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Lithological data determines the location of a prospective area at the early stage of geological exploration and are a valuable reference point for identifying unfavorable geological conditions during exploration. Core analysis is usually done manually by geologists. They determine lithology by the color, structure, and texture of the rock, as well as its mineral composition. This requires specialists to have a high level of expertise and extensive experience in the field. This work is not only labor-intensive and time-consuming, but also very subjective. In addition to naked-eye identification, geologists also use some physical inspection techniques (X-rays, CT scans, electron microscopes and isotope techniques) to help locate valuable rocks.
The AURAi solution makes it possible to use computer vision and machine learning in the geological exploration of the subsurface. Researchers are turning their attention to deep neural networks, and with its high computational power, AURAi will soon become the dominant solution in primary core description.
The AURAi solution makes it possible to use computer vision and machine learning in the geological exploration of the subsurface. Researchers are turning their attention to deep neural networks, and with its high computational power, AURAi will soon become the dominant solution in primary core description.
