News News
Contact us
  • Customer service number:64321087
  • Commercial service telephone:13918059423
  • Technical service telephone:13918059423
  • Contact person: Mr. Cui 
  • Service
  • Address: room 107, building 8, no. 100, guilin road, xuhui district, Shanghai

How machine learning can help identify new, deeply buried porphyry copper deposits

The date of: 2022-09-06
viewed: 2


A recent study published in the Journal of Geophysical Research: Solid Earth, presents two novel machine learning techniques to identify new, deeply buried porphyry copper deposits by characterizing magma fertility.
Fertile magma refers to magmas that can form porphyry deposits.
According to the paper’s authors, their main objective was to improve traditional geochemical indicators plagued by high false-positive rates.
To achieve such a goal, the researchers developed two algorithms, which they called ‘random forest’ and ‘deep neural network.’ They formulated the models using a global dataset of zircon chemistry, which is normally employed to evaluate the porphyry copper deposits in magma.
In detail, they focused the models on 15 trace elements. They then validated the models with independent data sets from two well-characterized porphyry copper deposits in south-central British Columbia, Canada, and Tibet, China.
Both models resulted in a classification accuracy of 90% or greater. The ‘random forest’ model exhibited a false-positive rate of 10%, whereas the ‘deep neural network’ model had a 15% false-positive rate. In comparison, traditional metrics report false positives at a 23%–66% rate.
Europium, yttrium, neodymium, cerium, and other elements emerged as significant indicators of magma fertility.
The models’ performances show that the algorithms can distinguish between fertile and barren magmas using trace element ratios. Notably, model performance was not affected by regional differences or geologic settings.
In the scientists’ view, as the demand for rare earth elements, minerals, and metals surges, machine learning is going to continue to be used as a robust, accurate, and effective approach for identifying and locating porphyry copper resources.

Hot News / Related to recommend
  • 2024 - 04 - 12
    Click on the number of times: 0
    source:TechxploreTwo-dimensional (2D) superconducting materials have been found to be promising for the development of miniaturized optoelectronic devices. To perform well while consuming less energy,...
  • 2024 - 04 - 11
    Click on the number of times: 0
    source:phys.orgResearchers at Columbia University have successfully synthesized the first 2D heavy fermion material. They introduce the new material, a layered intermetallic crystal composed of cerium...
  • 2024 - 04 - 10
    Click on the number of times: 0
    source:phys.orgNew forms of the light-emitting materials called phosphors, with enhanced versatility relative to existing options, are being developed by researchers at the National Institute for Mate...
  • 2024 - 04 - 09
    Click on the number of times: 0
    source:EurekalertThe ScienceThe metals called lanthanides have valuable properties for clean energy technologies such as electric vehicles and wind turbines and for many other applications. These elem...
  • Copyright ©Copyright 2018 2020 Shanghai rare earth association All Rights Reserved Shanghai ICP NO.2020034223
    the host:Shanghai Association of Rare Earth the guide:Shanghai Development and Application Office of Rare Earth the organizer:Shanghai rare earth industry promotion center