SensOre says iChromite automated mineral chemistry tool will boost diamond and nickel exploration

Posted by Paul Moore on 16th December 2022

Geoscience technology innovator SensOre Ltd has announced the launch of iChromite, a new suite of automated mineral chemistry assessment tools it has developed that it says can identify exploration targets more efficiently and accurately. “The mineral chromite is extremely stable in highly weathered environments. It preserves its unique geochemical fingerprint over geological time and thus has great utility for reliable detection of potential mineralisation and fertility.“

iChromite it says uses new and highly innovative data processing techniques integrated with machine learning tools delivered from an agile accelerated program. “The SensOre geochemical technology team has delivered the new tool suite from the first phase of a comprehensive research program directed at improving the fidelity of mineral chemistry. When the new tool is applied to the mineral chemistry of chromite, an important resistate heavy mineral sample, it can quickly aid in the rapid assessment of fertility, a key ingredient in generating new exploration targets for mineral discovery.“

Importantly, the new technology workflow can be used to rapidly analyse the vast quantity of legacy industry chromite geochemical databases collected from across Australia (and the world) over many decades. “Application of this technique will unlock value from in field sample collections and analysis currently concealed in mining and exploration company databases, which represents millions of dollars of previous investment.“

SensOre CEO Richard Taylor said: “As mineral exploration increasingly focusses on a new generation of targets to deliver mines of the future required to meet the world’s increasing demand for critical minerals, the industry is moving into more remote projects and deeper targets. Consequently, this shift has brought back into focus the role of resistate mineral geochemistry in early–stage exploration programs. Aided by new machine learning tools such as iChromite, the technique is potentially undergoing a revolution or new dawn in greenfield exploration.”

Major cited benefits of iChromite application to geochemical ‘Big Data’:

  • Rapidly and cost effectively process and classify vast quantities of historical chromite mineral chemistry data collected over many decades by industry
  • Identify the unique geochemical fingerprints of chromites with high confidence – iChromite considers 14 elements simultaneously in the classification process compared to more traditional methods which commonly assess two or three elements at a time
  • Provide important geological information such as age and paleo–tectonic environment.
SensOre’s development of iChromite it says significantly improves on the application of chromite as a kimberlitic indicator mineral (KIMS) as a vector to the presence of rocks such as kimberlites and lamproites and its use as a vector to nickel and copper, namely komatiitic–magmatic Ni and mafic/ultramafic–hosted V–Cr–PGE mineralisation.

SensOre’s steps in developing the new technology:

  • Compilation, cleaning, labelling and data imputation of global mineral geochemistry database + 1.5 million sample records
  • Advanced text–mining applied to attached textural information and SensOre’s adjacency modelling (SAM) utilised to identify individual samples coincident with, or proximal to, significant economic mineralisation for 24 different deposit types using our global metallogenic databases
  • State–of–the-art unsupervised learning workflow (SimClust™) applied to chromite chemistry to automatically generate highly discrete populations in the data in 14 element space
Application of SimClust™ technology resulted in identification of highly discrete populations that are observed to coincide with chromites derived from komatiite and magmatic Ni and V–Cr–PGE ore deposits in addition to diamond–bearing kimberlites leading to development of iChromite. SensOre says it is continuing development to apply its SimClust™ technology to other minerals including porphyry indicator minerals to assist with porphyry target assessment and vectoring. “The new mineral datasets will allow SensOre to provide an advanced suite of machine learning tools, like iChromite, that can be applied to the SensOre data cube to be utilised in its own exploration programmes and by clients on their own data in SensOre’s Solution as a Service (SOLAAS) targeting services.”