Machine Learning Developments and Applications in Solid‐Earth Geosciences: Fad or Future?

YE Li, D O'malley, G Beroza, A Curtis… - … Research: Solid Earth, 2023 - Wiley Online Library
After decades of low but continuing activity, applications of machine learning (ML) in solid
Earth geoscience have exploded in popularity. This special collection provides a snapshot …

Data mining for geochemical signatures of volcanic-type uranium mineralization, Duolun-Guyuan prospect, North China

Z Zhang, Z Wang, L Wang, X Zhang, Y Liu… - Journal of Geochemical …, 2024 - Elsevier
Application of advanced data mining methods to various types of geochemical data is able
to fingerprint valid signatures of mineralization, thus unveiling ore genesis and discovering …

Machine-learning oxybarometer developed using zircon trace-element chemistry and its applications

S Zou, MJ Brzozowski, X Chen, D Xu - American Mineralogist, 2024 - degruyter.com
Magmatic oxygen fugacity (f O2) is a fundamental property to understanding the long-term
evolution of the Earth's atmosphere and the formation of magmatic-hydrothermal mineral …

Slab breakoff diorite porphyries derived from two cratons in a continental subduction zone, Sulu orogen, China

P Feng, L Wang, T Kusky, Z Chen, W Hu… - …, 2024 - pubs.geoscienceworld.org
Syncollisional magmatism plays an important but underappreciated role in continental crust
growth and maturation. However, the origin of syncollisional intermediate magmas in …

Machine Learning in Petrology: State-of-the-Art and Future Perspectives

M Petrelli - Journal of Petrology, 2024 - academic.oup.com
This article reports on the state-of-the-art and future perspectives of machine learning (ML)
in petrology. To achieve this goal, it first introduces the basics of ML, including definitions …

Quantitative provenance analysis through deep learning of rare earth element geochemistry: A case from the Liuling Group of the East Qinling Orogen, Central China

Z Zhang, N Yang, Z Hong, J Yang, B Du… - Frontiers in Earth …, 2022 - frontiersin.org
With the ever-growing availability of massive geo-data, deep learning has been widely
applied to geoscientific questions such as sedimentary provenance analysis. However …