A new imaging technique in use at the University of Alberta may lead to faster identification of minerals in drill samples, which could improve extraction of bitumen from the oilsands and assist in reclaiming former tailings ponds.
Professor Benoit Rivard is working with mechanical engineer Mike Lipsett to test and adapt a device that measures the content of drill samples by examining the amount of reflected light they give off.
“Geologists and engineers try to extract as much information as they can from these drill cores to do an assessment of their properties — in the case of the oilsands operations, to figure out where they’re going to mine, to figure out what the reserves (of oil) are,” Rivard explained.
The lab contains two different machines to maximize identification of a variety of minerals, including bitumen, quartz, and clay — important because of the complications it presents to the oil extraction process.
“We can look at the bitumen abundance in these cores and get a sense of how it’s variable. We can see the signature of quartz, we can see the signature of clay as a group,” Rivard said.
“All of this is useful because the clay tends to reside in the sandy layers (and) is detrimental to the extraction of the oil ... So if we’re able to detect the presence of the clay, that would be useful. And right now, qualitatively, we can see the clay.”
The mechanism by which these machines can be used to detect certain minerals is examination of drill samples under a wide range of wavelengths.
Depending on samples’ interaction with the light, researchers can make conclusions about the mineral content of the samples.
“These cameras look at many regions of the spectrum, about a thousand different regions. We’re looking at a thousand colours, if you wish. The core would be translated automatically on this table and passed in front of the cameras and the light sources, and we measure the intensity of the light that’s reflected.”
The result is an image that contains detailed information of the reflectance and absorption of light at these different wavelengths in every pixel, obtained in minutes.
The interpretation of all the data contained in the image is a challenge in itself, but Rivard’s team is optimistic this method will result in a quick and quantitative means of identifying minerals in drill samples.
“In the area of field data collection, it could be a real game-changer for people who are trying to make good decisions with not a lot of time,” Lipsett said.
One application that Lipsett is working on is the use of rovers that could drive out over tailings pond land that is too difficult for humans to access directly.
Such land requires time to densify enough for the reclamation process to progress, as it starts off as material comparable to quicksand. Solving such problems is a long process that begins in the lab, but ends with innovative applications.
“We’ve been collaborating for the last few years, and we’ve been working with a number of students,” Lipsett said. “(The work) ranges from some of the very basic investigations around how some of the different properties of the samples show up in the spectra, as well as how these would systems actually be used, all the way up to the robotics solutions that could be part of the future.
“This kind of technology development — the combination of science and engineering research — is really important.”
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