Automating Block Modelling with AI
<p>Block modelling is a popular way to analyse the numeric data that is collected during drilling programs. In DRIVER we create and use block models to view the estimated concentrations (or grade) obtained using kriging or inverse distance interpolation methods. But creating accurate block models (i.e., turning the sparse numeric data into an interpolated grid) is often a time-consuming and technically involved geostatistical process. For this reason, multi-element drilling datasets will rarely have block models made for all the assays available.</p>
<p>In <a href="https://minerva-intelligence.medium.com/automating-anisotropy-analysis-with-machine-learning-45c578700866" rel="noopener">our last blog post</a>, we covered how DRIVER’s automatic anisotropy algorithm can be used to rapidly assess the geostatistical properties of a dataset and determine the optimal anisotropic configuration required for modelling.</p>
<p><a href="https://minerva-intelligence.medium.com/driver-primer-2-block-modelling-602a32e7953e"><strong>Visit Now</strong></a></p>