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Wednesday, June 26 • 16:30 - 16:50
Machine Learning for Natural Resources

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In order to identify new exploration targets to test potential zones of gold mineralization, geologists gather different sources of data such as drill hole observations and measurements to justify their decisions. Such activity is complex and requires expert tacit knowledge specific to each mining project, meaning that the location's underlying geology is unique. With the aim of aiding this decision making process, we present a machine learning methodology to predict the level of gold mineralization based on the surrounding geological information. In particular, we propose the use of Deep Learning models, 3D Convolution Neural Networks, to take advantage of the spatial nature of the data.  Through experiments with data from a real mine, we show that our proposed model overcomes the baseline model for all the metrics used, providing a much more accurate feature for the geologists in their investigations.

avatar for Bianca Zadrozny

Bianca Zadrozny

Research Manager, IBM
Bianca Zadrozny is a research manager at IBM Research Brazil, leading the Natural Resources Analytics group. The group's mission is to conduct research projects in knowledge-augmented machine learning for decision making in the areas of oil&gas and mining, with a great focus in developing... Read More →

Wednesday June 26, 2019 16:30 - 16:50 GMT-03
Room 8 Av. Rebouças, 3970 - Pinheiros, São Paulo - SP, 05402-600, Brazil