Our vehicle, handheld, and unmanned systems enable data to be collected rapidly in development areas without interrupting activity or risking the safety of personnel. Comparing the as-built to the as-design provides a detailed over-under-break analysis and identified areas outside of tolerances.

A heading can be scanned within minutes using LIDAR. Operators are able to capture data shortly after firing, before other development activities commence. Detailed point cloud data provides development shapes that enable development pickups. LIDAR data can also be used for more detailed analytics, such as calculating moved material volumes, bulking factors, and reconciliation.

Comparing pre- and post-blast scans can determine the in-situ rock volume, the post-blast bulked volume and the bulking factor.

To maintain a safe working environment in any underground operation, accurate monitoring of ground support is essential. SLAM LIDAR scans, captured by walking, vehicle, or flight, provide insights that are superior to those obtained from broad scale observational mapping or traditional extensometer readings.

Data accuracy is sufficient to identify changes exceeding 5 mm. Rapid scanning methods enable data collection to occur at regular intervals. This leads to improved recognition of convergence trends and closure rates. As a result, residual capacity can be estimated more accurately, and rehabilitation schedules optimized accordingly.

Our LIDAR high resolution point clouds are compatible with automated structural recognition programs, such as Maptek PointStudio, Sirovision and CloudCompare, the popular open-source point cloud analytics software.

In this example, the identified structures have sufficient scale to control the drive profile. More comprehensive characterization of the rock mass would include window mapping to identify other potential contributing factors.

LIDAR can be used to record the void, structures, and ground support, prior to shotcrete application. This data can provide a baseline for future analysis and audits.
Conducting a second scan of the surface after shotcrete has been applied allows engineers to determine whether the application is within specification and matches the invoiced volume. This second scan can also be used as a baseline for detecting damage or movement in the shotcrete after development activities commence.

By contrast, traditional methods, which rely on drilling and measuring widely spaced depth holes, are time-consuming and inaccurate.

TruNorthe drones can function with an autonomous, beyond line-of-sight flight allowing them to safely enter and scan areas of high geotechnical risk, such as failed headings.

Personnel can use the captured data to assess the conditions and develop job hazard analyses and safe re-entry plans.

LIDAR can be used to record the void, structures, and ground support, prior to shotcrete application. This data can provide a baseline for future analysis and audits.
Conducting a second scan of the surface after shotcrete has been applied allows engineers to determine whether the application is within specification and matches the invoiced volume. This second scan can also be used as a baseline for detecting damage or movement in the shotcrete after development activities commence.

By contrast, traditional methods, which rely on drilling and measuring widely spaced depth holes, are time-consuming and inaccurate.

After a significant geotechnical event, assessing the area and developing a rehabilitation plan to make it safe to re-enter is a priority for mine owners.

Drone based LIDAR can be deployed to scan the area, without putting personnel at risk. Captured data can be used to produce visualizations, calculate the volume and surface area of the collapse, and determine whether adequate pillars remain. It can also form a baseline for deformation analysis, predicting future falls-of-ground and convergence activity.

All of this can be safely accomplished in a completely blacked out environment.

Abandoned mines are now being reassessed for recommencement, due to price increases in some commodities. Typically, these old mines have substandard ground support, which has further deteriorated over time.

Sending in an autonomous drone to capture data reduces the unknowns, by allowing engineers to complete a comprehensive risk assessment safely. They can assess the rock mass and structural conditions to identify and mitigate hazards before personnel enter the area.

LIDAR can capture built environment in a flight or walking scans and all without additional light sources. Accurate and detailed as-built point clouds can be transformed into CAD plans of complex 3D structures quickly and easily.

Comparing consecutive scans allows engineers to detect whether changes have occurred between scans.

Drone and robotic LIDAR can deliver high resolution stope shape point clouds with uniform point density and minimal shadowing. Accurate stope data can improve mine efficiency by allowing drill and blast engineers to see how their initial drill pattern has performed. Subsequent patterns can be refined, to maximize ore body extraction, and improve material flow.

Our LIDAR delivers high quality point cloud data can enable geologists to analyze the final stope more accurately. Data can be used to reconcile production tonnes, quantify over and under-break and inform depletion modelling. Having access to accurate data makes it possible to quantify the expected grade of the stope with greater confidence and ensure material has gone to the correct ROM stockpile. In collaboration with the mill metallurgy, geologists can ensure target grades are blended and variability in EOM reconciliation is reduced.

Using SLAM LIDAR to scan a stope at regular intervals during the extraction process can help to build a richer understanding of blast performance. Comparing scans over time makes it possible to identify emerging issues, such as fragmentation and over-break, that may affect the mucking rate or impact adjacent stopes.

Having access to this library of data allows engineers to compare extraction progress with the schedule and adjust downstream activities accordingly, thereby averting the complications and cost of equipment stand down.

