USA

New technology is making overlooked deposits viable for development and production

Exploration in Arizona

AI-driven hyperspectral imaging and satillite remote sensing are currently being deployed across Arizona to identify critical strategic minerals and gold reserves in areas that were previously difficult to explore due to high costs or geological complexity.

 

Key Exploration Areas 

  • Arizona Copper Porphyry Belt: This region is a primary focus for high resolution airborne geophysical surveys.  These surveys aim to identify and map concealed mineral resources, such as copper and molybenum, that are hidden beneath sediment or in geologically complex structures.

  • Mohave County: This area was recently subject to a high resolution (3-meter resolution)  hyperspectral survey allowing the identification of a broad suite of minerals, including alunite, kaolinite, and sericite, which are indicators of gold-silver deposits that were previously overlooked by using the standard low resolution (30-meter resolution) daand upper mantle.

  • Legacy Mine Waste Sites (Statewide): The USGS (United States Geological Survey) is investing over 1 million dollars to map critical minerals in mine wastes across Arizona and New Mexico.  Using AI to analyze hyperspectral data, researchers can identify valuable minerals in "tailings" (waste piles) that were previously cost-prohibitive to re-process without precise compositional maps.

  • Laramide Porphyry Belt: Modern reconnaissance geochemical surveys, completed by remote sensing are targeting this belt to find resources such as lithium and rare earth elements.

  • Remote and Restricted Zones: Satellites like EnMAP provide global, high-quality hyperspectral data that bypasses the logistical requirements of sending personnel into physically inaccesable or regulated areas.

 

How Technology Unlocks Potential

  • Bypassing Complexity: AI models, such as Support Vector Machines and Neural Networks, process the "deluge" of raw data to recognize subtle chemical signatures in minerals like monazite (for rare earth elements) or lithium, which human analysis might miss in complex geological settings.
  • Reducing Exploration Times: AI-driven exploration can cut the time to identify mineral "hot-spots" from years to months.

  • Enhanced Resolution: By moving from 30 meter resolution ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) to 3 meter resolution VW3 (WorldView 3) allows for the mapping of small, high-grade upwelling zones and structural features that were previously too small to be seen from space.