none 10.1190/tle36030215.1 Society of Exploration Geophysicists Society of Exploration Geophysicists 186 88646579 5980 2025120814594376200 10.1190 2025-12-08T19:59:50Z 2017-03-03T15:41:15Z 72 The Leading Edge 1070-485X 03 2017 03 01 2017 36 3 Antoine Caté 1 INRS, Centre Eau Terre Environnement. 2 geoLEARN (geolearn.ca). Lorenzo Perozzi 1 INRS, Centre Eau Terre Environnement. 2 geoLEARN (geolearn.ca). Erwan Gloaguen 1 INRS, Centre Eau Terre Environnement. Martin Blouin 1 INRS, Centre Eau Terre Environnement. 2 geoLEARN (geolearn.ca). http://orcid.org/0000-0003-2327-5907 Machine learning is becoming an appealing tool in various fields of earth sciences, especially in resources estimation. Six machine learning algorithms have been used to predict the presence of gold mineralization in drill core from geophysical logs acquired at the Lalor deposit, Manitoba, Canada. Results show that the integration of a set of rock physical properties — measured at closely spaced intervals along the drill core — with ensemble machine learning algorithms allows the detection of gold-bearing intervals with an adequate rate of success. Since the resulting prediction is continuous along the drill core, the use of this type of tool in the future will help geologists in selecting sound intervals for assay sampling and in modeling more continuous ore bodies during the entire life of a mine. 03 2017 03 01 2017 215 219 1 10.1190/crossmark-policy library.seg.org true 2017-03-02 10.1190/tle36030215.1 https://pubs.geoscienceworld.org/tle/article/36/3/215/311757/Machine-learning-as-a-tool-for-geologists https://pubs.geoscienceworld.org/seg/tle/article-pdf/36/3/215/7434019/tle36030215.1.pdf https://pubs.geoscienceworld.org/seg/tle/article-pdf/36/3/215/7434019/tle36030215.1.pdf https://pubs.geoscienceworld.org/tle/article/36/3/215/311757/machine-learning-as-a-tool-for-geologists Machine Learning 45 1 5 2001 10.1023/A:1010933404324 Random forests Pre-feasibility study technical report, on the Lalor deposit, Snow Lake, Manitoba, Canada: HudBay Minerals 2012 Targeted Geoscience Initiative 4: Contributions to the understanding of volcanogenic massive sulphide deposit genesis and exploration methods development 131 2015 Geology and Au enrichment processes at the Paleoproterozoic Lalor auriferous volcanogenic massive sulphide deposit, Snow Lake, Manitoba Data mining and knowledge discovery handbook 853 2005 10.1007/0-387-25465-X_40 Data mining for imbalanced data sets: An overview Journal of Geochemical Exploration 145 12 2014 10.1016/j.gexplo.2014.05.008 Using geochemical proxies to model nuggety gold deposits: An example from Sunrise Dam, Western Australia JMLR 12 2825 2011 Scikit-learn: Machine learning in python Python machine learning 2015 Ore Geology Reviews 53 93 2013 10.1016/j.oregeorev.2013.01.002 A multi-sensor logger for rock cores: Methodology and preliminary results from the Matagami mining camp, Canada Recent trends in gold discovery 2011