Automated transcript · Written by software from the replay's audio. It can mishear names and figures; the replay is the record.
36:24 that velocity contrast between orange and red. So if we move our way towards the west more and we do it a little faster, what we'll realize is that the core or near the core of the deposit, definitely there is a break here in the velocity contrast and we believe that this here marks the ultramafic unit. So right where we see such a break in the footwall of that contact would therefore be the ultramafic unit And as the nickel sulfide lens is oasted by that ultramafic, it becomes straightforward targets for us, if it's not drilled, obviously.
37:11 So we're still in the core of the deposit here, where we can still see that very sharp velocity contrast. And then all of a sudden we'll reach the end or the Western end of the known portion of the NISQ main. So if we keep looking at the, what's happening here from 1 section to the other that becomes really really really interesting As we will see that contact here where the NISQ main lens is centered at we'll see that contact all of a sudden shifting a little bit further south and sinking down pretty much. So here's that contact and the really sharp switch in location that is happening between that one given section and the other.
38:03 So the interpretation we now have is that there are those series of faults, subsidiary faults that I was related to earlier, that are likely part of that same northeast running structural corridor are definitely impacting the deposit. Is that a bad news? No, not at all, because with the understanding we have now, having incorporated that 3D data set into our system, compared it with structural components and things like that, it just tells us where, well, we believe is the rest of the deposit, or so to speak, the offset portion of that deposit across them faults that we are now identifying quite easily using that data set here.
38:57 So if we were to keep going our way West, then we'll see that that contact still is preserved and at one point may become faint or something or even more pronounced, but no actual geological data in those areas, no drilling, no nothing. So obviously to us it becomes prime target areas that we'll want to test. Not only that, it seems that the profile also shows the same kind of break or signature that we had seen, I'll just go back here, the same signature that we had seen for NISQ main seems to not only repeat itself across Falk but it seems that we're also seeing other breaks like that that could lead to other pods as well or definitely other targets as well.
39:59 So to us that became very very a key data set that I've used quite a bit, actually. And I'm told by the fleet group that I'm probably one of their clients that have used the most that data set. You're the best user, Ken. For a very good reason, because it's super interesting. And what I ended up doing actually is building manually my own interpretation, I guess, of the data. And what I came up with is designing a series of interpreted lines, I guess, that I've built on sections. So, if I show you guys a little bit what I've done here, is based on section view. I'll just recut a section here, just to show you how I've proceeded.
40:53 I've just basically designed rough polylines that are marking where I saw the transition between velocity contrast happening. So that would be for the first layer and then I've done that for the other layers. So we can't really see now but what I'll do is I'll explode the view again and for temporarily I'll get rid of the point set here if I can locate it in my menu. So I'll just add it really, really, no, not even, I'll just close it off. So when we look at those polylines that I've made, there are some views, and when you rotate it in 3D, there are some views that definitely shows breaks in the data set. Like for instance, in here, where you have all of them blue lines pretty much lining up in that in those orientation here, those are definitely the faults that I was referring to earlier. So those relatively low angle faults that are impacting the system. Sorry, sometimes we can't see it.
42:12 So from them lines, what I ended up doing is to simplify our view a little bit more, I ended up creating them surfaces that are representing pretty much what the point set is telling us, like in a summary, if we can say it that way. So when we take time to evaluate and have a look at all of them surfaces together, we will definitely see them breaks happening. Some breaks seems to be cut by others and I do believe that this is telling us a little bit more about the chronology of them structures. So another piece of very very valuable information that we're learning from that data set as well.
43:05 And from those surfaces what I ended up doing actually to ease the pain at looking at the data, because the point set is sometimes very difficult to look at, What I ended up doing here is converting them surfaces or contact into volumes in between the different velocity ranges, thresholds that I've used. So if we were to look at the entire ant model that way, what we would see, and I'm just trying to relocate it in my list here. So what it would be looking like is something like this. So if we start from the bottom, we'd have a couple areas that the velocity is super high and super deep.
