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Lyceum 2021 | Together Towards Tomorrow

This presentation is a case study about a significant structural and lithological data inventory from Lumwana Mine’s Chimiwungo Deposit

Which was carefully interpreted in Leapfrog Geo to create a series of block-faulted ductile, tectono-stratigraphic domains and internal structural form interpolants that encompass an intensely strained 100-meter-wide shear zone. Discover how dynamic modelling workflows and the resultant 3D model honours structural cross-cutting relationships and depicts deposit- to regional-scale kinematics, and learn how the model is currently being used for forward geotechnical domaining.

Overview

Speakers

Corné Koegelenberg
Principal Geoscientist, Tect Geological Consulting

Duration

20 min

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Video transcript

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Hello everybody, thank you very much for tuning

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into the Lyceum and giving us the opportunity

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to present some of the work we’d like to present.

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What I’m presenting today is a project

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that we’ve started in 2016.

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It’s run up to 2019, it largely revolves

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around 3D modeling of the Lumwana mine,

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in Zambia.

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Now it showcases some of the really distinct capabilities

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of Leapfrog Geo and largely how you can sort of

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feed a conceptual structural study into the modeling sphere.

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So it’s essentially what we call a structural model,

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is when you can sort of see

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the conceptual structural understanding in a model.

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And this is one of the projects that we like,

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to show people just to showcase what Leapfrog is all about.

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And so to speak, what a structural modeling

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is all about.

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So I was leading the team on the ground at the mine.

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We also had Hastings Lupapulo, we had Vincent

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from the geotechnical department

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with Peter Hornsby as well, assisting on the ground.

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These guys largely work for geo-tech

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and sort of structural departments.

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And obviously those other guys are most interested

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in the products that we ended up

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delivering at the end of the day.

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So to get into it.

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Firstly, is the conceptual sort

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of structural evolution of the mine.

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Lumwana sits in the Lufilian Arc.

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The Lufilian Arc’s also well-known

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for basically hosting

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the DRC copper belt.

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And the Zambian copper belt.

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It’s part of one big great sort of collisional Arc.

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Now what makes Lumwana mine unique is

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that it sits in the core of this Arc.

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It’s not as a typical sort of,

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external fold and thrust belt setting.

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Unlike for most of the largest copper mines,

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copper cobalt mines in the world.

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Lumwana is actually sitting in the core

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where it’s situated on,

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deepest structural terrain.

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You’re looking at high metamorphic degrees

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and really very, very high strain rates.

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So if you look at the location,

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the mine situated on the Mwombezi dome.

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It’s one of the windows into the basement,

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essentially a window through the Katangan Supergroup,

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which has largely defined your Lufilian Arc.

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In that the mine

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exposes shear zones

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in between the Katangan Supergroup and the basement.

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Whereas the mine is actually

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sensu stricto acidic in the basement.

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The basement around this particular deposit

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consists of large sort of thrust sheets.

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If you can imagine it’s like a deck of cards

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that’s just sort of slided up to the one side.

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That’s essentially what the tectonics

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or the tectonostratigraphy this mine looks like.

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So it’s a very unique setting in the copper belt region.

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So.

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To just show you where the Chimiwungo Deposit lies.

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The Chimiwungo Deposit forms part of the Lumwana mine.

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It’s actually one deposit, the other deposit is,

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Malundwe.

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That is to the east whereas Chimiwungo is to the South.

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the general stratigraphy of the mine,

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is what we call a tectonostratigraphy.

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It’s not a typical sort of sedimentary stratigraphy.

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You’re looking at sort of sharp thrust sheets

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lying on top of each other.

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The base of this stress stratigraphy,

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is what we typically refer to as gneiss

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or gray gneiss package.

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That’s very competent gneiss or undifferentiated gneisses

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that line with schists or interlayed with schists.

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Now, it’s not just a flat sort of package.

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There are folded gneisses or isoclinal folded gneisses.

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They are in between the isocline folds you get

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on the limbs that are bound with shear zones.

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And you can also see a gneiss fold

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on one of the cores there.

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If you go on top of that unit, you’re going from a footwall.

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And then you’re going into what’s typically

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referred to as an ore schist.

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Now an ore schist is what’s essentially,

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the thrust.

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That is in between some of these larger thrust sheets.

