Key Takeaways
- Tailings management has become its own specialized AI category following several high-profile dam failures.
- GroundProbe (Orica) combines radar, including its SSR-SARx synthetic-aperture radar built for tailings, with piezometers and drone imagery in one dashboard.
- Insight Terra and similar platforms add satellite InSAR deformation data, extending coverage to areas without ground sensors.
- The genuinely AI part is using ML to separate benign, expected consolidation settlement from the shear deformation that precedes a failure.
TL;DR
AI tailings management means running the facility from one data platform instead of scattered spreadsheets and reports. Bring radar, piezometer, InSAR and survey data into a single system such as GroundProbe’s MonitorIQ Next or Insight Terra. Then let its ML models flag abnormal deformation, and tie every alert to a clear response plan.
What Is Tailings Management?
A tailings storage facility holds the fine waste left after processing. It is not built once and left alone. Most facilities grow in stages, with new embankment raises as the mine produces more tailings. They also need care for decades after the mine closes.
Tailings management covers that whole life. It includes design, construction of each raise, deposition planning, water control, monitoring, inspections and closure. Since 2020, the Global Industry Standard on Tailings Management (GISTM) has set the benchmark. It asks operators to manage each facility across its entire life, with clear accountability and monitoring suited to its risk. In practice, that turns tailings management into a data management problem as much as an engineering one.
How Do I Manage Tailings Dams With AI?
The core idea is data fusion. No single sensor type tells the whole story, so the leading platforms stitch several together and keep the record for the facility’s life.
Building one data platform for tailings management
GroundProbe, now part of Orica, is the incumbent. Its slope stability radar line includes the SSR-SARx, a long-range synthetic-aperture radar built for tailings dams. Data feeds into the MonitorIQ Next analysis platform, alongside piezometers and drone photogrammetry. Competing products worth evaluating include Birdi and continued build-out from Worldsensing. The aim is one system of record, not a separate dashboard per sensor.
Adding satellite coverage across the facility
The newer piece is satellite coverage. Insight Terra, a London-based platform, partnered with SAR satellite operator Synspective. Together they add InSAR ground-deformation detection to Insight Terra’s cloud IoT platform. As a result, you can watch parts of a facility that lack ground sensors, or where sensors are hard to install.
Turning data into decisions
What makes this AI-relevant, rather than just more sensors, is the detection layer. The software must tell the gradual, expected consolidation settlement of a new facility apart from the accelerating shear deformation that has historically preceded failures. That is a pattern-recognition problem, not a simple threshold. Configure alerts around the platform’s ML classification rather than raw displacement numbers. Then link each alert level to a documented response, so everyone knows who acts and how fast.
How AI Supports Tailings Management Across the Facility Life
Setup is an integration project more than a modelling project. First, instrument the dam or verify existing instruments. Next, subscribe to a satellite InSAR feed if you want wider coverage. Finally, connect the platform to your engineering records, so each reading sits beside the design it tests.
Management goes further than the sensors used for tailings dam monitoring.
For example, upstream thickening controls how much water goes to the facility. Downstream, water quality monitoring tracks seepage leaving it. A long, clean data record also makes closure planning and audits far easier.
FAQs
What does tailings management include?
It includes facility design, construction of each embankment raise, tailings deposition, water balance, monitoring, inspection, emergency planning and closure. Under GISTM, operators must manage all of these across the facility’s whole life. Good data management ties the pieces together.
How does AI help tailings management?
AI brings radar, piezometer, satellite and survey data into one view and watches it continuously. Its main job is to separate normal settlement from deformation that signals a developing problem. That lets engineers focus on real risks instead of sifting through raw data.
What is GISTM in tailings management?
GISTM is the Global Industry Standard on Tailings Management, released in 2020 after the Brumadinho disaster in Brazil. It sets requirements for the design, operation, monitoring and closure of tailings facilities. It pushes operators toward continuous, auditable monitoring and clear accountability.
Which platforms support AI tailings management?
GroundProbe’s MonitorIQ Next combines radar, piezometers and drone data. Insight Terra adds satellite InSAR through its partnership with Synspective. Birdi and Worldsensing are also worth evaluating, depending on your sensors and budget.
Try It With Geocluster
Fusing radar, piezometer, InSAR and geological model data into one coherent picture of dam behaviour is a multi-source geoscience reasoning problem. Geocluster is designed to support exactly that. It is worth a look if you want to connect tailings data back to your geological and geotechnical models, or read how the Geocluster Research Harness works.