43:58 So it's creating those 2 holes, kind of, in the system here. And then if we load the layer just above, so the velocity one notch lower, well, yeah. So then we start seeing a little bit more of the detail about the location of the demotromafic units. And the same thing's going to happen if we were to load up all of them layers one by one to finish with the top top layer. So the advantage of dealing with the data set that way is that now we can cut section and actually have a look through the velocity model in a much more, I'm thinking, better visual way, much easier to see things in there. So what I'll do is I'll just get rid of all of them, little faults, but I'll preserve where NISQ main is on that image.
45:04 And very fast if we were to re-browse again the same data, we would observe the same thing as I just described with that velocity contrast contact here shifting at one point. When we move to the west, shifting a little bit deeper. And if we are to do the same exercise, but then moving east again, towards the end of that data set. What becomes really, really interesting is, we won't lie, we were kind of losing the lens a little bit to the east there. But the thing is, again, we believe that it's a fault cutting across, moving the lens a little bit further east and deeper.
45:55 And the ant profile scan is suggesting that is happening when we look at where the location is of NISQ main here, just right adjacent to that very sharp dipping velocity contrast. And then if we continue moving east, we'll see that is disappearing, but at one point further down the road we do see a little bump down in here with a lot less resolution in that part of the survey. But from what we understand it may mean that in here is the same velocity contrast break that we're looking for, the same signature, and that whole area became to us the ANT2 target area.
46:47 So ANT number 2, that is to the east of that. So, all in all, when we look at, not this because that we can't see nothing, But when we look at the overall story here, not only we've, I believe, understood very well what signature we are looking for, but definitely the Ant Survey has allowed us to confirm, literally, the structural hypotheses that I had to start with. And we can see even in the main lens where there is little variations and it's very subtle but it coincides really really nicely where we can see breaks in the ad survey data. So that was converting me quite a bit to tell you the truth, because it seems to work really, really nicely with the interpretation, but it works nicely because the response seems to be very, very nice and great for us. That is very, very cool.
48:05 So another view that we can have a look at there is a long view throughout the lens and see what are we learning from nickel distribution versus that ant profile that we see here. So since the beginning I've displayed the lens as a shape or a volume one color only. So what I'm going to do is I'm going to replace that by the NI percent numerical model that we have. So just for the time being I'm going to hide voluntarily the ant profile and just focus a tiny bit here on that long view which is showing distribution of nickel grade in percent. So pretty easy to recognize couple things in that slide. Well if we look at the hot colors, we'll see a couple very high-grade shoots that are sticking out from that long view. And then if we look at the cold colors, we'll see definitely some breaks, it seems, within the lens itself.
49:19 So we interpret them blue areas, breaks, areas being faults that are impacting the fine scale location of the lens itself, and some other faults on the boundary of the known NISQ main lens Some other faults being related to the embrace and more major faults that we have in the system leading to those offsets and generation of targets and things. So that being said, if we put back the AMP profile on there, and I'll just minimize here the slice width to about 50 or even 20.
50:06 50 was better. So what we can see is where we had interpreted faults to happen, definitely there is a very sharp change in the profile in that long view view, which is super interesting. And again, we will recognize the same thing happening to the Northeast with that shallower trending line here, which I believe represents the intersection lineation between that major fault that we have to the east leading to Ant 2 on the other side. So in whichever view we look at this, it seems that we're confirming the primary hypotheses that we had.
50:54 And from there, quite frankly, we've explored quite a bit the entire survey, but we're yet to complete the exercise. We've identified so far a bunch of targets that were the most obvious. We're yet to have a second look at that in a much more detailed way and identify other targets that are further away from NISQ main still. And could you show us a plan view of the Ant 1 and Ant 2 trends? Sorry, what? Could you show us a plan view of the Ant 1 and Ant 2 regions? Absolutely. So let's get right now the plan view through the model and I'll get back to the point set. But I think in here, just a random cut, plan view here definitely shows those oblique breaks that we're referring to since the beginning here.
