This software uses machine learning and AI technologies to assess all analytical data and deliver insights that others overlook.
Top business benefits
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Maximises drilling data
This solution gathers every shred of drill-hole data and uses it to identify important patterns you may have missed.
Fast and efficient
It works in a matter of minutes, allowing you to harness the power of accurate geoscience data and make strong decisions.
Mitigates risks
The 3D models it constructs are informed by raw numeric drilling data, allowing operators to avoid geotechnical hazards and de-risk the project.
Requires no technical skill
By automating geoscience interpolation and block modelling, it requires no technical knowledge, no software installations, and no hardware.
Reduces exploration costs
This solution replaces the need to invest in expensive 3D modelling software, providing a fast, easy, and cost-effective way of analysing exploration data.
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In more detail
Full description
Mineral resource evaluation requires drilling many boreholes into a targeted mineral deposit, typically yielding thousands of metres of samples necessary to estimate the grade, mineralogy, size, and structure of the deposit. But modern assay results provide a vast array of results beyond the key target and associated mineralogy that geologists are searching for, making the process time-consuming and overcomplicated.
This solution was developed to dramatically improve the identification of patterns specific to drillhole sample data, further enhancing the geologist’s own insights with the use of AI technology.
The challenge
While most mining companies devote significant human and analytical resources to interpreting drill results, they typically do not have the time or resources to interpret all other analytical drill-hole data available, even though this data may contain patterns of great economic value. There will often be tens of thousands of metres of drill core from a single exploration property. Most of a geologist’s time and effort is spent searching for key commodities to build out a JORC or 43-101 compliant ore body.
However, much of the drilled core will not contain these key commodities. Often this waste material’s mineral content is ignored during modelling as it would be too time-consuming to review all the sampling data. But this data, although not directly containing economic minerals, may contain patterns and correlations associated with key metals, which can be overlooked due to the time and cost pressures of exploration.
The approach
This AI-powered mining-specific solution was developed to facilitate the cost-effective discovery of important patterns in mineral exploration drilling data that most mining companies do not have the resources to identify. This solution is able to achieve these objectives by:
Exploiting the speed and memory capacity of modern computers, which enables the AI-powered solution to quickly generate multiple 3D geochemical block models consistent with a single input collection of drilling results but postulating multiple possible anisotropies.
Applying unsupervised machine learning technology to identify anomalous single and/or multi-element geochemical zones of potential economic significance (to exploration, resource evaluation, and/or geo-metallurgy).
