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Are you working with magnetic data?

Using open-source Geoscience data, we will illustrate how Oasis montaj can improve your understanding of an exploration project. This demonstartion will highlight some of the new magnetic interpretation tools within Oasis montaj. We will start with some fundamentals, 1D & 2D Filtering, then jump into Grid Texture Analysis, Magnetic Inverison and Self-Organizing Maps.

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Geoff Plastow
Senior Geophysicist – Seequent


28 min

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Video Transcript

(soft music)

<v Geoff>Hello, and good morning</v>

and good afternoon to everyone in attendance.

Welcome to a live presentation

at the 2021 PDAC Virtual Conference.

Thank you so much for joining today.

We’re going to be looking at Oasis montaj

and how to improve your understanding

of an exploration project with magnetic data.

So just a quick introduction.

My name is Geoff Plastow,

and I’m a senior geophysicist here at Seequent,

and I am currently based in beautiful

Vancouver, British Columbia.

I’ve been at Seequent for just about three years now,

but I’ve been using Oasis montaj for about 15 years.

I’ve had the opportunity to work with a wide variety

of geoscience and geophysics datasets,

everything applied to exploration, energy,

civil and environmental applications.

I should also mention on the webinar panel

and monitoring today, we have my colleagues,

Adriana Carbone, and Kanita Khaled.

Before we get too far into our discussions today,

I just have a quick statement

of confidentiality and disclaimers.

I’m not going to read it to you,

but I’m just going to leave it here

for a moment for you to digest.

The good thing or the great news

about today’s presentation

is that everything I’m showing is available

in the current release of Oasis montaj version 9.9

and it’s available to all maintained

and subscription customers.

So what are we going to look at today?

Today’s focus is an early stage

greenfields exploration project.

Our objective will be to take a public domain data

and extract more information

from the magnetic data

to try to vector our exploration efforts

to the most prospective areas

within the project area.

So what are we actually going to look at?

We’re going to look at some open geoscience data,

where to get it and how to quickly get it

and integrate it into your project.

We’re going to look at a new Multi-Trend Gridding algorithm

available in Oasis montaj.

We’re going to look at some 2D filtering or data transforms

that we can apply to magnetic data

to squeeze more out of it.

We’re going to do some grid texture analysis.

So we’re going to extract the fabric from our magnetic data

and we’re going to create a structural complexity map.

Then after this, we’re going to take a look

at some magnetic inversions

and how they can also improve our insights

into our project area.

So just before I get going,

just a couple of acknowledgements,

the dataset we’re looking at today,

it’s a public domain dataset.

The data is available on the Natural Resources Canada’s

Geoscience Data Repository.

The link is here

and this data repository is powered

by Seequent DAP technology.

So for those who are using Oasis montaj and Target,

you could access this data and a huge wealth of geoscience

information via Seeker.

The name of today’s dataset,

or what it’s called is the Southern Glennie project.

It was collected in late 2019

and early 2020 by Geotech.

And for those who are aware,

it is a VTEM max system.

Just a quick comment about the project area,

where the project area is located in Northern Saskatchewan.

So just to locate ourselves,

my apologies for the quality of these images

they were just taken from the report.

This is Saskatchewan, we have Lloydminster, Flin Flon,

and we have La Roche, and this is Lac La Loche here.

The crew is situated in Lac La Loche,

and this is the actual project area.

The geophysical survey data that was collected

was airborne magnetic and time-domain electromagnetic data.

There was a total of 6,500 line kilometers that covered

approximately 1,100 square kilometers.

And just for perspective, this is 80 kilometers end-to-end.

So it’s a pretty large exploration area.

So why are we talking about magnetic data today?

Well, in Canada, we’re so lucky.

Most of Canada is covered with high quality magnetic data

and Natural Resources Canada

and the various provincial governments and organizations

are always adding new datasets into the mix,

just like this one.

But really why magnetic data?

Well magnetic data is a cost-effective way

to map geological and geophysical environments.

It can be acquired on the ground,

it can acquired in the air

through airplanes, helicopters, UAVs,

and it could also be collected in marine environments.

So pretty much anywhere on earth

and it’s very cost-effective.

Magnetic data ultimately allows us explorers,

geoscientists to map and interpret geological features,

faults, dykes, contacts, intrusive bodies.

Magnetic data is a great structural mapping tool,

and it’s really one of the common denominators

in many exploration products.

Okay, I’m just going to jump into the application now.

I’m just going to jump into Oasis montaj.

I’m also just going to turn off my webcam

just to save a little bit of bandwidth.

So we’re actually going to start at the end.

We’re going to start at the end product

and then we’re going to kind of build towards it.

So what we’re looking at here is a 3D view

of our project area.

The overlay image in the background here,

this heat map, is a structural complexity heat map

that we’re going to create from our magnetic data.

The areas that are red or hot in color represent areas

that have a high structural complexity.

Then that means there’s lots of lineaments

and faults and folds that are intersecting each other

at a number of angles.

The black dots here represent all of the known mineral

occurrences within the project area.

I’ve downloaded these

from the government of Saskatchewan website,

and I’ve just imported them into Oasis montaj.

So predominantly in this area,

we have a number of known gold,

copper, pyrite mineralization.

We have a little bit of rare earth elements here as well,

and then as well,

gold on the Western side of the project area.

And underneath this,

we’ve done a magnetic inversion,

a magnetic vector inversion.