52:00 So the ant 2 would then be following that break that we have to the east. So if you take the main lens and you break it or cut it and offset it in that location that the profile is indicated to us at that, then that became prime target ant number 2. What is ant number 1? Well, ant number 1 is that trend that leads towards the Wildcat target area way up northeast about 5 and a half kilometers away, which coincides realistically with that regional break that we've looked at earlier. And then if we explore to the West, then we'll recognize again, potentially major breaks here that are slicing and dicing that still, and then therefore prime target areas to rediscover equivalents of the NISC, me and Paul somewhere else along the property.
53:12 And we are moving at depth a little bit more in those ultra mafics as we move west. So I think there's like a couple of drill holes that weren't quite deep enough as we were stepping west and that applies for also I think 1 or 2 of the drill holes that were in the northeast as well. So one of the things that we were doing is pulling up some of those drill logs and say, okay, well, where are they placed in relation to the ANT data? And if we had drilled a little bit deeper, what would that have been our recommendation? So that's one of the things that Ken and I have been discussing a little bit, as well as the site team, the GeoVector team as well. Absolutely, absolutely. And what's really, really cool to do is once all of those exercises were done and discussions with you Bronwyn and the entire team, And when we, at one point, I guess we can say we finally understood what the heck we were looking at.
54:08 Now it was time to go back to the initial data set and compare, you know, with what we had to play with before. So perhaps what we can do here is to show again some of the mag data we had to play with and have a little look, trying to understand what the heck is happening here. Oh, OK, I get it. Sorry. So when we compare the mag data we had on surface from before with the AMP profile, it becomes really, really cool to observe a few things. So now I'll try to do that live.
54:58 So bear with me a sec here. So what I'm gonna do, one of the exercise we can do to compare things together is what if we are convinced now that we've identified those breaks that are oblique to the mainland. So, what if we are to look at them, say, along them, so we look on a long stripe view here of them break. So on that view becomes very, very obvious that there is a sharp break there, and we can definitely see it's there. So now when we combine that to previously acquired data, that's where I'm trying to see here the whole thing together, is you take a view and then you convince yourself, okay, I'm looking along strike a major fault seen by the Ant Survey, you realign camera and then all of a sudden you start seeing the same kind of breaks happening in the other data sets, which is very, very nice to have because it to me did confirm actually that the signature we were seeing from the AMP data is something that is real. We can support it with other data, not only the drilling, but also mag data seems to show a response that is compatible
56:28 with the Ant Survey and things like that. So very clearly becoming a complimentary tools to all of the other tools that I knew of before. So it was really, really cool story for me that thing. And to end up the whole story here, if I'm going back to more... I hope that's the right one. So, if we're going back more to the regional view, we've covered essentially that area here with great detail. We've ran a survey at NISQ Wildcat area, sorry, to the north east in here and at this point based on the very successful interpretation we had on that survey for NISQ-MAN, what I'm trying to do at this time is to redo the same thing with the Wildcat dataset, such that we can better prepare ourselves for what's coming up next after Christmas, which will be drilling that thing as much as we can due to the very high grade in PGEs that we've discovered there.
57:47 So and after that that rig being set up the intent is to bring a second rig at site to actually and effectively drill all of them identified targets starting from ant 1, that is where my cursor is, along that trend leading to wildcat, ant number 2, which is, we believe, the equivalent of NISQ Main, but further east and a little deeper. An ant number 3, which is the same thing but on the west side in here, and an ant number 4 which is in that location way further west here where the same signature has been observed when we compared that location to NISC-Maid. So, a very cool tool that led us with a lot more confidence at designing them targets and better spending that money drilling those areas underground.
