
Mine through mill reconciliation, in my view, is an under appreciated topic that could benefit from more conversation amongst industry members. Unfortunately, reconciliation is sometimes viewed as a time consuming frustrating activity, with what some consider less than verifiable results. However given the ongoing innovation that we are seeing in mining, reconciliation may need to play a bigger role than ever.
The mining industry is implementing more and more technology in the mining cycle.
For example, this can range from AI assisted resource modelling, down hole logging, blast movement tracking, GPS controlled dig limits, MineSense bucket grade tracking, load scanning, truck dispatch control, smart mining and edge computing, online grade analyzers, belt weightometers, drone surveying of stockpiles, and real time process controls.
Lots of different innovations are continually being adopted by the mining industry, contrary to what some may say.
The question is does all this innovation improve the overall performance of a mining operation, and if so, by how much? It can cost a lot of money to implement the new technology, is there a payoff?
One cannot answer those questions if one doesn’t undertake proper mine reconciliation. A concern might be that mining is innovating faster than the ability to assess the results of that innovation. To monitor it, you need to measure it.
What is Mine Reconciliation
Mine reconciliation is the process of comparing and aligning the estimated production with the actual production from mining and processing. It requires assessing the accuracy of pre-mining predictions against actual results to identify inconsistencies in the system and hopefully improve it, be it resource estimation, mine planning, or process efficiency. Comparisons can be made between multiple stages in the mining system, as shown in the image below.
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Mine reconciliation requires information such as initial predictions from exploration data and geological models, actual measurement: data from mining sources, such as blast holes, stockpile samples, or mill feed. As well it will need data on the final product being shipped off site. Do the metal quantities balance out throughout the mining operation? -
Mine reconciliation tends to aggregate over longer time periods (monthly, quarterly or annually) due to short term impacts of material handling in stockpiles and plant circuits and the labour time needed to collect the input data.
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Mine reconciliation ultimately attempts to assess how well the delivery of the final metal product relates to the initial resource model (i.e. what the project decision was originally based on)? It is also tool to evaluate the impact of any innovation implementation on the operation.
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Reconciliation will help mine operators highlight issues and optimize extraction, manage costs, and ensure compliance with regulatory or investor expectations. Factors such as poor resource estimation, excessive dilution and ore loss, inaccurate sampling, etc. can cause discrepancies, making reconciliation an important part of any operation.
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The reconciliation process is also used to derive Mine Call Factors. These factors are used to modify the forecasts from long range models, short range models, and grade control models to better represent the actual performance the operation will likely see. Large call factors suggest something is amiss in the “forecast to actual” progression. The first problem is to identify the causes. The list of the common sources of error can be lengthy. Then, once identified, the second problem is how to fix them.
Harry Parker initially suggested various reconciliation parametrics and labelled them F1, F2, F3. In a 2009 paper by Fouet titled “Standardising the Reconciliation Factors Required in Governance Reporting”, indicates that Rio Tinto had decided upon fifteen (15) different possible reconciliation correlations (see image below). Each one provides an insight on the efficiency of the operation in one way or another. I have seen modified versions of the reconciliation relationships, so it appears there may be no industry standard at this time. Fouet was asking about industry standardization in 2009 (an excellent paper to read by the way).

Mining Codes Getting Involved
It appears that the JORC Code may be recognizing the importance of reconciliation. In an August 2024 Exposure Draft JORC is suggesting the following text: “Where an Ore Reserve has been publicly reported for an operating mine, the results of both production reconciliation and any prior estimate comparison must also be included in the annual Mineral Resources and Ore Reserves statement. Refer to Clause 2.36. The relationships and variables being reconciled must be described in plain language or depicted graphically and must include reconciliations of both the Mineral Resources and Ore Reserves.”
Interestingly, it appears that NI43-101 has not yet jumped on the bandwagon about the importance of disclosing reconciliation results. However, it may just be a matter of time before it becomes one of their disclosure requirements.
If more regulatory focus will be put on mine reconciliation disclosure, then perhaps more industry standardization is warranted. This would help better define some of the terminology and “F factors” shown in the diagrams above to ensure consistency and help avoid each mine doing reconciliation in their own way.
Excel versus Cloud Based Reconciliation
Each mine site may be unique with respect to; ore sources; terminology; ore types; mining methods; stockpiling philosophy; processing methods; technology availability; and personnel capability. So often the easiest approach for mine reconciliation is based on the Excel spreadsheet. (Reconciliation is generally not an easy undertaking).
Spreadsheets can be built site specific, based on an operation’s unique characteristics.
Spreadsheets are often built by a user for that user. They are tailored for the tailor. In my experience, typically the modeler is the only one comfortable with an Excel model’s logic, since all of us may think differently. Unfortunately, with the spreadsheet approach, it becomes more difficult to standardize an industry wide reconciliation process.
An alternate solution to spreadsheets is to use a cloud based standardized software package. Toronto based Minebright has one option, called Pit Info (see link for more info). There are a few other reconciliation software applications available. They tend to be cloud based, hence multiple people can have access to the input modules or output modules. (I would like to thank the Minebright people for steering me towards some of the technical papers on this subject).