The value extracted from a stope is one of the key metrics for an underground operation. Using drone mounted LIDAR to scan stopes regularly can help to maximize this value.

Because of the precision and density of LIDAR point clouds, geotechnical engineers can conduct detailed back analysis on failures, identify the geotechnical mechanisms responsible for over and under-break with a high degree of confidence, and adjust their method to minimize the likelihood of re-occurrence.

Our accurate, high-resolution LIDAR point cloud data can allow geotechnical engineers to identify structural traces and planes with greater confidence. Structural characteristics, such as dip and azimuth, persistence, roughness, and spacing of features can be extracted and used for rock mass characterization and design purposes.

Stoping relies on the stability of large un-supported walls so identifying structural features that may affect current and future stoping performance can improve stope economics.

Traditional scanning methods have not allowed this level of detailed analysis.

LIDAR scans can be used to monitor backfill heights and ensure backfill types are installed correctly. Rather than relying on bucket counts, schedulers are able to obtain an accurate measure of remaining stope volumes and can direct material accordingly.

LIDAR scans can enable surveyors to maintain highly accurate void models. This is a statutory requirement for underground mines in many jurisdictions. Traditional CMS void modelling methods typically result in gaps in the data and this may expose surveyors to legal risk, in the event of an incident. Moreover, having accurate, high resolution spatial models of stopes limits the need for other technical teams to conduct their own inspections.

In the event of brow failure, drone or dismounted scans can be used to create a comprehensive picture of the affected area and extract detailed measurements of the damage. Engineers can use this intelligence to determine whether the area should be rehabilitated or abandoned. Traditional CMS methods cannot provide this level of clarity and obtaining the scans can put operators and equipment at risk.

LIDAR scans can provide engineers with superior insight into oversize material and hang-ups at drawpoints, in stoping and caving mines. These phenomena pose a safety hazard to personnel and to the equipment used to clear them. Flown or attached to a loader LiDAR’s range and wide field of view capture can enable it to deliver scans which provide a better perspective of the blockage than those obtained via traditional CMS methods.

Orepasses and vent raises are essential but expensive infrastructure in underground mines. To maintain safe and efficient operations, mining and geotechnical engineers need to understand the effect of mining-induced and tectonic stresses on orepasses and vent raises. The traditional data collection process, involving C-ALS scanners and the drilling of inspection holes, produces incomplete, low-resolution scans of raises. It is time-consuming and expensive and very often not undertaken until significant failure has occurred.

By contrast, LiDAR scanning is cost effective, typically accounting for less than 1% of the raise bore/orepass excavation cost. It is also extremely efficient. For example, a 100 m (110 yd) raise can be scanned by drone platform in around 20 minutes.

These systems can be drone mounted or even lowered by existing winch or crane to scan longer features.

Ventilation is a critical component of any underground mine. LIDAR can scan vents easily and economically: by flight when the diameter of the vent is greater than four meters, and mounted in a protective cage and lowered on a tether when it is less than four meters.

Using our SLAM LIDAR system engineers can quickly create as-builts of ventilation systems, for comparison with the original construction specifications. Stress induced damage can be easily identified, and this intelligence can enhance geologists’ understanding of the deformation.

Maintaining the structural integrity of orepasses helps mine operators meet production targets. Regular inspections enable engineers to detect changes, deformation and blockages promptly, and to ensure no undercut is present at the tip head location. Lowered in a cage the SLAM LIDAR can scan orepasses hundreds of meters in length, quickly and easily, and produce accurate condition data that can be used to inform remediation decisions.

A raise must be inspected once reaming has occurred, to prepare for shotcrete lining, create a baseline for further inspections and to ensure it has been constructed to specification. Using the protective cage or drone attached units the LIDAR can be used to capture data to produce as-builts and condition reports quickly and economically.

By contrast, inspecting a raisebore using traditional CMS scanning methods is difficult and expensive.

Old vertical infrastructure frequently lacks technical drawings or as-builts. The protective cage system or drone can be used to conduct condition inspections safely. The data captured can be used by engineers to identify hazards and inform remedial planning.

In underground mines, geological features, such as fractures, faults, lithology changes, mining stress and tectonic stress, can contribute to changes in rock mass behavior. Monitoring deformation and failure in raises, and determining whether remediation is required or cost effective, is a perennial challenge.

Analyzing LiDAR data can assist geologists to infer a wide range of geological features and improve their characterization of the rock mass.

This enhanced intelligence can be used to inform management responses.

Local, mine or regional-wide structures can have a significant impact on raise performance. Lowered in a protective cage these same systems can be used to capture high resolution, multi-attribute data, to inform structural analyses of vertical raises and other underground voids. Identifying the structures, using Maptek PointStudio, Sirovision or CloudCompare, that have caused an existing failure can help geotechs assess the potential for more significant failure, and inform back analysis to improve future designs.