Mikael Artursson, Minalyze Pty Ltd, Australia, considers why machine learning should be used in the mining industry.
M
achine learning (ML), artificial intelligence, and deep learning are all buzz words that have been frequently mentioned in the mining industry over the past few years. A question that often comes up in discussions related to data in the industry is: “Can ML do this?”. Very often, the answer is yes, but there is no point introducing ML just for the sake of it. The first step is to define the problem that one would like to solve. Why should ML be considered in the first place? In general, ML could be set up to solve a well-defined problem in a fast, objective, and cost-efficient way. There is no doubt that ML could be used to solve almost any problem out there, although this is not without certain pre-requisites and it does not mean it is practically the best solution for just any issue.
Solving a real issue The issue that this article focuses on solving is a well-known issue related to classification of rock-types when logging lithologies. This is something that any geologist that has been logging rock core would be able to relate to. The task of logging and classifying rock types is very time consuming, subjective and iterative. The subjective nature of the task, in particular, means that results vary based on the person, their educational background and, of course, any previous experience. A classic saying is that if four geologists look at a piece of rock, there are at least five answers to what type of rock it is. This problem could escalate quickly, since there is a turnover of people in the industry and the new persons need to be calibrated towards the
global mining review // September 2021
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