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So the ore schist is in the shear zone.

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This is a ductile setting.

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So the ore schist is essentially,

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the equivalent of a fault gouge

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or a sort of a fault breccia in a brittle setting.

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It’s a complete rock unit that was created

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with dynamic metamorphisms.

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Basically as you ingress fluids, you change the composition

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and the structure of the rock.

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As you can see, it is intensely foliated.

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And largely the mineralization

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is sitting on top of the folia.

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The mineralization is largely chalcopyrite

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or copper-bearing sulfides.

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Depending on the level of oxidation

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that’s more copper, less sulfur, less oxygen.

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What you can see in the top right there as well,

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is that this unit is extremely thick in some cases.

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The ore schist can be up to 100 meters thick in some parts.

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Shear zone that’s 100 meters thick.

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It’s a pretty significant site,

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and you can also see the footwall exposed there.

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Our ore schist is sort of copper, like a bronze color.

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That’s largely the oxidation of the sulfides on the surface.

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It’s a really spectacular deposit.

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If you ever a chance to go there, please visit.

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Now on top of that, if you’re going into the hanging wall,

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it’s the top most layer of the tectonostratigraphy.

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You can see that the contact sometimes is sharp.

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And it’s all not always very sharp.

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You can see a slight transposition

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going from the ore schist into the gneisses on top.

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So you can see how the gneiss is progressively

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being infected by the dynamic metamorphism,

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creating more and more ore schists.

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It’s typically also what we refer to,

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as sort of strain-softening.

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So as you change the composition and the rock type,

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it starts to accomodate more strain.

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That’s largely because you’re going from competent gneiss

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into ore schists that’s very, very strained.

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Now the top unit, which is the pink gneiss.

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That’s the thrust or the layer right on the top.

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It’s extremely competent like the footwall.

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In this case, it’s just a gneiss with a different composition,

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a bit more potassium in the system.

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So it sort of just gives you that beautiful pink color.

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Now again, because of the pink gneiss competency,

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it can’t absorb the same amount of strain

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as you see in the shears on it.

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So what happens with the spent gneisses

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to accommodate sort of a flattening strain

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across the entire deposit.

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It’s got to break somewhere.

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It’s got to sort of accommodate strain.

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And what it does is that you form

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very narrow shears of it in this package.

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And you can see that these shears are obviously shifting

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or allowing this package to accommodate

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or to fit into the sort of narrow stratigraphy.

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Now these shears are due technically very, very bad

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or very significant for mining.

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In that you don’t want them to be exposed

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in the unfavorable sodum geometry geo pit

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because they are prone to be very weak.

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So if you take the evolution

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or the structural evolution of the sites.

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All the elements into consideration,

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you can see the three distinct

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sort of stratographical packages.

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And you can see that the strain across the entire mine,

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in this case across those three stratographical packages

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is accommodated differently.

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So the footwall is different to the shear zone,

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is different to the hanging wall.

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And all the internal sort of structures are rotated.

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and sort of align is different.

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So you’ve got to treat every sort of single package,

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especially if you’re modeling them,

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you’ve got to take all these things into consideration.

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If I go towards the southern end of the deposit

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across the Southern pit,

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you can see the same sort of features.

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The important bit here is that for the mining perspective,

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is that the shear zone, and the ore schists,

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and obviously the hanging wall

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is largely exposed in the pit.

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And very little of the footwall is.

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Obviously in mining past the ore schist,

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you don’t want to be mining too much waste.

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So if you can see a long section through the mine,

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apart from it being a ductile setting,

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you can also see that there are

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significant sort of brittle faults.

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Now these faults are much, much, much younger

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than the sort of structural evolution.

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All of the events that actually form the deposit.

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These faults sort of cuts from east to west across the mine.

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And they obviously segment the deposits

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into various fault blocks.

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And those are also very significant

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for the modeling considerations.

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Again just a nice summary of everything we’ve seen.

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Just a bit more 3D is that you can see,

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sort of the different kinematics

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stemming across the ore schist into the hanging wall

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And all these things we’ve tried to conceptually figure out.

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We’ve got a very good understanding of the model

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and structure that formed the deposit.

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Now the name of the game is,

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how do we model all these elements?

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It was quite a sort of careful exercise,

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in that we’ve got a very good conceptual

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understanding of the model.

