earlier stage 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.

 

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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.
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Multi-Company Engineering Studies Can Work Well…or Not

Date: May 4, 2015 Author: Ken Kuchling Comments: Leave a reply
Mining studies
Most, if not all, advanced studies these days rely on engineering teams comprised of participants from different consulting firms or from different regional offices of the same company.   This approach gives the opportunity to use  experts for different parts of a study.
My recollection is that years ago larger consulting firms would offer to do an entire study in-house.  That now seems to have changed and the multi-company approach seems to be the norm.
This is partly being driven by the clients who wish to work with  consultants they are familiar with and have existing relationships. It
In some instances, larger firms may still make the argument they can take on all of the project scope themselves.  However reflect on such offers, the danger being a less qualified team seconded from offices that are not busy.  Possibly you won’t get the best team; you  get who is available.
In many joint company studies, often few of the team members will have ever worked together before.  It may be a 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.  Some of those in-house teams may not have previously worked together.

The Study Manager is Key

To have a successful 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 making sure timelines are met. (I have another blog discussing the Study Manager role).  A single team member delaying their deliverables will delay others on the team.
Some consulting firms have multiple client projects underway at the same time.  Unexpected delays in one study may cause them to shift personnel onto other clients.  Unfortunately sometimes it is difficult to bring the team back together on your project 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.  (I have another blog on the subject of WBS ).
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 is up.   In such cases it is important for the relevant parties to continue on or have a separate call.

Make it apparent to everyone that they should speak up if something is not clear to them, regardless of the time remaining.

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.
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Metal Equivalent Grade versus NSR for Poly-Metallics. Preference?

Date: May 1, 2015 Author: Ken Kuchling Comments: 4 Replies
NSR for poly-metallics
Some of the mining studies that I have worked on were for deposits containing multiple recoverable metals.  For example Ag-Pb-Zn mineralization or Cu-Pb-Zn-Au-Ag mineralization.    Discussions were held regarding whether to use a “metal-equivalent grade” to simplify the deposit grade or to use a Net Smelter Return (“NSR”) dollar value.

The NSR represents a $/tonne recovered value rather than a head grade.

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 simpler to select the cutoff grade based on similar projects.
Generally I have no concerns on 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 the head grade to an operating scenario which may rely on different mining or processing methods generating different final products (e.g. dore versus concentrates).   The NSR makes it easier to understand the actual ore quality.
On the downside, the NSR calculation will require more input data.  Information such as metallurgical recoveries, concentrate characteristics and costs, and smelter payable parameters will be needed.  However the end result is an NSR block value that can be related directly to the 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 NSR block 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 with equivalent grades.

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

If using pit phases to start mining in high grade areas, one can immediately get a sense for the incremental benefit by looking at the profit margin per pit phase.
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 the NSR block values.
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.

Pit Optimization

Pit optimizations 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.
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 being used for the ore/waste cutoff, I don’t feel it is necessary to get too detailed in its calculation.
The bottom line is that from an engineering standpoint and to improve project clarity, I recommend the use of NSR values rather than equivalent grades.   Geologists may feel differently.
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PEA’s – Not All PEA’s Are Created 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.
For more about preparing a mining PEA, read the blog “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/.
For those interested in reading other mining blogs, check out the Feedspot website at this link: https://blog.feedspot.com/mining_blogs/
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Four Study Stages (Concept to Feasibility) – Which Should We Do?

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.

Four basic types of studies

In my opinion there are four basic levels of study, which are listed below.  My objective to simply provide an overview of them.  Detailed comparison tables are readily available, and anyone can contact me at KJKLTD@rogers.com for an a full copy of the table  shown below).

Four Studies Table

1. Desktop or Conceptual 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 recommend doing a documented desktop study.  It doesn’t take much time and is not made public so the inputs can be high level or simply guesses.  This type of study helps to frame the project for management and lets one test different scenarios.
2. Preliminary Economic Assessment (“PEA”)
The PEA is 43-101 compliant and presents 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.   Please do not sell the PEA as a feasibility study.