58:59 That covers it for me. Ken, thanks so much for that. That's obviously a lot of Intel for everyone to absorb. And that's sort of what we'll get back, probably in touch on some of the questions that are coming, but as the business guy on the team, what's great from our perspective is you wanna reduce risk of drilling because drilling is expensive. That's your last resort. You gotta do it. That's how you ultimately make discoveries. But you want to get as much of the brain work you can possibly done. And what we've found is that, you know, in my observation, it's just a business guy in terms of spending the capital is that, you know, by getting this Intel together, this operating system over arcing above the downhole EM and the IP and the magnetics and all that, bring it up, pull it all together, you could really start to see the layout of the possible growth of your deposit. And you can start to do, as Ken said, bigger step outs. And then obviously, once you've hit infill drilling, we can get to at some point in time.
1:00:13 But our job as an explorationist is to try and knock as many tons on the board as possible and obviously get the best grade as well. So I think this is an amazing tool in that respect. And we expect to, it was like learning steps in this first round, And then we were able to get a lot of Intel and then obviously we expect to apply it in the winter program, starting early in January and continue on until breakup in April, May. And we'll be adding a second rig and who knows. You know, so we expect to really step this up. And then ultimately, you know, we didn't touch, we probably don't have time to get into the deeper stuff, but I will make an observation that nickel, generally speaking, is not something you find at surface too often. It's generally a deeper metal. If you look at all the big discoveries like Raglan and Voices Bay, which are very close to home for Canadians, it's basically there. It goes from 500 kilometers down to probably 2 kilometers.
1:01:16 But Norilsk is a classic. It's literally the world's biggest and most valuable mine and started as a surface deposit, you know, close to surface deposit. And then, you know, over the years, they discovered that, wow, there was some amazing stuff available at depth, you know. So that's, you know, that's the, you know, the thing that we love about NISC from an asymmetric investment perspective is that we've got this nugget of NISC main that's being very prolific. It looks like it's got legs and we can add to it. And looks like there may be these, you know, and 123, and 4, all relatively near surface in geological terms that offer us great opportunity to expand that. And then we also have the upside of potentially the depth thing, And that's ultimately what we'll be bringing back, you know, fleet in for next summer's program to, you know, obviously the good news is as we drill, we get more accurate data. It goes back into the, into the, you know, the ANT system and they can iterate. And then it gets smarter. It's like, it is AI, you know, so it gets smarter with it. And then we've got like obviously the experts from their side, people like Nick and Brownman who are working with us, not just with the power of Nichols the robot, but many, many other clients and learning all sorts of, you know, new enhanced approaches to how to analyze the data and how to make it work for us.
1:02:38 So let's get to some questions from some of the audience here. I had 1 detailed question, which we may or may not be able to do, but I do want to bring it up here. Let's see here. Can you show lithiologies on a NAF track plot? I have no clue what that is, not being a geologist. Maybe Ken or Bronwyn, you guys know. Ken, you're on mute. Sorry, what type of map? A NAF Drake plot. NAF hyphen Drake. Plot. I'm gonna have to be honest and I'll Google that up. Okay, okay, so while you're looking at that, we'll ask some other stuff then. One of the questions was, you know, does Fleet see this being a university course at some point that this will be something that all geologists and geophysicists will need to learn? Has there been any conversations that way?
1:03:42 Yeah, it's definitely a tool that would be great to add to any explorationist toolkit. Nick, our geophysicist who's on the call, he actually has been running a course and to how to interpret the data for exploration companies. Nick, do you just kind of want to give us a brief about what that course looks like? Yeah, sure. So it's just a little bit more of a deep dive in terms of the physics, I guess, behind the method. So there is, I guess, a level of understanding which is necessary in order to make the best use of the data sets. And if you look at, you know, ambient noise tomography, compared to say gravity or magnetics, what those other methods represent and what, how do you actually invert those 4 physical properties.
1:04:35 The INT is quite a bit more complex. So yeah, the whole idea of the course is to build a little bit more intuition around what the data sets represent, what their strengths and weaknesses are, what the different methods that we employ during the processing are. Just, you know, ultimately we're trying to build intuition here. So the data sets are delivering the best value possible. Yeah, fair enough. Question we had, just the chap who asked about the North North Drake plot suggests it's the velocity of P waves versus density. So I'm sure that sounds like a geophysical thing to me, but I'll throw it in.
