Botswana Minerals has reported that an AI-assisted exploration study discovered 36 copper anomalies within two of its eight northern Botswana licences, organised into six exploration corridors.
The licences are situated in an under-explored geological corridor connecting Namibia’s Damara Belt with Zambia and the Democratic Republic of Congo’s (DRC) Central African Copperbelt, both key copper regions in Africa.
The identified anomalies exhibit geological traits similar to major existing and historic deposits.
Botswana Minerals plans to commence initial fieldwork within three months.
It will refine and prioritise the 36 identified target areas, develop field programmes for key corridors and plan the next stage of exploration based on the integrated target inventory.
The company plans to make further announcements in due course.
The assessment utilised Planetary AI’s Xplore platform, combining machine learning (ML) with expert geological insights to identify areas from comprehensive datasets.
This included geological mapping, structural and geophysical data, geochemistry and remote sensing.
Geological features indicate potential for sediment-hosted and structurally controlled mineralisation, as well as iron oxide copper gold-style systems.
The targets share similarities with major deposits such as Kamoa-Kakula in the DRC and Tsumeb in Namibia.
Botswana Minerals chairman John Teeling said: “There is no doubt that AI techniques are revolutionising identification of mineral targets. The ongoing analysis of our huge database continues to provide outstanding results.
“The analysis uses data from copper mines around the world to identify areas with similar geological characteristics, with the next step to rank these anomalies to better focus future fieldwork and any subsequent drilling decisions. This involves deeper AI analysis to support targeted fieldwork.”
“Botswana Minerals’ AI study uncovers 36 copper anomalies” was originally created and published by Mining Technology, a GlobalData owned brand.
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