I have a very special relationship with stockpiles. A few years ago, I was on the top of a stockpile picking up my spot heights and mapping out my breaklines with a good friend, whilst at the same time my wife was in the labour ward 16km south of my location. Don’t judge.
A couple of years later, we had the brilliant idea of scanning each stockpile with our brand-new Faro Focus 3D laser scanners, and a few years after that we tried out photogrammetry with the DJI Mavic Pro Platinum and Pix4D, but here’s the thing; stockpiles are always going to be an estimate. No matter what equipment you throw at it, several factors will always keep the exact value elusive.
When I did my first large-scale stockpile project, I used a Wild RDS theodolite. Yes, you read that correctly.
Based on the T16 theodolite, the RDS was used with a vertical staff and the normal stadia lines were replaced by very flat curves. This badass piece of equipment made light work of bulk volumes. The work was nothing like the reflectorless total stations of this day and age.
But I digress, the point density (or the number of point measurements per unit area) was relatively sparse when compared to the number of points you could pick up in the same time frame with a total station. So with the RDS, you needed significantly more planning in the selection of your spot heights and break lines than you would with a total station. With newer total stations, and the reflectorless sensor’s measurement and onboard recording, you could go nuts picking as much detail as your heart desired (disk size permitting). This was a far cry from needing a dude booking your figures and another dude clamoring up the side of a stockpile, good times.
My point is the point density increased with technology. I’ve deliberately avoided using the word improved, but I’ll get back to that in a moment. Laser scanners, Lidar (Light Detection and Ranging), drone photos and associated software have really picked up on the number of measured spatial points per unit area. This is one factor that affects the quality of your volumetric estimate.
The original topography of the base on which the stockpile is sitting is another source of volumetric error. The ideal scenario is a perfectly flat slab onto which everything is heaped. Unfortunately, this only ever occurs for materials like high value concentrates. The next best alternative is a detailed model of the ground on which the stockpile sits. This is also the most practical, however, this practice is sometimes neglected and surveyors are required to pool their resources and establish the base of a massive dump or stockpile from historic records. So for non-survey readers, it is absolutely imperative that the survey team is involved in the decision on where to place a stockpile or dump, in order to provide the opportunity to create a file depicting the natural topography; this incidentally applies to open pits as well.
Although this will not necessarily affect your volume calculation, the final tonnage value you end up with will be affected by the variable density of your stockpile. This is a function of the material type with coarser material having a lower bulk density than finer material if the instu source is the same.
Generally speaking, the bottom of your stockpile is denser than the top and this is due to the following very scientific explanation:
“The stuff above squashes the stuff below.”
The equipment driving to the top of the heap to dump more stuff vibrates and settles this material into a compressed compact conglomerate. This obviously changes the density of the material to be measured.
Most software applications create digital terrain models of wireframe by linking each spatial point to the next in a systematic manner that most accurately represents the terrain being measured. However, these links are invariably subject to the algorithms running in the background and as can be envisaged, these methods vary from one package to another. However, in most cases, the differences are minute as long as the spatial points have been honoured.
Ultimately, the method and technology are usually justified by the material being measured; the more valuable the material, the more accurate the measurement methods. This is by no means a comprehensive list, and additions are welcome in the comments.
Ultimately this volume will always be an estimate.