Economic Analysis of Mineral Deposits- Part III: October 2010

This is the technical portion of the article in which I explore the importance of economic analysis of mineral deposits. In my experience, the economic analysis of mineral deposits is required for the following three primary purposes;

Purpose #1            Giving Context to Exploration Programs
Purpose #2            Identifying Acquisition Targets
Purpose #3            Due Diligence Evaluations for Mergers and Acquisitions

Purpose #2 – Identify Acquisition Targets

Last month I explained Purpose #2 – Identify Acquisition Targets and described some of the methods and sources of information I use to identify and evaluate interesting targets. I also gave an example of building a simple economic model for an underground copper mine based on historical mining costs and other operating statistics. I would like to continue with this same topic with a second example of using another “Short Cut” to evaluate an opportunity, this time for a thermal coal property.

First I would like to explain that there are a number of “Short Cuts” in the form of costing formulas, factoring rules or basic technical rules of thumb that can be used in mining cost estimating for high level evaluations. Most of these short cuts have been established and passed down over the years through experience and by trial and error. Anyone really interested should Google a collection of rules of thumb called the “Hard Rock Miner’s Handbook” written by Jack de la Verne and sponsored by McIntosh Engineering of North Bay Ontario. The pioneer of mining cost formula modeling is T.A. O’Hara, a mathematician and mining engineer who while with Hudson Bay Mining & Smelting during the 1970’s, published a number of empirical formulas for quickly determining quantities such as mine personnel requirements, electrical power demands, mining capital and operating costs and equipment sizes etc. within various regions of the world.    

The short cut that I would like to explain in the following example is the “Six-Tenths Rule” which defines natural internal economies of scale of production since mining costs (both construction capital and operating) are a mixture of “Fixed’ and “Variable“ costs. The Six-tenths rule quantifies the relationship between the relevant costs of a companies decision to expand production and the increased internal economies that result from that expansion. In other words, if it costs $100M (Cost 1) to build a mine with a production rate (Parameter 1) of 1Mtpa, the cost of building a 2Mtpa (Parameter 2) mine should be about $152M (unknown C 2) using the Six-Tenths Rule applying the Formula 1 below.

Formula 1 : Cost ₂ / Cost ₁ = ( Parameter ₂ / Parameter ₁)^0.6
More precisely the average cost of major equipment have been observed to follow, roughly the same formula above but where the exponent has been replaced by anything from .6  to 2/3 to .7. The choice of the exponent is dependent upon the particular industry and upon the degree of conservatism by the estimator.
Building the Model – Example 2 (“Short Cut”)

This is a simple but actual example of a quick capital cost analysis of a thermal coal opportunity located in Western Canada where I used the Six-Tenths Rule.

The property was located in a well known and coal mining friendly region with good access to existing rail infrastructure. The property had a respectably historical coal resource (+80Mt) which could be mined at about a 4:1 strip ratio with a clean (washed) coal quality of 5,700 Kcal/kg, Moisture 12%, Ash 11%, Sulphur 0.29%, Volatile Matter 31.6% and Fixed carbon Content of 45.4%. Historical metallurgical work indicted that washing the coal to a saleable quality would provide a yield of 57%. This was a project which had been dormant since the mid-1970’s when a full feasibility study had been completed. Although the project IRR (internal rate of return) was very positive it was turned down by the optionee in favor of an alternative and competing project in Columbia.

Since the coal had to be washed to be saleable, one of the most import issues for me was determining the cost of a new wash plant. After making a couple of calls to my coal industry contacts, I quickly came to the realization that the cost of a wash plant could vary significantly depending upon the location of the project, equipment supplier and construction contractor etc.. However, I had one advantage which could assist me greatly in estimating the cost of a plant and this was the 1983 capital cost estimate of a 2Mtpa (Million tonnes per annum) and an alternative 4Mtpa plant defined in the historical feasibility study (FS).  Although very out of date, the feasibility estimate could be very helpful in giving insight into the economics and particularly the economies of scale necessary to make this thermal coal project viable.