1:05:21 Nick, is that something that you're familiar with? Yeah, so I don't have the plot or that information for NISQ, the specific example. But yeah, I mean, that's P-Wave velocity maps to density with a more or less linear trends for common rock types. So example of common rock types, we're looking at sedimentary rocks versus igneous rocks versus metamorphic rocks. That trend is useful to kind of, if we have drilling, for example, a lot of density data measured on that, then it's useful to inform or to constrain velocity structure in our models, either be it a starting model for the inversion or more on an interpretation basis.
1:06:18 It's also worth pointing out that that that trends, that mapping of density to the velocity, it breaks down under certain circumstances. And one of those is when we have highly altered rocks. Also when we have mineralized zones. So yeah, we utilize that trends in some parts of our interpretation process, but it's more of a guide. And also worth mentioning that the surface waves which we extract from the ambient noise, we model the actual shear wave velocity from that information. So shear wave velocity is different to the P wave velocity, it's slower, but again it does map with a relatively constant ratio from VS to VP. So yeah, there's a couple of layers of information there. Summary is we can use that mapping of density to velocities as a guide for interpretation.
1:07:11 Okay, cool. So another question, What creates ambient noise in a very remote location, i.e. Places with no roads or volcanoes or trains or twisters? Yeah, yeah, yeah. So it depends on frequency. So higher frequencies, so above 5 hertz in this example, generated predominantly by human activities. And that's infrastructure, mines, towns. And these things can be around 50 kilometres away or up to 100 kilometres away, say, if you have a town, which is generating noise around 5 hertz. Above hertz, you really need sources which are quite close by. And at low frequencies, we generally don't have an issue with sources because the generating mechanisms are large-scale atmospheric effects. We're talking about swells interacting with the shallowing of the depth of the water, the continental shelf, the margins of continents, And these waves, they generate, these sources, they generate low frequency signals, so below 2 hertz, and they propagate for many thousands of kilometers.
1:08:23 So generally we see, we're readily able to acquire the low frequencies, And high frequencies, you know, depends on the area of the project. But it's also worth mentioning that so the geode, which is the sensor which Fleet manufactures is designed specifically for picking up these weak sources in the ambient noise wave fields. And so it allows us to go to a little bit higher frequency and build up signal faster than other nodes which are commercially available. Okay. So a question, Terry mentioned that you had a roughly 50% to 60% success rate when drilling in terms of intersecting the mineralized zone.
1:09:08 What percentage of the drilling was done before using the Ant application? What percentage success do you expect to get now that you're using the Ant application? We drilled most of it before Ant, I would say, just the last section. Probably in the fall we started to use it. But Ken, maybe you want to take that one? Yes. Actually, we haven't tested really nothing using the ANT technology, except I would see the deeper part of the deposit right now, and a little bit to the east. But I guess we were interpreting the Ant survey and getting to a conclusion.
1:09:57 22,036 we probably did because we sort of saw that it looked like it was okay when it initially looked like it. Our theory was it wasn't going to be good. And then when we saw the data, it sort of showed that, no, that's probably going to be okay. And then we stepped out 300 meters and hit it. So that was probably, That was 1 for sure. Yeah, absolutely. Yeah. The other stuff, again, we've got the data now. We're going much deeper on certain trends on the core NISQ main. And then we've identified this Ant 1, Ant 2, well up to Ant 4, and we have not done anything on those yet, but, you know, and there's still work for the team to do, you know, over the holidays, you know, to, you know, from now until, you know, mid January, when we pick up again, is to, just to again, crunch all the data, look at it from a variety of different fronts, and then we'll start to test it.
