Sara Momenipour - Master in Science Economic Geology
Nima Dolatabadi - Master in Science Geophyics

This study focuses on the challenges faced by mineral exploration in Iran and proposes theintegration of Python programming and machine learning to overcome these challenges. Itexplores the complexities of geological and topographical mapping, remote sensing applications,geophysics, and core drilling. Python libraries like GDAL, GeoPandas, Spectral Python, OpenCV,ObsPy, and GeoMagPy are highlighted for their ability to automate and enhance various aspectsof mineral exploration. The study emphasizes the importance of accurate geological mapping andthe potential of deep learning methods in analyzing remote sensing data. It also discusses theapplication of joint inversion techniques for interpreting exploration data and improving theunderstanding of magnetotelluric data. Despite challenges related to insufficient data and ashortage of specialists, the adoption of Python programming and machine learning techniques canlead to significant advancements in mineral exploration in Iran, fostering economic developmentand job creation in the mining sector.

PYTHON, MINERAL, EXPLORATION, ML