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Mathematical Geosciences in Exploration Geochemistry

Special Issue Information

Dear Colleagues,

Mathematical geosciences include geostatistics, simulation, uncertainty quantification, classification, numerical and statistical analysis, data/big data analysis, machine learning, and deep learning. All these methods in 2D (on the ground) to even 5D (underground/subsurface) have been developing and being applied to geological data in different fields such as exploration geochemistry, exploration geophysics, remote sensing, petroleum engineering, mining engineering, hydrology, GIS and mineral prospectivity mapping, etc. In exploration geochemistry, such methods have been taken into consideration to recognize geochemical anomalies vectoring into mineral deposits with less uncertainty. This helps decision-makers to focus follow-up exploration projects on the anomalies defined as significant using robust models. Considering these points, all papers related to advanced methods and developments in applied geochemistry using various anomaly classification methods such as fractal/multifractals and geostatistical modeling (e.g., uni/multivariate analysis and simulation methods), error propagation and uncertainty quantification, GIS and mineral prospectivity mapping, and numerical/data analysis are welcome.

Dr. Behnam Sadeghi
Guest Editor

Manuscript Submission Information

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Keywords

  • mathematical geosciences
  • exploration geochemistry
  • fractal modeling
  • geostatistics
  • classification
  • GIS
  • simulation
  • uncertainty quantification
  • error propagation
  • geochemical data
  • geomodeling
  • data analysis

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Mining - ISSN 2673-6489