1:11:00 There's a question out there, what would you think will be your level of accuracy going forward? You know, I don't know. Do you, is that something that you guys have, you know, you've got, I think you said you've read 150 or 180 surveys. I'm sure you generated, you know, I don't know, you know, 900 or 1000 targets, you know. If you've done any back testing on this to see what's the success ratio and stuff? It depends on the property really and what the results are coming through. We've definitely had clients drilling specifically on the areas of interest that surveys have shown and fleet have identified with really good success rate, but it is dependent on the project. So what Exosphere and the A&T surveys is good at doing is mapping those bulk changes and those really interesting kind of larger scale features. And we're also considering the resolution as well of the data set. So for the NIST deposit where we had the infill survey, so we were dealing with about a 30 meter resolution.
1:12:10 So when we're looking at features, we keep in mind that that accuracy as well of those data sets. And as we get deeper into the model, the resolution does change a little with depth, but your trade-off is seeing those big scale features lower in the deposit type. So Yeah, it's really dependent on the deposit, but we have had a really good success rate. I can't give you a specific number because not all the time it's fed back to fleet, but the clients that we've worked with closely and have drilled a few of the targets based on the responses are very pleased with their process. And I just... Sorry, go ahead, Darren. No, go ahead. Go ahead, Bellamy. Yeah, I just wanted to tie that into to one of the questions that popped up about using Exosphere and the geodes on a purely exploration-based survey.
1:13:01 That's definitely something that we do. We're currently working on a project in South Australia that the only geological data they have is a map from the 1970s. So other than that, we are going completely blind and that survey is our deepest to date, so up to 3,000 meters depth. And we have a lot of other clients using it in a purely exploration sense. And the model does have really good velocity responses in all of those cases, and that's what we're looking for. So either changes in lithology or big structural features that cause changes in the velocity response such as faults and folds, those still pick up really well. And we don't need constraining data to make a model, but it is helpful for the interpretation process and tying it back to what the field geologists have interpreted already. And that's one of the great things about working with the clients and that we have a designated team at Fleet is that it's a collaboration process to analyze the data and work through the results regardless of if it's a known deposit or not.
1:14:12 Obviously with NISQ, we were fortunate we had a bunch of drilling data, a bunch of the other data sources that we could look at, is your sense that given that we run both a narrow and a wider survey, that what we see at 1, 2, 3, and 4, they're unlikely to be mirages. They're, in your view, if one is definitely a mirage and 10 is an ore body, how are you feeling about those targets? Well, I think that's a me and Ken question, or Nick. Nick, go ahead. I'll just jump in quickly.
1:15:03 So surface waves, when we model these surface waves, really what we're looking for is for contrasts in bulk velocity structure. So in this example for NISQ, we actually see that. It's a perfect scenario for the method because we see these offsets and these contrasts, lateral contrasts between high and low velocity. So we're able to image how these packages are offset and we're able to image the packages themselves. So it's more difficult when the contrasts are more subtle or the features that we're looking for are quite small in proportion to the array station spacing. So I think to answer the question, in this case, we do see these contrasts in bulk velocity structure. And we also see a really coherent strike orientation of that response, which is not constrained at all by by outside data. This is purely model data driven.
1:16:04 So yeah, a lot of these features do build up our confidence in the models at the end of the day. So I think, yeah, to answer the question, they're probably not mirages. I won't give you a hundred percent. I mean, you can't guarantee we're going to hit nothing but pay dirt. I mean, come on. Well, I mean, in geophysics, you know, all models are wrong, but some are useful. And I think, you know, that's the case. I appreciate that. And I think we all know that Mother Earth is a tricky rascal and she never makes it easy on us. But it is an important new tool and clearly we think it will enhance our odds dramatically.
1:16:53 And the neat part about this is that, if we drill 1 of these structures and we don't hit, we're gonna learn from it, and they'll be able to reiterate off that learning. I think that's the other important thing is that, and it's like when people say, well, why don't you hit 100% of your holes? People just like haven't been around mining, whatever. They don't realize that you gotta miss, otherwise you're not doing your job because you're not pushing the envelope. So in order to really, you know, you've got to step out and miss, otherwise you're not going to find out where the constraints are for your ore body or your deposit or your mineralization. I don't want to get in any 43-101 trouble. It's, you know, such as it is. But I mean, generally speaking, that's important. And it will be the same thing with this tool in that there'll be a series of targets that it'll identify and as obviously they've done with us. And we think we'll be more successful with this than any other tool we could be using.
