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- Title
Geochemical Evaluation of a Geothermal Region for the Trace Elements Related to the Subsurface Mineralization Using Machine Learning Methods.
- Authors
Moradpouri, Farzad; Sabeti, Hamid
- Abstract
The aim of this paper is to identify the promising geochemical anomalies in the geothermal area of Mianeh in northwestern Iran. This was carried out using 840 stream sediment samples, which were analyzed by ICP-MS for 42 elements for Multivariate Geochemical Analysis (MGA). Due to the high migration and mobility power of the Arsenic element, it was selected as the main geothermal pathfinder. Thus (As) element was determined as a labeled variable, and the other important elements and their relationships with (As) can be identified through MGA. Some of these related elements can then be proposed for future exploration. Firstly, for the implementation of MGA, a Probability Plot Modeling (PPM) on the (As) concentration values was carried out to separate background and anomaly subpopulations and extract threshold values for each subpopulation. Secondly, based on the PPM results for the (As) variable, the Discriminant Function Method (DFM), using their functions of code 0, 1, and 2, was implemented to distinguish different variables belonging to each of those subpopulations (background, mixture, and anomaly). Also, Principal Component Analysis (PCA) and Clustering Analysis (CA) were carried out which lead to almost similar results to the DFM. Finally, the elements of Au, Mo, W, Cu, Be, K, and Rb were recognized as the most important elements related to the (As) element. Finally, ArcGIS mapping shows a geothermal region from the NW to NE of the study area for plans and detailed exploration.
- Subjects
TRACE element analysis; ARSENIC; NONMETALS; MINERALIZATION; BIOMINERALIZATION
- Publication
Jordan Journal of Earth & Environmental Sciences, 2024, Vol 15, Issue 2, p94
- ISSN
1995-6681
- Publication type
Article