Cascade Copper (CSE: CASC) is collaborating with Blockware Technologies of Calgary, Alberta to develop and deploy a field-based data collection and predictive modelling system. This innovative system enhances the identification process and boosts the likelihood of discovering significant mineral deposits. It integrates previous exploration data with newly acquired field data to model and predict mineralization areas within minutes.
Jeffrey Ackert, president and CEO for Cascade Copper, commented: “This technology and application is a real game changer for the junior mineral explorer. We will be able to react immediately to any new data that has been collected and modelled, instead of waiting weeks or months for analysis and then interpretation and then deploy back to the field for follow-up. It will save us time and money, so we are quite anxious to start using this in the field this year.”
Blockware Technology integrates all previous exploration data into a database. This includes airborne magnetic data, airborne EM data, LiDAR, satellite imagery, and ground-sourced data such as soil geochemistry, rock sampling, induced polarization (IP) data, hyperspectral rock/soil data, and geology. The machine learning algorithm then analyzes the dataset, comparing multidimensional associations to identify positive correlations with minerals or metals of interest.
Field crews acquire new data in the field, such as soil or rock sampling data analyzed through portable analytical equipment (pXRF, LIBS, SWiR, and/or NiR). They perform QA/QC protocols on-site to ensure the quality meets required standards. Once the data passes these criteria, the field team sends it to the project’s cloud database for integration and modelling. The system processes the new data immediately, validates it, and delivers predictive updates to the field team for further follow-up.
Andrew Hillson, president of Blockware Technologies, added: “This collaboration with Cascade is helping our team at Blockware step through the challenges that exploration companies encounter, from data collection, to validation, to a timely interpretation with all available site information. Of great interest to us are the massive improvement in timelines, the ability of crews to make informed decisions in the field and our software’s ability to detect valuable anomalies within the large amounts of site data we process. The proliferation of portable analysis equipment and the advancement of AI and machine learning, especially related to the mineral industry, has created the perfect situation for this new solution.”
Blockware’s software suite streamlines data collection and prediction to identify optimal areas for mineralization. Field crews use FieldScanONETM, a software module that actively collects data from various portable instruments and enforces built-in QA/QC processes. Crews often struggle in the field with ensuring proper calibration and accurate usage of equipment, which can lead to compromised data.
FieldScanONETM eliminates these issues by running QA/QC protocols during data acquisition to ensure its reliability. The software then uploads the validated data to the cloud, where the SUBTERROTM service processes it using AI to uncover associations and deliver predictions for locating additional target minerals.
Currently, Blockware has developed the SUBTERROTM service to manage surface data but will unveil a 3D version soon that will incorporate inversion modelled geophysics and drill hole data into the surface-derived data. More information is posted on www.CascadeCopper.com and https://blockware.tech/
