No matter what commodity a mine will be producing it simply cannot get started without exploratory drilling having taken place. During the exploratory stage, a vast amount of information is gathered on the potential economic material. This data is then used to inform resource models that can make or break the success of downstream mining activities.
However, while typical exploration data—such as core and/or chip samples, downhole geophysics, structural data, lithology description, and groundwater yield—are important, there are additional data that should be considered for collection during this stage to maximise the investment in exploration.
Types of data
To make most of the available data, it is important to know what is potentially available. The options begin with the analysis of trace fossil descriptions/collection. Trace fossils, such as shells from gastropods, can provide an insight into the chemical makeup of the rock being drilled into. By collecting this data, users can more quickly identify formations and varying facies.
By capturing detailed facies descriptions, exploratory drillers will have a greater wealth of data that details changes in the depositional environment. This data will then provide more access to geologic indicators of potential ore locations.
Images of core or chip samples can be useful. While core/chip sample data is a typical data set for exploration with the data generally recorded in a spreadsheet, visual cues about the material can be overlooked. By including images, it is possible to expand the amount of recorded data by visually assessing the sample and catch additional, key information—such as whether or not the material has been oxidized.
Completing sieve tests enables analysists to capture key data about grain size that can have hydrologic significance. With this data, they can also figure out how much of the material is being lost once it gets to the crusher or mill.
Geotechnical information, such as compressibility, bulk densities etc. are crucial to understanding slope stability
Geotechnical information, such as compressibility, bulk densities etc. are crucial to understanding slope stability and how the material will act if there is a failure. Capturing this data early allows mine owners to plan and prepare for the specific behaviour of the material being mined so that they are not caught off guard once the mine is in operation.
Miners should take time to get to know the mineral characteristics of the area being explored. By arming themselves with data around material characteristics, mine operators can prepare their sites for how the material will behave under varying scenarios. For example, if they encounter bentonite during exploration, they can prepare for its swell factor that could cause future instability.
They could also collect data that could be used in Young's Modulus and Poisson's Ratio. Once operational drill and blast procedures begin, they will know how the material will heave when it is shot—saving the mine both time and money during operations.
It is important to note that there is such a thing as "too much data". Do not get distracted by trying to collect everything. But, note an anomaly during exploration, it is worth the cost to go that extra mile now instead of trying to find funding later on.
Collecting these "outside-the-box" exploration data sets may require a small, additional investment upfront, but the benefits they bring further down the life of mine can greatly expand a mine's revenue.
At the end of the day, a model is a model, but that model impacts a number of operations throughout the life of the mine. And the more tools a miner operator has at the start will boost downstream success.
Benefits of collecting ancillary exploration data
Going above and beyond what is mandated in the typical exploration stage can have significant benefits down the road. Three key benefits of collecting this "outside-the-box" exploration data include:
Increased resource model accuracy
With access to more exploration data, mine operators can increase the accuracy of their initial resource model. This leads to more accurate tonnage estimates, which fuels a better mine plan and greater resource recovery.
Additionally, starting with a more accurate resource model helps ensure lower discrepancy rates during the resource model audit when the mine is in operation.
Enhanced understanding of the deposit
For many mines, complex geology can complicate production. Without an in-depth knowledge of the material under the surface during the exploration phase, the downstream processes could become excessively complicated causing a loss in revenue or missed projections.
Seemingly ‘ancillary' data, such as material descriptions, seam or unit designation, as well as grain size of mineralisation, could help with a better understanding of what events coordinate to what types of assays, reducing the need for "model smearing". Thus, with a more complete picture of the deposit operators will have better production rates, reduced waste, and less dilution.
Even better? With a greater deposit understanding upfront, engineers are likely to reduce the over-design of the mine, which will help bring overall operational expenses down for the life of the mine.
Improved life-of-mine processes
One of the biggest benefits of collecting more data during exploration is that mine operators have it as a resource in the future.
When an operator is in a later stage of the mining process, if an anomaly pops up, he can go back and audit the archive exploration data for insight. For example, say the team comes across faulted or oxidized material during production in an area where they were not expecting to find variances. They can reference archived exploration data to help explain why this may have occurred — they may not have found explicitly faulted or oxidized material, but instead found indicators of these traits. This data then enables them to tell a more complete story of the geology in the immediate production area, thus adjusting operations to better take geologic information into account.
With access to this data, especially when paired with a mine planning software, miners can cut down on operational costs—such as redrilling—and use their enhanced understanding to improve processes through the life of the mine.
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