Don’t Announce a PEA Until You Know the Outcome

I recommend not announcing or undertaking a PEA until you are confident in what the outcome of the 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 timing for a PEA and then during the study, have seen things not working out 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 and financial 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 the PEA stage.
3. Pre-Feasibility Study (“PFS”)
The PFS will be developed using only measured and indicated resources (not inferred) so the available ore tonnage may decrease from the PEA study.  The PFS costing accuracy will be better than a PEA.  Therefore the PFS is the right time to evaluate the remaining 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 PFS, possibly a comprehensive infill drilling program to upgrade the resource classification from inferred.  Many companies, especially those with smaller projects might skip the PFS stage  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 analysis at this time.
Smaller companies should be careful entering the FS stage since, 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 now hit a wall.  What to do next?

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

I don’t think 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 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 give as much or more comfort than a completed Feasibility Study would.

Conclusion

executive meetingMy bottom line 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.  Management must decide which path is in the best longer term interests of the company.
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Early Stage “What-if” Economic Analysis – How Useful Is It?

Date: April 27, 2015 Author: Ken Kuchling Comments: Leave a reply
Mining study economics
Over the years I have worked with both large and small mining companies and watched how they studied potential acquisitions.
Large mining companies have their in-house evaluation teams that will jump on a potential opportunity that comes in the door and start examining it quickly.  These evaluation teams 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 pursue the opportunity or walk away.
Early stage economics are not right all of the time but more than often they save their company from wasting money on projects unlikely to fly.
If you are a small mining company, what are your options?
You don’t have an in-house technical team sitting around ready to hit the ground running.  Management needs to know if this project has a chance.  If the project is early stage, sometimes management thinks it is better to put money into the ground rather than on early studies.

It is possible to do both

I feel that you won’t know if you have arrived at your destination if you don’t know your destination.  Early stage financially modelling can help define that destination.
The exploration team and management usually have a vision of the potential project, even those projects with only an early resource estimate.   Each person may have a different opinion on the potential size and scope of what may eventually exist.  However the question is whether any of those vision have sufficient potential 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 simple internal cashflow model that is simply to tweak to examine “what-if’s” scenarios for the project.  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?

Early stage modelling adds value

The tangible benefits to early financial modelling are:
  • It helps management to think about and better understand their project.  If done honestly, it will reveal both the good and the bad aspects.
  • It helps management to understand what parameters will be most important to resolve and what technical factors can be viewed as secondary. This helps guide the on-going exploration and data collection efforts.
  • Periodically updating the economic model with new information will show the if 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 be 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”, treating them as if they are accurate estimates.  All subsequent advanced studies somehow need to agree with the original cost guesses, thereby placing unreasonable expectations on the project.
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 guidance 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 a modeling expert on hand at all times.  “Simple” means the model should be well written and understandable (see the article Financial Spreadsheet Modelling – Think of Others).
Most companies have a CFO that can easily undertake this modelling, with the help of some technical input.
To learn more about simple 1D financial models, read my blog “Project Economics – Simple 1D Model” .
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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#1 Financial Spreadsheet Modelling – Please Think of Others

Author: Ken Kuchling Comments: Leave a reply
Mining Cashflow modeling
In my current 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, using numerous 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 file.  They will build in the capital cost too and finally provide the economic model… all in one!
This makes the model very complex and difficult to follow the logic.  Sometimes your gut feel says there must be formula or linkage errors in there somewhere but you just can’t find them.  In these types of models more focus is spent 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 they have  done everything correctly.

Cleverness is not a virtue

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 is not an example of someone saying “look how clever I am”.
In building the spreadsheet models I have learned to not try to do too much in the same model, especially if several different technical people are involved in its foundation.   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 conditional formatting when possible to help identify errors.
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.
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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