1:17:46 And I'm sure we won't hit 100% because nothing works 100% of the time, but we'll also learn from it. And then, you know, maybe the next time we'll be able to get even more success. You know, that's, would you agree, Nick, that that's sort of a good way to look at it philosophically? Yeah, absolutely. And particularly, you know, moving forward into next year, we're constantly looking at ways where we can deliver a result which has a lot more geological context. So at the moment we model data in terms of velocity structure, but really what we wanted to move towards is geological inference from the datasets. So that kind of, you know, it's a lot closer to the geology. It's a lot more useful for validating exploration targets and hypotheses moving forward. So yeah, particularly, you know, that's where we want to go. And I'd also mention that the addition of the velocity data, so the geometries and the velocity structure you get from that model, it works as an independent constraint on all your other geophysical data. So when you try to extract maximum value from the exploration data sets, it's really important to have data which constrains other data, So you can get a nice coherent, well-constrained geological model hopefully out at the end of the day. And that's kind of what ANT really, really provides at this point.
1:19:13 Yeah, I agree 100% of that. I had a question. Does Exofer share any similarities with the Typhoon technology that iPulse backed by Robert Friedland has developed? I understand that Typhoon is a distributed IP system. So no, I would say that there's no similarity there in terms of the method, possibly in terms of some of the backend software that there might be, but I'm not aware of any. Okay. What is the resolution depth extent of the answer? Yep. So for this one, for the infills, we were down about 300 meters and for the regionals down to about 900 meters.
1:20:04 But I mentioned before we have a survey going that's about 3 kilometers depth. So it's all dependent on the geospacing and that obviously impacts the depth and also the resolution. So with each client we work with, we set out the objectives and what you want to do, what the regional and local geology is, and what the target zones are, whether it's analyzing structural controls or if you have certain mineralization that might cause a difference in velocity response. All of those features we take into consideration before designing a survey. We have a team of experts that will design it to make sure that we hit exactly what you're looking for, for depth and resolution. The way the geodes work is we can manipulate these surveys on the fly as well.
1:20:51 So for deployment, we usually have a couple teams of 2 or 3, and those teams will deploy the geodes. It's a very easy process. So they're just put into the ground. I saw a question about whether we've done any Arctic Circle work, but we need that coupling of the geode to the ground surface to record that information. But the teams will take these geodes, whether it's on foot, or in PowerNickel's case, we did some helicopter work. We have a client who's using horses. So it is really diverse in that deployment process. But generally you can deploy these geodes in a day or 2 days, depending on the field size and the spacing between the geodes.
1:21:40 Once those geodes are in the ground, we make sure that there's satellite connectivity so that that data can be transmitted right away, so that we can start collecting the data and have those models generated as soon as possible. So with Power Nickels case we did the 6 surveys over the field season. They had a team on site that was obviously doing the geological work on other projects but also helping out with the deployment of the geodes during that project. So the way it works as far as the programs, the geodes are leased to the clients for a certain amount of time, 1 month to up to 6 months or more for some of our clients. And it's as many surveys as you can get done during that time. And then the data collection period is dependent on the signal that the geodes are collecting as well as the data quality. So It's a big balance, but Fleet kind of guides you through that process the whole way. And you get models generated as that process continues. So instead of A36 month turnaround with some traditional methods, we are turning around models in a couple of days from data collection. So it really can speed up your exploration process for your projects.
1:22:50 So we're going to get one more question here, and then we'll just do a wrap up before we go. So one of the questions was, does Exosphere add information that is simply not available by other means, or does it effectively just accelerate the time scale for collecting the data? I don't know who's best, Nick or Bronwyn, whoever. Yeah, I can probably have a stab at that one. Yeah, so it does both basically. So clearly it accelerates the acquisition and delivery of results from the datasets. But critically is, it goes back to what is the makeup of the ambient noise in a particular project area. So typically when we go into a new project and the first survey of that, we will deploy a subset of the geodes, so maybe 5 geodes, say, in a small array.
