Digital Geology: A Key to improve blast performance
Importance of Rock Mass properties
Rock mass properties have a substantial influence on blasting outcomes. Blasting outcomes including fragmentation is sensitive to geological conditions. Large scale features such as bedding planes, joints, faults, mud or clay seams, and open voids control the explosives performance and fragmentation size.
Implications of geological features on blasting results include imbalance of energy distribution, escape of gases produced during detonation through discontinuities, blast hole cut-offs by differential movement of bedding planes, widening and lengthening of cracks to name a few. Standard design of shots without consideration to geological features results in poor fragmentation and blast damage.
Economic implications of these designs without deliberations of geological features can be high. Furthermore, HAULING and CRUSHING cost escalates with poor fragmentation. Evaluation of geological properties helps gain critical insights for drill and blast planning.
Geological discontinuities detection using drones
Stratus has a novel solution to detect these discontinuities using aerial imagery and machine learning. The methodology involves capturing images of bench face using drones and delineating features of interest on them. A graphical positional information of discontinuities are generated on burden profile report for blasters to utilize in blast design.
Visual bounding box is created on critical features for their identification on 3D model. This approach also integrates the digital layer of geology data into a 3D profile of the bench face. Computer vision and machine learning are used in developing this approach where AI models were trained with an extensive dataset to familiarize it with the geological features. Model testing on drone images has yielded excellent results in terms of detecting the geological features. Overall, this solution could provide the blast design crew with clear information of the discontinuities.
Machine learning as a solution
Machine learning analysis of aerial imagery on bench face can provide detailed information of existing features. Additionally, it is included in the burden profile report to delineate positional information which can be used in the blast design. Stratus’s objective is to help the Mining and Quarry industry generate more value on their drill & blast projects by applying advanced analytics across multiple stages to generate clear, actionable insights for a profitable operations.
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