Use Cases
Subsurface Sensing and Geological AI Intelligence
Browse grouped use cases within Subsurface Sensing and Geological AI Intelligence.
Use Cases
Implementation scope and rollout planning
Clear next-step recommendation
Use RF-based sensing and physics-informed AI models to identify high-potential mineral deposits with 90% less land disturbance, accelerating exploration and reducing capital risk.
Deploy continuous AI analysis of sensor data to predict dam failures weeks in advance, preventing catastrophic environmental liabilities and ensuring regulatory compliance.
Continuously analyze geotechnical data with AI to forecast slope failures, enabling proactive intervention that reduces unplanned downtime and protects worker safety.
Instantly analyze core samples and geophysical logs with AI to deliver accurate lithology and grade estimates, slashing analysis time from weeks to hours.
Dynamically plan and adjust drilling paths in real-time using subsurface AI models, maximizing ore recovery while minimizing costly deviations and equipment wear.
Model and predict the migration of contaminant plumes in real-time with AI, enabling faster, more effective containment strategies and reducing remediation costs.
Anticipate water ingress into mines and tunnels using AI-driven hydrological models, allowing for safer dewatering plans and avoiding costly project delays.
Use AI to rapidly identify geological discontinuities from seismic and survey data, de-risking excavation projects and optimizing underground mine design.
Continuously update mineral resource models with new drilling data via AI, providing a real-time, accurate view of reserves to inform extraction and financial planning.
Rank and score exploration prospects by synthesizing vast geological datasets with AI, focusing capital on the highest-probability, highest-value targets.
Use RF and sensor fusion with AI to create live 3D maps of voids and stopes, enhancing safety for personnel and equipment in complex underground operations.
Forecast the generation of acidic drainage from waste rock using AI, enabling pre-emptive mitigation that lowers long-term environmental liability and treatment costs.
Assess ground conditions and predict geohazards like rockfalls or subsidence in real-time at active work faces, enabling immediate safety interventions.
Safely identify and map unstable workings and voids in abandoned mines using AI analysis of historical and modern survey data, preventing surface subsidence and enabling safe redevelopment.