From Reality Capture to Operational Intelligence: Improving Workforce Performance in Underground Mining
Written by Matthew James, VP of Business Development - Resources at Pointerra
Improving workforce performance in underground mining was the focus of Pointerra’s recent Austmine webinar, where VP Business Development – Resources Matthew James explored a challenge familiar to many mining operations: while underground reality capture has advanced rapidly, the processes for turning that data into actionable information have struggled to keep pace.
Drawing on two real-world Australian case studies, Matthew demonstrated how automating spatial workflows and publishing results through a cloud-native mining digital twin can significantly reduce processing times, improve collaboration and help engineering, survey and operations teams make faster, better-informed decisions.
The Underground Mining Bottleneck Isn’t Just Data Capture
Underground mines are generating more spatial data than ever before. LiDAR, SLAM and other reality capture technologies have made regular scanning part of everyday operations.
The challenge is what happens next. As Matthew explained during the webinar:
“The core issue wasn’t data capture. It was the gap between capture and action, and by the time insight arrived, conditions underground had already moved on.”
At many operations, each scan dataset can require four to six hours of manual post-processing by specialist personnel. With dozens of scans being collected every month, the backlog quickly grows, while operations, engineering and safety teams wait days or even weeks for information needed to support critical decisions.
The result is a disconnect between the speed of data capture and the speed of operational decision-making.
Closing the Gap Between Capture and Action
The webinar showcased how two Australian underground mining operations addressed this challenge using an automated spatial workflow built around a cloud-native digital twin.
One was a Tier 1 underground coal operation focused on gate road profiles and roof bolt quality assurance across more than 600,000 poles and bolts. The second was a hard rock gold operation using SLAM and terrestrial LiDAR to monitor convergence across arched roof roadways. Despite different mining methods and priorities, both operations followed the same underlying workflow.
The process consisted of four key stages:
- Automated classification of ground, roof, walls, ribs, bolts, mesh and services.
- Cross-sectional analysis to compare actual conditions against design profiles.
- Automated compliance checks for roadway dimensions and rock bolt installation.
- Publication of results into a browser-based mining digital twin accessible across the organisation.
Rather than leaving valuable information locked inside specialist desktop software, the workflow makes operational intelligence available to survey, engineering, geotechnical and operations teams through a shared Common Data Environment.
Measurable Improvements in Underground Mining Workflows
For both mining operations, improving workforce performance wasn’t simply about processing scans faster. It was about enabling people across the organisation to spend less time waiting for information and more time acting on it.
The Tier 1 underground coal operation reduced processing from four to six hours per dataset to just 19 minutes, while roadway dimensioning time fell by 80–90%. Automated classification maintained 90–95% accuracy across more than 600,000 poles and bolts, with gate road profiles feeding directly into shearer automation systems and over- and underbreak mapping becoming an automated process rather than a manual one. The operation estimates annual value of between $900,000 and $2 million per site through a combination of time savings, risk reduction and faster operational decisions.
At the hard rock gold operation, convergence monitoring workflows were similarly transformed. Manual processing times of around 2.5 hours per dataset were reduced to between 30 and 60 minutes, while automated cross-sections detected deformation to within 25–50 mm, allowing movement to be identified before it developed into a larger operational issue. Like the coal operation, the site estimated annual value of up to $2 million per year.
As Matthew summarised:“Manual processing measured in hours became automated processing measured in minutes.”
Four Ways Operational Intelligence Improves Underground Performance
Stepping back from the individual case studies, four common themes emerged that demonstrate how operational intelligence contributes to improved workforce performance.
- Design conformance
Automated comparison against design profiles reduced roadway dimensioning time by up to 90%, allowing deviations to be identified much earlier than traditional survey cycles.
- Structural integrity monitoring
Automated convergence analysis consistently detected deformation within 25–50 mm, enabling teams to monitor trends over time instead of relying on manual scan-to-scan comparisons.
- Asset management
More than 600,000 roof bolts and poles were automatically analysed and compared against installation specifications, creating a comprehensive audit trail throughout the life of each heading.
- Safety
Publishing results into a browser-based digital twin reduced the need for routine underground inspections by making more analysis possible from the surface, allowing teams to act on measured data rather than visual estimates.
Get the Right Data in the Right Hands to Help Your Underground Teams
The webinar’s key message extended beyond automation alone. Reality capture technologies have largely solved the challenge of collecting underground data. The greater opportunity now lies in ensuring that information reaches the people making operational decisions quickly enough to influence outcomes.
By transforming reality capture into operational intelligence through automated analytics and cloud-native digital twins, mining organisations can reduce manual processing, improve collaboration between disciplines and provide decision-makers with timely, trusted information across the operation.
If your team is still relying on desktop tools, manual verification, and repeated site visits to manage underground scan data, now is the time to look at a faster, safer alternative. Pointerra3D helps mining operators centralise scan data, automate conformance checks, and give every stakeholder secure browser-based access to the same up-to-date digital twin.
Book a demo to see how cloud-native digital twins can reduce processing time, cut unnecessary underground visits, and improve visibility across your operation. As our workflows are repeatable, we can chat about a small pilot project of one site so you can test the lift in workforce performance for yourself.