What I wanted was to not only come up with a current cost of building a 2Mtpa coal washing plant but also to estimate the cost of building much larger plants at annual capacities of 4, 5, 6, 7 and even up to 8Mtpa of clean coal. My interest in these larger production rates was because I was aware of other historical coal resource tonnages within the adjoining properties (extension of the known seams). In the event that the project did not look attractive, possibly consolidating the local coal resources could result in a viable and much more attractive coal opportunity to the right investor (client).

The historical feasibility study on the project was well done and at a cost of $5M (which was allot of money in 1983) and was based on a Base Case 2Mtpa clean coal operation but also looked at the benefits of operating at a similar design but 4Mtpa capacity. The original cost estimate in 1983 for the 2Mtpa plant was $73.6M. The 1983 cost of a 4Mtpa plant was estimated in the FS to be $121.7M. My first step was to take the two historical FS capital costs at the respective production rates and solve for the exponent values which made Formula 1 true (see Formula 1, above). Table 1 below, shows the historical FS capital costs for the plants at 2Mtpa and 4Mtpa and the appropriate (calculated) exponent values.

Table 1
BUILDING A MODEL
Example – Capex Estimate
Coal Wash Plant (1983 $C’s)

As shown above, the exponents vary widely from sub-cost item to sub-cost item (ranging from 0 to 1), but averaging at 0.73 for the Total Project Cost for the two production rates.

The next step was to get some cost estimating help and retain an estimator familiar with coal wash plants and to give me a order of magnitude or scoping level estimate of building the same 2Mtpa plant as described in the 1983 feasibility. This was a relatively inexpensive effort as I was only looking for a scoping level estimate and the estimator could use the FS as a guide for the size and type of equipment selected for this specific coal type and project. He came up with a revised capital cost for a 2Mtpa coal wash plant of $200M in current Canadian dollars (2008 at the time).

The final step was then to apply the base $200M capital cost for the 2Mtpa plant with the 0.73 exponent at increasing production rates to determine capital cost for the various expanded wash plant capacities as shown below in Table 2.

Table 2
BUILDING A MODEL
Example – Capex Estimate
Plant Capital vs Capacity

Table 2 shows that there is some very strong economies of scale for expanding production and therefore reducing the total cost of producing a tonne of clean coal (maximize profit margins). This however assumes that the coal seams of interest are of sufficient size and geometry (i.e. thickness, continuity, and depth etc.) to support high production rates.  The other caveat that must be kept in mind with these results is that the degree of accuracy of the capital cost estimates reduces with increasing production rates. This is because at some point you are extrapolating too far from the original base plant design and capital cost estimate. At some point when increasing the production rate a total new approach will have to be taken to the plant design and equipment selection.  For example, if the original 2Mtpa plant design called for installing a primary jaw crusher, you may find that a gyratory crusher would be required for production rates greater than 4Mtpa. In this case a new approach to the plant operation maybe required which would also impact the capital and operating costs of the operation which would not be reflected in the original Six-tenths exponent. In this case a new base cost estimate would be required.

I hope with this example, it is again apparent that you don’t have to spend allot of time and money in doing a scoping level, first pass evaluation on a target opportunity. However you do have to work the limited information that you have been given and look for creative ways in which to work this information to give context and guidance for that next decision whether to reject or pursue the opportunity to the next and more expensive stage(s) of analysis. 

The rest of the Story

The coal story above did not have a happy ending for yours truly. My prospective client for this proposed deal was very bullish on coal but thought the venders were asking too much for the property. I tried to show that this acquisition would be the cornerstone to set up two or three other bigger transactions which would give the project some real critical mass, economies of scale and also create investor interest. The property was acquired for cash and a production royalty by an Australia junior (Xenolith Resources) shortly after we withdrew our interest. Xenolith has changed its name to Coalspur Mines and is listed on the ASX (CPO) with plans to soon have a dual listing on the TSX. The company in two years has been very successful in growing their thermal coal assets in the Hinton region of Alberta in a strategy very similar to what I was hoping to do for my client. I’m therefore a little biased when I say I think they are on the right path!