
Create a drill hole database in Micro Mine by importing color, survey, geology, and assay tables from CSV, set delimiters, and color-code by geology and iron assay.
Apply a top cut to cap outliers and nugget effects, using a threshold to constrain data for more accurate block modeling.
Move from basic block modeling to drillhole compositing, learning how to choose compositing length using statistics and histograms, apply filters, and generate density-weighted downhole composites for block modeling.
Create a search ellipsoid to estimate a point's grade from surrounding data, then configure its three-dimensional axes, scale, rotation, and sectors, and save it for use in estimation.
Explore filling blank block model by interpolating data with inverse distance weighting, using four by four by four blocks and a search ellipsoid to classify blocks as measured or inferred.
This block modelling course will teach you to create an efficient block model and estimate the grade and tonnage of a mineral resource using one of the best software in the mining industry which is Micromine. This advanced course outlines the main steps needed to perform the estimation and provides background information where needed to explain the underlying statistical concepts. This course Begins by statistically describing the data (mean, median, histograms…), and then we move to the steps required to construct a block model like Drillhole compositing, blank model creation and the classical Inverse Distance Weighted (IDW) interpolation for estimation. Lastly, we will classify the block model into Measured, Indicated, and Inferred categories based on the level of confidence in the assay data and how close the estimated block to the assay data and then report on the ore grade and tonnage within each category. Even that this course might look like it is for experienced geologists, mining engineers, or geoscientists in general it’s delivered in an easy to follow methodology where beginners can follow along too. Any questions related to the course subject or the software used will be answered and more lectures will be added if needed. A part 2 of this course will be created soon that will get into geostatistical methods and variogram modelling.