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What’s significant, is that we had a extremely

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sort of large database of structural data.

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We were able to map all the pits extensively.

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we had 1200 hundreds of stations.

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There were more than 3000 measurements.

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Individual measurements of fabrics,

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and foliations or any relevant features.

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The structural, from a structural logging point of view.

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Exploration logs provided us with more than,

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12,000 measurements, conventional readings.

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So you know, actual geologists log those readings.

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it’s good readings.

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And if you’ve got 12,000 readings it’s really grateful for,

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I’m sort of comparing data sets.

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Again we also had some ATV

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and OTV micro structural readings.

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Now the most important part of all these datasets

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for us was to do a bit of due diligence.

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And discretization of the data.

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So the first, due diligence is obviously

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where we checked if all the data sets match.

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Because with massive data sets like this,

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each sort of unique data set’s got a bit of a bias to it.

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We had to make sure that we sort of,

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did not give any particular dataset,

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more weight because of a certain bias.

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We had to sort of straighten out the data.

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As well as discretization is for each sort of block

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or each domain that we looked at,

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to make sure that the populations overlapped.

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Now, we did this essentially for foliations

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across the entire body.

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We looked at

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joints across the entire body,

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and you can see it’s sorting various datasets.

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Lots and lots of sort of, staring at analysis.

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And also we looked at faults and making sure

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that we weigh the data properly.

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And obviously beyond this,

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we had to start looking at structural domaining.

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How are we going to domain or segment this model?

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What we did was firstly, and this is a logical step,

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was to use some of the significant brittle faults

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to define brittle fault block domains.

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Now you’ll see that there are some of these brittle faults

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that we have not selected.

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They obviously represent very little offsets,

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maybe two to three meters up to six meters.

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Some of the larger faults are far greater.

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I mean the orange faults which define the blocks taken,

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can throw the whole body off by 20 30, 50 meters.

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That was a really significant fall for geotechnical

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and sort of, resource modeling purposes.

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Beyond that, obviously we spoke about the tectostratigraphy,

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is that we went on to divide the model.

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The model volume then between hanging wall,

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ore shifts and footwall.

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To being cognizant of all the different

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sort of structural features in each one of those blocks.

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Now what’s nice about this, you could really see

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if you just take out the ore schist.

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And you look at the topography which is dip shaded

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and ore schist sort of thickness.

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You can already start to see sort of structural elements

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coming out of the shear zone,

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that sort of matches conceptual sort of structural model

[00:13:56.503]
that we initially show.

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Now in this case you can see very sort of small,

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secondary peracetic folds.

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as well as sort of larger gentle scale folds.

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In the model later on you’ll see,

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how these sort of structurally, come into play.

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So what we did was to,

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sort of use these

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tectonostratographic domains.

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We wanted to model inside of them, we wanted to refine them.

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But how do you define a particular structural feature

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or particular dominant structural trend

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in each one of these domains.

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Obviously as to use the

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large structural database that we had.

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And in this specific case, we sort of divided the data

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into each one of the domains, and then we groomed the data.

[00:14:46.400]
Now here strictly when I’m referring to grooming,

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is when we take the careful due diligence

[00:14:52.930]
and structural discretization that we did was,

[00:14:55.770]
to remove outliers in a spatial way.

[00:14:59.300]
Leapfrog is really, really good for doing this.

[00:15:02.870]
In that you can use the Leapfrog stereonet functionality.

[00:15:06.490]
Whilst you’re looking at stereonet, you can also spatially

[00:15:09.230]
assess the data and where it’s sitting.

[00:15:11.860]
So it’s really, really great to remove outliers

[00:15:14.600]
and not just on a geometrical base

[00:15:16.742]
but on a spatial sort of base as well.

[00:15:19.240]
We sort of groomed through all of the data

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to make sure that it fits the conceptual structural

[00:15:26.890]
understanding of each domain.

[00:15:29.280]
And just as a caution, I say grooming and not de-clustering.

[00:15:35.150]
So in any sort of structural model and with this database

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is that you want to make very, very,

[00:15:42.410]
carefully sure that you feed data into Leapfrog that is,

[00:15:49.190]
how can I say, already checked and discretized.

[00:15:52.440]
Because the structural, the de-clustering tool which is

[00:15:55.440]
automatically used in some of these modeling processes,

[00:15:59.500]
basically removes duplicates.