1:23:42 And from that information or from that data set, we can determine the composition, frequency composition and directionality of the wayfield. And then that information is critical, absolutely critical for designing subsequent surveys, which best adapts to the wayfield conditions and deliver the best model. So I guess the analogy for this is an ultrasound. So you have an ultrasound wand and you have some detectors and you have an imaging technique. And the idea is that you can move your ultrasound wand around to better image the target. And that is exactly what we try to do with Exosphere, having that real time information coming in. We can determine the way of composition, frequency content, directionality, and then subsequently design arrays, which are best suited.
1:24:31 And again, just to reiterate, those high frequencies are really important for detailing our model, but they are also the hardest ones to pin down and understand. So having that real time gives us a real benefit in that regard. Okay, cool. All right, well, listen, why don't we go around the table here and just get some last thoughts from everyone here. So Nick, why don't you start off? You had the last comment there and give us your last thoughts and then we'll go to Brown 1, Ken, and then I'll wrap it up. Yeah, look, I just wanted to say, it's been a pleasure working with you guys on this project and it's fantastic to see the ways in which you're using the datasets and yeah looking forward to continuing to work with your team so thanks very much. All right, Rowan? Yeah I share the same sentiments as Nick.
1:25:19 So this data set is one of the best and I probably shouldn't say my favorite to work on. But you know, when we're dealing with a project that has great geologists and people that are really capable to push the data to its limits is really valuable for fleet. And we appreciate the time Power Nickel has spent with us. And yeah, we're really looking forward to next year's work and also seeing the drilling results over the winter. Super. All right, Mr. Kent. Well, same here. I guess my conclusion will be Maybe I was a little reluctant in believing in the technology at first, as you did mention, but hey, they did work, they tried.
1:26:12 Absolutely. I mean, as it's been documented, it's complimentary data set that we could have lived without it, but it makes our life so much easier in terms of being capable of interpreting what's happening at depth. That yeah, very, very, very successful story on my end, the way I've used the data. When I look at it from the business perspective, part of a junior mining company's mission life is obviously you've got a geological vision of what you've got, and then you've got the reality of what you've got. And then you need to bring that to the market. We had this vision of NISQ and now we've got a pile of very positive results. And then it's like, how big can it be is sort of the next key question. You know, we think we've established it's going to be a commercial deposit. We think That's why people like CVM are involved and are working towards a feasibility study. So we believe we can get this thing operational in 4 or 5 years.
1:27:26 At some scale, the question is how big and eventually this thing could be really a monster. And that's why we look at Ant 1, 2, 3, 4 as enormous opportunities for us as explorers to test what looks at this point to be a really great exploration bets that have got all the right signatures, the right sort of characteristics that we would think would be attractive and receptive to a successful drilling program. Now, will they be successful? That's ultimately what we'll find. But we'll even as I suggested, even from, you know, you know, not being successful, we'll learn how to be more successful. But I know one thing in the history of time, every single nickel sulfide mine in the history of the world was multiple pot. So is it possible that NISQ will only be a single pod discovery? Well, I guess anything's possible, but based upon what we're seeing from the data and everything else, I believe we're onto a multiple pod discovery here. And this could be really an amazing Nickel discovery story. So we're going to look forward to bringing you more conversations like this over the year with Fleet and ultimately soon with CVMR, you know, as we explore the other side of the story about the production.
1:28:47 But we're pretty stoked about what's happening at Power Nickel and we look forward to bringing it to those people that are interested in our story and in our stock. And we'll look forward to keeping you engaged over the coming year and we wish you all a happy holiday season. I hope you have a really great one. It's been a bit of a rough year for humanity this year and we could all use a little peace and goodwill. So God bless you all and have a great night and thanks for attending our show today. Cheers.
