Sunday, June 30, 2019

lherzolite: A New Diamond Indicator Mineral

The discovery of a new source-rock indicator for diamond formation has the potential to help geologists locate and identify valuable diamond deposits around the world, a study by the University of Alberta and De Beers shows. 

“The outcome of the project fundamentally changes our understanding of where diamonds come from,” Thomas Stachel, a University of Alberta geologist and the Canadian research chair for diamonds, was quoted as saying in an online article published by Phys.org. “[It] has the potential to cause diamond companies to retool their approach to exploration.” 

Geologists at Canada’s University of Alberta studied a sample of 116 diamonds from De Beers’ Victor mine in Ontario. The goal was to characterize the sample’s mineral inclusions and identify any that could be age-dated using their isotopic compositions, which could serve as indicator materials for kimberlite. 

Of the stones tested, 99 showed garnet inclusions, a typical indicator for diamonds. However, 85% of those garnet samples were found to be lherzolite, a peridotitic rock that had previously been discovered around diamond areas, but had been considered unimportant. 

“This makes Victor the first significant diamond mine in the world that extracts a predominantly lherzolite-derived diamond production,” the study notes. 

Lherzolite rock has been identified in other areas of Canada, including Buffalo Head Hills in Alberta and the Saskatchewan region, Tom Ormsby, head of external and corporate affairs for De Beers Canada, told Rapaport News Tuesday. It is also found at mining sites such as Ellendale in Western Australia and De Beers’ Venetia in South Africa, according to the study. 

“In the long run, this could make a big difference in diamond exploration,” Stachel explains. 

The University of Alberta is also studying inclusions from De Beers’ Snap Lake and Gahcho Kué mines in Canada that will enable them to identify and separate “barren” lherzolite from the diamondiferous kind using machine learning, Ormsby added. 

Many thanks to Rapaport.

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