[00:16:02.150]
So you don’t want, in a certain sense,

[00:16:04.370]
when you’ve got dominant groups.

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the dominant groups will be weakened

[00:16:07.450]
because you’re removing duplicates.

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And those obviously that are not duplicates.

[00:16:11.260]
The sets that do not form part of the main groupings

[00:16:15.340]
will be more precise or more dominant.

[00:16:17.590]
So it’s very important to do your sort of grooming

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before you use these tools.

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Not afterwards or whilst you are using them.

[00:16:28.080]
You need to sort of do it in advance.

[00:16:30.640]
Now as you can see, what’s really nice is

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when we built form interpolants it’s a really nice tool.

[00:16:36.290]
And Leapfrog is essentially showing you,

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general structural trends through

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sort of a point cloud of structural data.

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And you can see for each of the tectonostratigraphy,

[00:16:45.214]
of one of the domains.

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The form interpolants in this case showing you

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in ore schists, the Schistocity of the ore schists.

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In the top, the footwall and the hanging wall,

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more of a Gneissocity.

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And you could see the kinematics sort of rotation

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of these form interpolants.

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Fitting the conceptual structural model very nicely.

[00:17:08.730]
We were very happy with these results.

[00:17:12.380]
So with that sets, if you zoom out,

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we had enough data to construct this

[00:17:16.820]
across the entire sort of mining volume to acertain.

[00:17:20.780]
Obviously we’ve got more data, you’ve got more accurate

[00:17:24.470]
sort of structural form interpolants.

[00:17:26.970]
More further away from the data you have to use other

[00:17:31.220]
sort of sets, or interpolations, or interpretations.

[00:17:34.000]
For example, just using the contacts.

[00:17:36.200]
But largely this sort of model was informed

[00:17:38.410]
by the large structured data set that we had.

[00:17:45.160]
Now that we’ve established the structural trend

[00:17:48.660]
for each one of these domains and on a block by block basis.

[00:17:52.090]
We could continue to do a refined lithological model.

[00:17:55.756]
A lithological modeling that essentially came down

[00:17:59.380]
to doing sort of a more pure implicit modeling,

[00:18:02.230]
Where we fit the form interpolants.

[00:18:08.570]
Obviously trying to keep the volume that we were modeling

[00:18:12.430]
for a particular block, as small as possible.

[00:18:14.680]
Allowing Leapfrog to work at a greater resolution.

[00:18:17.680]
Okay, so now that we’ve defined our sort of structural brain

[00:18:21.410]
in our tectonostratigraphic domains.

[00:18:25.028]
We from a more pure implicit way try

[00:18:28.220]
to model the detailed lithology.

[00:18:30.430]
So obviously in your hanging wall

[00:18:32.100]
and your footwall sort of domains,

[00:18:33.810]
we extracted gneissositian schists.

[00:18:36.600]
Obviously undifferentiated gneissositian schists.

[00:18:41.040]
Whereas for the ore schists, we looked at essentially

[00:18:44.600]
everything that is considered ore and not considered ore.

[00:18:47.680]
Those that’s not considered ore is typically waste lenses.

[00:18:51.870]
Now these waste lenses are bodies of ore chunks,

[00:18:56.040]
of hanging or footwall floating around in the ore schists.

[00:18:59.740]
Only those things you want to sort of pull out

[00:19:02.360]
or not feed into your crusher when you are mining.

[00:19:07.520]
So if you put a slide through this,

[00:19:09.246]
you can really see how the implicit modeling

[00:19:13.050]
and the structural trends work together

[00:19:15.260]
and dragging out the geometry of the shear zone.

[00:19:17.900]
Obviously, the hanging wall and the footwall as well.

[00:19:22.310]
Like I said, we were really pleased with these results.

[00:19:25.740]
If you consider that the massive drill hole database,

[00:19:29.350]
that this is an instructional data.

[00:19:31.650]
All this sort of working together giving you a really,

[00:19:33.960]
sort of concise structurally accurate model.

[00:19:39.200]
What we did beyond that is to even go further.

[00:19:42.420]
So in serving a refined model what we did was

[00:19:44.950]
to extract waste lenses, like I’ve just mentioned.

[00:19:49.170]
On a higher resolution.