The cloud based approach may help make reconciliation a group effort instead of a tightly controlled internal function. It may also help standardize reporting from a company’s multiple operations, reporting from the mining industry globally, or simply for consistent JORC reporting.
The downside to the cloud approach is the mine site teams must learn the software and tailor it to their operation. However, once that hurdle is passed, personnel changes become less onerous due to the model consistency. I have seen cases where a person doing the Excel reconciliation task has left their job, and hence forward the reconciliation effort came to a halt. The people remaining may be too busy or simply don’t want to have to figure out the Excel logic of someone else.
The other nice thing about a cloud software approach is that when improvements are rolled out, every user gets the same update. The “wisdom of crowds” will result in learnings and suggestions that will tend to improve the application functionality over time. There are a lot of smart people out there, and it would be nice to see them working together rather than individually, as the open source software community has demonstrated.
With AI, we also may get to the point where cloud based mine reconciliation platforms can use learnings from other projects, and help identify where the likely technical shortfalls are at a mine site and why production is not reconciling. Let’s ask AI do some of the thinking for us to get to the bottom of a problem.
Conclusion


There have been fairly recent heap leach pad failures in both the Yukon and Turkey and tailings dam failures in Chile and the Philippines. As a result I have been seeing more posts on LinkedIn about the application of satellite based InSAR deformation monitoring. I had never heard of InSAR before, so thought a little bit of background research on my part might be worthwhile. (Note: this article was written in 2024 and technological improvements are happening all the time).
An example of a satellite being used is the Sentinel-1, launched in mid-2015 by the European Space Agency. This satellite information is open-source data. It will have a 6 to 12 day revisit cycle in many locations.
On LinkedIn, one can see numerous posts where independent experts are examining historical InSAR data for recent failures to see whether any early movement should have been detected. The results seem to be quite positive in that zones that have failed might have been red-flagged in advance.
A mining site consists of numerous constructed embankments and slopes of all types and heights. Many of these slopes may be creeping and moving all the time – it’s a living beast.
Recently I have been seeing more mining studies proposing to use the dry stack approach. In some cases, they no longer even do the typical tailings trade-off study that look at different options. The decision is made upfront that dry stack is the preferred route due to its environmental acceptability and positive perceptions.
The Guide covers several topics, including tailings characterization; site closure concepts; filtered tailings stack design; material transport, stacking systems; and tailings dewatering methods. The Guide covers all the basics very well. The one area that jumped out at me is the tailings characterization and testing aspect.
Major miners, such as BHP and Rio Tinto, typically spare no expense on material testing for metallurgical or geotechnical purposes. They have the funds available to test and engineer to a high level to adequately de-risk the project to meet their investment thresholds.
This is Part 2 of the blog post discussing junior mining scams and the sanctioning of those responsible. Part 1 can be found at this link “
43-101 regulations state that “An issuer must not file a technical report that contains a disclaimer by any qualified person responsible for preparing or supervising the preparation of all or part of the report that
This ends Part 2 of this blog post. It hopefully highlights the importance of QP’s being knowledgably on the disclosure rules and the technical aspects of what they are hired to do.
In April 2024 Red Pine Exploration issued several press releases highlighting that some assays in their geological database were found to have been manipulated. Numerous assays input into their database did not match the original lab certificates. Is this another mining scam?
The focus of this blog is on the types of activities that raised the red flags in the past. I am less interested in naming the people responsible, although the associated web links do provide more detail on the events.
This ends Part 1 of this blog post. Part 2 will continue with a few more examples, specifically involving Qualified Persons, and can be found at this link 
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.
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.
ake 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.
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.
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 in this Chwithout requiring a lot of external input. You can read Part 1 at this link “
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.
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 value, smoothing the ore delivery to the plant.
Once the production 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.
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 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.
These two blog posts 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.
When people asl what I do and learn that I’m a mining engineer, I’ll normally get perplexed looks. Most people don’t even knew the job exists
There is always a mineral resource estimate available before doing a PEA. The way the resource is being reported will indicate what type of mine this likely is. The geologists have already done some of the mining engineer’s work.
Before starting pit optimization, we require economic inputs from several people. The base case metal prices must be selected (normally with input from the client). The mining operating cost per tonne must be estimated (by the mining engineer). The processing engineers will provide the processing cost and recovery for each ore type.
Once the optimization is run, a series of nested pit shells are created, each with its own tonnes and grade. These shells are compared for incremental strip ratio, incremental head grade, total tonnes, and contained metal.
The mining engineer is now ready to undertake the pit design. The pit design step introduces a benched slope profile, smooths out the pit shape, and adds haulroads. Hence a couple of key input parameters are required at this time. The mining engineer will need to know the geotechnical pit slope criteria and the truck size & haul road widths. Let’s look at both of these.
Ramps: Next the mining engineer needs to select the truck size, even though the production schedule has not yet been created.
Podcasts. There are thousands of them out there, free for anyone to access. This blog post is about the top mining podcasts that I find entertaining and educational. There are probably some missing from this list that I have not heard about. One only has so much free time in a day.
Fresh Thinking by Optiro-Snowden
There is no shortage of material in the podcast world about the mining industry. It all depends on what grabs your attention.
Normally Major and Intermediate miners advance their projects through the study stages with the ultimate intent to actually build the mine. Sometimes they may opt to sell their project if it no longer fits in their long term strategy or if they desperately need some cash. However, selling the project when it was first acquired was likely not their initial intent. They want to be on a 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.
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.