Subsurface Void Detection

Acknowledgements

Project Advisor: Prof. Robin Bullock

Technical Advisor: Dr. Hugh Miller

With Help from: Center for Wave Phenomena, Dr. Jeffrey Shragge, Jihyun Yang, Aleksie Titov

Video

Elevator Pitch

Mining for coal, metals, and other natural resources is an ancient human practice that has occurred around the world for millennia. As technology has improved, mining techniques have adapted. In the last 30-40 years, many historic mines have been converted from underground to open pit. Open-pit mining allows for more efficient resource extraction, but one of the challenges encountered has been the frequent and sudden collapse of portions of the mining floor due to subsurface voids. Subsurface voids in this context arise primarily from underground mines that were poorly back-filled or abandoned entirely. Shock waves from blast-hole drilling can further aggravate loose sediment, leading to void formation.This motivates the need for a subsurface void detection system.

Design Approach

Design Solution

For the final design solution, we created a decision matrix of all subsurface void detection systems that we researched. We included probe drilling as a basis for the rest of the ratings.

It’s fun to note that of all the methods we surveyed, the best, most accurate way to detect a hole in the ground is to dig for it and look. For all of its benefits though, probe drilling is stilled tied with GPR, which can provide more complete information about the depth and shape of the void and requires less intense labor.

Autonomous Drones and Robots

Autonomous drones and robots tied for second place after GPR. Recent improvements in these devices like extended battery life and payload capacity have popularized them as exploratory devices. Drones and robots can navigate difficult terrain and go where humans can’t, or where it would be inconvenient or impossible to trench cables or push a GPR device. Besides providing direct results in the form of videos and pictures, many autonomous robots also have a suite of add-ons that possess additional sensing and imaging capabilities. Spot from Boston Dynamics already has a LiDAR add-on. There are still some obstacles. Robots and drones can easily become stuck and irretrievable. They can also be damaged from exposure to fluids and gasses. Despite the present limitations, drones and robots are making rapid strides in terms of their technical capabilities and are presently the future of subsurface void detection. 

Testing the Terra Treble15 Fiber Optic DAS System

This semester, our team had the exciting opportunity to collaborate with the Colorado School of Mines Center for Wave Phenomena to test a hybrid fiber-optic DAS system at the Edgar Research Mine in Idaho Springs. Remote wave sensing systems are prone to unreliable measurements, long recording/processing times, and often require complicated imaging techniques to fully utilize. Data quality often depends on a successful coupling system, the demands on which are environment-specific. Despite the current shortcomings of remote sensing systems, improvements in precision sensor technology and integrated photonics is paving the way for devices with more sophisticated sensing capabilities. Although fiber-optic DAS came in 8th place in our decision matrix, we recognized it as a promising technology that has the potential to dramatically improve in the coming years.

We trenched nearly 300m of single-mode Kevlar strength fiber optic cable across two roads joined by a switchback above the mine entrance. We struck the ground near the cable with a sledgehammer every 5m and recorded the acoustic back scatter with the Terra Treble15 DAS, keeping a log of the location and time stamp of all strikes. We segmented the data into 50 second snapshots using python, which came out to approximately 4GB of image data. We did not perform image processing to verify the presence of the void, but hope that the data can be used in future projects.

Next Steps

Based on the work done over the past two semesters, we present three paths forward that we consider the most viable and worth pursuing.

1. DAS Software Development

We believe there is merit in a senior design project to develop DAS software with a user-friendly GUI that runs specialized DSP algorithms on the data in real-time, specifically for the application of subsurface void detection. An out-of-the-box solution like this would lower the education threshold necessary to use the software and increase speed of data collection. Furthermore, because remote sensing systems are most appropriate for long-term monitoring, the steady long-term influx of image data suggests that artificial intelligence (which has recently seen huge advancements in the computer vision field) could be particularly fruitful in helping to rapidly advance the accuracy of remote sensing systems.

2. Rapid DAS Deployment System

One of the biggest obstacles to our testing efforts at Edgar was how much time it took to trench and bury the cables. We investigated the possibility of using a ditch witch, but found it could be impractical in very rocky environments. We believe the development of a rapid deployment system for use in an open pit mine specifically could go a long way in reducing labor and set-up time and keeping the mine operational with minimal breaks in work.

3. Further Research into Drones and Robots as Sensing Platforms

Drones and robots are making rapid strides in terms of their technical capabilities and are presently the future of subsurface void detection. There are still obstacles to overcome in terms of battery life, payload, and water resistance, and we highly encourage a project geared toward solving one of these or a related problem.

Meet the Team