[00:19:50.720]
So what we did was to evaluate volume metrically

[00:19:54.120]
structural data and also form interpolants inside

[00:19:57.900]
and outside waste lenses but still within the ore schist.

[00:20:01.810]
And we used those two to build

[00:20:03.990]
even higher resolution structural trends.

[00:20:07.290]
And what you can see is that from that,

[00:20:09.350]
we sort of redid the pure, sort of implicit modeling.

[00:20:14.030]
And what we got was really, really accurate

[00:20:17.330]
sort of geometries that really sort of represent

[00:20:20.330]
what a natural sort of shear zone looks like.

[00:20:23.147]
And again, we were pleased, really pleased with the results.

[00:20:28.710]
So beyond that because it’s a structural model

[00:20:32.367]
and because we’ve largely worked not only with resource,

[00:20:35.750]
but mostly with geotech,

[00:20:38.617]
is to use the ore schist

[00:20:42.130]
to define a geotechnical or structural geotechnical domains

[00:20:46.110]
where,

[00:20:47.164]
we divided the ore body as well

[00:20:49.750]
as the hanging wall up into sections.

[00:20:52.550]
Sort of different sections for kinematic analysis

[00:20:55.490]
across the deposit.

[00:20:56.950]
We looked at sort of ore thickness, ore schist thickness.

[00:21:01.320]
But more importantly, we looked at some of those peracitic

[00:21:04.207]
and more gentle folds to sort of establish domains

[00:21:07.300]
where you get a more consistent geometry font

[00:21:10.730]
from particular features.

[00:21:12.640]
And the model really, really sort of aided

[00:21:15.090]
that whole thought process.

[00:21:19.170]
Beyond that we’ve also taken the form interpolants

[00:21:22.750]
or the dominant fabric orientations

[00:21:25.710]
in each one of those domains.

[00:21:27.250]
And we’ve juxtaposed it against the sort of,

[00:21:30.950]
long-term design or pit designs.

[00:21:33.750]
And in this case we can see red, warmer colors

[00:21:37.000]
versus colder colors.

[00:21:39.080]
Obviously red in this case would mean

[00:21:41.310]
more unfavorable situations.

[00:21:44.330]
Whereas the blue would mean that it’s really favorable.

[00:21:47.800]
In this case,

[00:21:50.167]
what we categorized favorable and unfavorable

[00:21:54.400]
was the fact that you had foliation that is day-lighting.

[00:22:00.010]
So if the dominant foliation is day-lighting outside

[00:22:03.080]
of your pit, you would obviously have some

[00:22:05.680]
of those really bad

[00:22:08.000]
shears that you saw on previous slides day-lighting.

[00:22:10.650]
You don’t really want that.

[00:22:11.850]
So the red zones largely represent areas

[00:22:15.330]
where you could possibly end up having that scenario.

[00:22:19.000]
Whereas the blue area, you end up not having that scenario.

[00:22:22.670]
Now this is a sort of a double-edged sword

[00:22:25.290]
in that you can mitigate some of these risks.

[00:22:28.960]
But you can also optimize on either end

[00:22:31.100]
where the slopes are blue.

[00:22:32.630]
You try and perhaps increase the slope if you want to.

[00:22:35.810]
These are all sorts of factors,

[00:22:37.330]
that feed into the whole geotechnical design process

[00:22:40.350]
for this particular mine.

[00:22:42.690]
So yeah those are some of the elements

[00:22:44.470]
that we were able to draw out from the structural model.

[00:22:49.210]
Like I said, a structural model

[00:22:52.330]
starts with a conceptual understanding of your deposit.

[00:22:56.380]
And then that feeds into Leapfrog,

[00:22:58.720]
which absolutely allows you

[00:23:02.029]
to sort of realize that sort of structural concepts in 3D.

[00:23:05.950]
And that obviously feeds into downstream geotechnical

[00:23:09.270]
and resource capabilities that are very, very accurate.

[00:23:17.950]
To satisfy geologists like myself,

[00:23:21.102]
who would like to see structural

[00:23:22.673]
or complex structural geometries being realized.

[00:23:27.100]
Yeah, thank you very much.

[00:23:28.140]
Thank you for your time.

[00:23:30.403]
And I hope you enjoy the rest of the conference.

[00:23:35.847]
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