Reading the Rock: Removing the Guesswork from Geotechnical Mapping
Relying solely on visual inspection or physical profiling tapes to assess a dangerous highwall face puts field personnel in high-risk zones and leaves your blast results completely up to chance. A single missed joint plane or miscalculated bedding angle can trigger volatile flyrock liability or excessive oversize rock.
The industry is moving past manual profiling, leading engineering teams are using autonomous computer vision to map site lithology safely from the office.
The Technical Workflow Demonstrated in the Field:
- Drone Ingestion: Capture a high-overlap UAV flight of the active bench face from a safe standoff distance.
- AI Feature Extraction: Toggle on Rock Mass AI during upload to automatically map faults, seams, and bedding structures.
- Blast Design Calibration: Analyze the generated 3D stereonets and 3D burden maps to adjust pattern layouts and explosive loading.
Core Geotechnical Baselines Tracked:
- Facets and Seams: Automatically isolates geology anomalies to prevent explosive energy escaping through hidden joint cracks.
- Dip & Strike Angles: Quantifies rock mass plane tilting to optimize structural pit layout planning and face directions.
- Joint Spacing Metrics: Evaluates the in-situ degree of fracturing to accurately adjust blast fragmentation output models.
Frequently Asked Q&A:
- Q: Why is rock mass structural data critical to the blast loading phase?
- A: Knowing the location of hidden joint planes allows blasters to stem directly through the discontinuities, containing explosive gases and preventing backbreak.
Read the full engineering guide to safely optimize your blast designs: https://blog.strayos.com/rock-mass-ai
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