Unlocking mine productivity by changing-the-equation on the where, what and when of orebody characterisation

At its simplest, the classification and characterisation of an orebody is a matter of Where, What and When. Where and with what spatial resolution are measurements taken, What properties are measured, and When are the data acquired, processed, and delivered to create the most value. This paper delves into how existing and near-term advances in measurement technologies, field automation, and whole-system-digitisation are combining to open new routes for mine and exploration productivity improvement. Commencing when the initial exploration hole is dug, the advancement in deployment of survey technology—from expert-operated, to driller-operated, to driller-integrated—is used to demonstrate a template for adoption of higher technology measurements. We then introduce and discuss the multi-use measurement as offering outsized returns from a single measurement run, highlighting two new technologies that acquire rock strength while drilling and downhole assay data as examples. For rock strength, we highlight a novel approach to determining Uniaxial Compressive Strength (UCS) while drilling, its relationship to and advantages over Mechanical Specific Energy (MSE), and how it offers utility to multiple downstream processes. For downhole assay, we detail how a back-tophysics approach to Pulsed Fast and Thermal Neutron Activation (PFTNA) analysis offers significant advantages over other measurement methods and earlier implementations of PFTNA, generating a rich data set that can significantly extend and improve the information on which mining decisions are made. Finally, we discuss the possibilities enabled via optimising data delivery, collection, and curation— noting a fundamental limitation of historical systems and exploring the possibilities that will be unlocked by soon-to-market solutions that better enable Orebody Characterisation data to (virtually) move in space and time with rock material post-blasting. Ultimately, the value of optimising the Where, What, and When from point of measurement to the moment it generates maximum value will create greater life-of-asset production for a lower cost and energy input.