Hi All, Let’s talk about improving these estimates or how to do a site specific adjustment. Revisiting the literature I found this paper Álvaro Corral, Álvaro González (2019). Power Law Size Distributions in Geoscience Revisited one could argue (but you won’t argue) that I should use a power law distribution for the cavities instead of an exponential, but that would require two parameters instead of one and it is easier to reason with less parameters at least initially.

Hi All, In this article we are going to integrate our estimate of background rate of cavities from caliper data we modelled in Part 1 with the likelyhood of detecting a cavity by drillhole spacing we generated in Part 2 . One of the issues with the simulation modelling estimating the background rates in Part 1 was the estimate of cavity distribution was done for the entire data set. As this is an Iron Ore data set from open file WAMEX data I know from experience that there are more cavities in certain stratigraphic units and alteration zones (hard cap).

Wecome back, Before integrating the data we generated in part 1 we are going to estimate the chance of intersecting a cavity on a blast pattern for a series of cavity sizes and blast pattern designs. To start the demonstration we build a baseline drill pattern of 5x7m with a fixed 0.27m hole diameter that we will keep fixed for all simulations. Now that we have a grid, we add a cavity of 1m diameter.

Hi All, Here is the first in a series of posts covering a bit of ground on cavity detection. From estimating the proportion of cavities in exploration drill holes to their chance of detection with MWD on a blast pattern. First off we define a cavity, for the sake of an exploration drill hole a simple definition might be a caliper measurement that flatlines at the maximum value. Looking over the histogram we can see a few points of interest: