University of Alberta on Non-destructive Multi-Sensor Core Logging for Permafrost Cores

University of Alberta on Non-destructive Multi-Sensor Core Logging for Permafrost Cores

The University of Alberta’s Permafrost ArChive Science (PACS) Laboratory is the first of its kind in Canada. As a formal permafrost archive and analytical lab, the PACS lab provides researchers with a state-of-the-art facility to develop the best methods for data capture, and gain understanding of climatic and environmental change in permafrost regions. In 2020, an MSCL-S was installed for non-destructive analysis to protect the state of the permafrost cores.

To see how the MSCL-S has been used since its installation, we spoke with Joel Pumple, PACS Lab Manager, and specifically about his latest paper ‘Non-destructive multi-sensor core logging allows rapid imaging, measurement of bulk density and estimation of ice content in permafrost cores.’ Joel works on everything from machine maintenance to project management of the lab. Mainly, the lab is used for methodology based projects, pushing the boundaries of its instruments to perform in applications they haven’t previously.

Working with Sub 0° C Core

Q: Could you tell us a about working with permafrost?

One of the big sides of our research is we deal with thaw sensitive material. If the material thaws, a lot of the data which we hope to capture is compromised. It all starts to change when material approaches 0° C.

We want to capture all the data from core in its frozen state, so that we have a digital archive, and can keep the core for future studies that might require a more destructive approach.

Q: How does the MSCL-S fit into your research?
MSCL-S in the PACS Laboratory

MSCL-S in the PACS Laboratory. Credit: University of Alberta

So it’s the first step in one of our methods, where we’re trying to show how we can collect data from permafrost cores in a non-destructive manner. We’re illustrating that the MSCL can collect non-destructive data from these frozen cores, what that data is, and how that data is useful to us. We’ve taken gamma density, getting bulk density from the gamma sensor, the magnetic susceptibility, and high-resolution imagery, and shown that with those three data sets, we can compare results to a destructive approach that we use and collect volumetric ice content and bulk density, which are two very important attributes in in permafrost.

We’re working on how to extrapolate that to excess ice, which is arguably one of the more important physical attributes of permafrost when it comes to infrastructure development or climate change as well. The main thing is illustrating how this machine allows permafrost scientists or people working on thaw sensitive material to collect data non-destructively, identify what that data means, and why it’s useful.

Q: Was the core throughput affected by the thaw sensitive nature of the samples?

This machine has a huge throughput. If you’re really pushing it and wanted to run all day, you can get through a huge amount of material, which is really one of the big things we wanted to say and it’s in the title, is that it provides a rapid method relative to existing destructive methods.

It truly is a rapid method for non-destructive approach. The amount of time you spend to cut up a core and find and collect all the same data that we’re getting by just passing the core under these sensors, it really is a fast approach. The huge benefit you have to consider is the core you’re collecting this data from is not compromised, it’s still in your freezer for future use. This retention of physical material is an important aspect of this non-destructive approached covered in the paper.

Destructive Vs Non-Destructive

Q: How do you think this style of MSCL scanning compares to conventional techniques of analysis, like destructive techniques?
Images of the cuboid method as implemented for this study.

Images of the cuboid method as implemented for this study. Credit: University of Alberta

This paper does a direct comparison with destructive analysis. We’re a bit biased, but we compared with a method we developed that’s destructive and has really good constraints on the physical volume of the sample. We call it the Cuboid Method. We basically take a chunk of frozen material and cut it into a cuboid, measure it with digital callipers, and weigh it with an accurate scale. And so, we’re getting really solid bulk density, volumetric ice content, gravimetric moisture content out of it, what you would consider to be the best, most accurate data for this style of data collection.

We went for the half centimetre resolution using the half a centimetre aperture, so a pretty fine resolution. The cuboid, because of the physical sampling, is restricted to about two centimetres. We point out that a lot of the discrepancies can be tied to the difference in resolution because if you average the whole core, these two datasets look really good. They really line up on top of each other.

Multi-Sensor Core Logging for Digital Archiving

Q: Beyond the research presented in your paper, how are you using the MSCL system?

Generally, we have a process that involves cutting the core in half, running it through the MSCL-S regardless of what we’re going to be doing with it. Then, we have that digital archive, and again, one of the points we’re pushing in the paper is that this machine will aid in the development of a digital archive, which is a critical component of digital infrastructure for the future.

When it comes to future climate studies or infrastructure studies, you can imagine if you’ve cored a thousand boreholes in the Canadian North it costs a huge amount of money to collect the physical cores. If you just did some primitive studies on the side of the road and let them thaw, collect some data scribbled on paper, and that’s all you have from those hundreds of thousands of dollars you spent on coring, it’s not really that useful.

That’s mostly what we deal with when it comes to trying to build a national or regional scale permafrost map, or more local products for infrastructure projects. It’s not the best data quality, so one of the things we’re pushing is this machine can allow you to collect a high-resolution digital archive of these materials

Q: One of the applications mentioned is the visualisation of cryo-structures. Could you elaborate on how MSCL helps in visualising these structures within permafrost cores?

A lot of that comes down to us understanding the sensitivity of the focal length. So the 50 mm cannon lens that’s on there is a pretty tight focal length. We had to have our core sitting just right. We did have a struggle with the imagery taking the cores from the -25° C storage and putting them straight on the scanner for imagery. That contrast in temperature started to collect frost on the surface of the core because the humidity in the air was attracted to the core. What we ended up doing was putting the core in a -7° C or -5° C chest freezer and then take it to do the imagery which eliminated this frosting habit. So, with a clean image without that issue, the maximum resolution to 25 µm, I believe our resolution allowed us to visualise most of the visible ice. We’re still developing methods on this machine to expand it even more from a non-destructive approach, but hopefully be able to extract excess ice as well.

Q: Have you been able to use the MSCL beyond its intended purpose?
Image of a core highlighting the destructive subsample (cuboid) locations (in black) relative to the non-destructive data paths of the MSCL transects.

Image of a core highlighting the destructive subsample (cuboid) locations (in black) relative to the non-destructive data paths of the MSCL transects. Credit: University of Alberta

We’ve expanded the application of the MSCL by using the other estimations, or let’s say non direct estimations, from the direct parameters taken from the MSCL. With the direct parameters from the MSCL we can start expanding that database too, combining it with some equations from other research and find some new parameters.

In this paper, we took the data from it and used an equation from another publication to actually push that data to collect even more non-destructive information. And so just looking at the machine for what it produces and stopping there, you’re not doing yourself any favours. We have at least one, if not two more publications where the MSCL will play an important role, providing some integral data, whether it’s comparing datasets, extrapolating data, or even using imagery to pull out more data via some other software.

Data Without Compromise

The non-destructive analysis the University of Alberta have been able to acquire has been instrumental in developing a digital archive of the permafrost core. Using the MSCL-S, they’ve been able to gather valuable insights whilst preserving the integrity of their sample, keeping it whole for future analysis. The paper is a brilliant illustration of how alternative techniques to conventional can still provide you with high resolution data, which can also be used for estimations for further interpretations, with the added benefit of preserving the core. Thank you to Joel, as well as Mahya Roustai, Permafrost Scientist at the University of Alberta, for providing us with such interesting and detailed insights into not only how they have applied the MSCL to their research, but also into the intricacies of working with permafrost.

To read the full paper, follow the link: