AI analysis identifies seven new kimberlite

Botswana diamonds identifies 7 new kimberlite targets 

According to the Botswana Diamonds report, their highlights say, Seven significant kimberlite targets have been identified to date that have never been previously reported, one of which is of extremely high interest, in the opinion of the Botswana Diamonds board. The Artificial Intelligence (AI) programme has also revealed compelling polymetallic targets in areas currently unlicensed. 

Chairman, John Teeling, commented: “The identification of seven, previously unreported, anomalies is a major achievement. To discover them in a few short months is a major step forward in mineral exploration. 

Using AI techniques and powerful computing, almost 400,000 kilometres of airborne geophysical and other exploration data has been analysed and evaluated. It is astounding. Botswana Diamonds is extremely fortunate to have such a vast treasure trove of decades of diamond exploration data in Botswana.

I would like to highlight one anomaly which has a signature that outranks all of the others and is of particular interest to the Company. We are long term believers in the diamond prospectivity of Botswana and these results reinforce the belief. We believe more diamond mines will be discovered in Botswana”.  

Botswana Diamonds announces, further to its announcement of 16 August 2024, the preliminary findings of its Artificial Intelligence driven, multi-mineral prospectivity programme. The programme is using the Company’s extensive owned database with other comprehensive open-source databases.  

These databases include over 375,000 kms of airborne geophysical and other data, covering many decades of work in Botswana. Data utilised includes geophysics, geological, structural, geochemistry and satellite data. The purpose is to identify new targets. The Company utilised Planetary AI’s Xplore mineral prospectivity platform to perform the detailed analysis. Initial results identified an exciting number of new and promising targets across much of the country.  

A workflow comprising a combination of AI models was applied in the first instance to understand the data, analyse it and then enrich it. The enriched datasets were then interrogated against Xplore’s proprietary in-house deposit models to identify prospective areas within Botswana in the search for diamonds, but also covered a number of different minerals.  

Seven significant kimberlite targets have been identified to date that have not been previously reported, with one target being identified by the Board of being particularly high interest due to its geological qualities. The AI work also discovered new compelling polymetallic targets in areas currently unlicensed.  

Work is ongoing on these new areas of interest which now focuses on four main deposit types and eleven sub types. These deposit types include elements such as gold, copper, silver, nickel, zinc and PGMs. The Company will now assess these opportunities.