Geophysics
Geophysical targeting with AI: load processed magnetics, gravity and EM grids into VRIFY DORA or OreFox, which fuse them with geochemistry to rank targets.
Eigenform AI Geo Tooltips: Page 9
Geotechnical Monitoring
Geotechnical monitoring with AI runs slope radar (IDS GeoRadar) and satellite InSAR (SkyGeo) through ML layers so wall-failure warnings surface early.
Geotechnical Reports
Automate geotechnical reports by connecting Power BI or Tableau to your live geotechnical block model and monitoring feeds, so they regenerate on their own.
Grinding
Grinding circuit optimization with AI: closed-loop platforms like ABB Ability Expert Optimizer or Imubit learn your mill and adjust setpoints live.
Ground Water Model
Build your groundwater model in MODFLOW 6 or FEFLOW, then use PyHydroGeophysX to test it against resistivity and EM data through pyGIMLi or SimPEG.
Handheld XRF
Scan rock, core or soil with a handheld XRF analyzer like the Evident Vanta Max, and let onboard chemometric calibration return near-lab results in seconds.
Hydrological Modeling
Make hydrological modeling AI-ready: script MODFLOW 6 in FloPy instead of a GUI, so the same pipeline can feed ML calibration and prediction workflows.
Hyperspectral (Point or Scan)
Hyperspectral scanning, point or imaging: use a handheld spectrometer for spot mineral ID or a core imager for full coverage, then classify spectra with ML.
Hyperspectral imaging / Spectroscopy Device
Point a portable spectrometer like the ASD TerraSpec at rock or core, and onboard spectral-library matching identifies alteration minerals in seconds.
Hyperspectral Input Models (High Resolution Clay Models)
Hyperspectral clay models start with Corescan HCI or CSIRO HyLogger scans, about 800,000 spectral samples per metre, then automated mineral interpretation.