And these are some of the ISO surfaces from that inversion.

So this kind of what we are building towards.

So let’s jump into our project area.

So this red outline represents my area of exploration.

How do we get going?

Well, in Oasis montaj,

we can get into our data services menu.

And one of the first things I like to do is import

a satellite imagery through Bing Maps.

You’ll see that it loads very quickly,

and it just gives us a nice foundation base map,

for the project area.

After this, I can jump into Seeker.

And once I click the Seeker button,

this little pop-up is going to appear

and it’s grabbed the corner points of my map

or my area of interests,

my area that I’m exploring,

and it’s drawn this red box here.

I can resize it.

This is an area that I’m going to search

for public domain geoscience data.

Once I’m ready to click Search,

I can click the Results button.

So we can see that I’m connected

to the Natural Resources Canada Geoscience data portal.

There’s a huge variety of public domain data

that’s available across the country.

There’s also a number of other public domain

geoscience servers, including the Geosoft DAP Server

that serves a high resolution,

topography, magnetics and gravity information.

In this case, I’m just going to jump into the magnetics.

Radiometrics EM folder, jump into surveys

and here’s our project area.

And we can see a large number of survey deliverables.

I can click on a product I’m interested in.

I’ll get a quick preview of it.

And when I’m ready, I can just click Download,

and then download it to my project.

So right now my computer is reaching out

to the Natural Resources Canada’s server

and it’s downloaded

the total magnetic field data directly into my project.

It’s geo-referenced correctly.

So I don’t have to worry about referencing my data.

So one of the most important things

that we do in geophysics is visualizing

the data that we’ve collected.

And we call this technique gridding.

Gridding, it’s such an important thing,

but we don’t talk about it a lot.

It’s one of the key deliverables

that we provide our colleagues, our clients, our management,

and it’s really how we visualize our data.

Now, what are the challenges that we have

with magnetic data and geophysical data

is being able to honor the data

and honor the geological information

that we’re collecting or mapping.

And I’m just going to show you just a quick example.

On the top of the screen here,

we have a grid of this very data we’re looking at

that was created

using the minimum curvature gridding technique.

The minimum curvature gridding technique

is a great technique.

It’s been around for a while,

it’s really fast, it’s robust,

it allows us to visualize data really quickly.

But one of the challenges that has is

it doesn’t allow us to enforce trends in the data.

So you can see that this magnetic dataset

has a lot of magnetic lineaments,

that are striking at different directions.

We have some east-west trending information.

We have some that are oblique to the survey lines.

Some that are perpendicular to the survey lines.

We have some circular features,

really minimum curvatures struggles a little bit with this,

and we can see some of this rippling

or broader nudging effects in minimum curvature data.

With the latest release of Oasis montaj 9.9,

we’ve included a new gridding technique

called the Multi-Trend Gridding technique.

And what this does

is it seeks out trends in your geophysical data,

and it tries to better honor that data by connecting them.

The great news is we don’t need to insert a specific trend

or strike direction.

The algorithm will simply do this for you.

So on the bottom here,

we have an image of the multi-trend gridded dataset.

This is the exact same dataset,

gridded at the same cell size.

So we don’t see a lot of this

sort of like broader nudging effects

or the string of pearls or rippling that we see

in minimum curvature gridding techniques.

So just to really highlight this,

if we try to work with this data,

the minimum curvature data,

and we try to do some data transforms,

let’s say we try to do a very simple

first vertical derivative.

Okay, so this broader nudging and rippling effect

really kind of stands out

and especially structure that’s oblique to the survey line.

When we use the Multi-Trend Gridding technique,

we can really preserve our efforts

and the hard work that we’ve done to collect process

and reduce the data.

And when we do higher order products

and we do derivatives, transforms,

we really eliminate some of these

sort of gridding artefacts from the data.

So if you are working

with potential fields geophysical data,

I would certainly recommend you

and your team check out the latest edition

of Multi-Trend Gridding,

on your magnetic dataset and just compare for yourself.

So I’ve already mentioned,

and we’re already looking at some data transforms.

So let’s take a look at

the new 2D Filtering tool within Oasis montaj.

One of the most common things

that we can do with magnetic data are transforms.

So we can take our total magnetic intensity data

and transform it into a higher order,

more valuable interpretation product.

So the first thing I’m going to do is click 2D Filtering,

then MAGMAP Filtering.

I’m going to provide it my total magnetic intensity,

multi-trend grid.

That was the grid that we were just looking at here.

And what we’re going to do

is we’re going to do just a first vertical derivative,

and I’m going to just click Create Filter.

What’s great about this tool

is that it is completely interactive.

So on the top right-hand corner here,

we have a map of our total magnetic intensity

across the survey area.

The areas that are pink or hot in color

represent the areas of a high magnetic intensity.

The areas that are blue or cold

represent an area that has a low magnetic intensity.

This is our data, and we can move around in here.

We can see the coordinates

and the values where I hover over.

As we move into the left-hand side of the screen,

we see a power spectrum of our data.

This is incredibly useful

if you are going to be applying filters to your data.

So let’s go ahead and do that.

The first filter I’m going to apply,

you’ll see once I click this,

I have a huge list of filters that I can apply.

Each one sort of has its own purpose.

For the sake of today’s presentation,

I’m not going to go through all of them obviously,

but I’m just going to focus on one of them

that I’d like to use,

it’s called the Gaussian regional residual filter.

The second I select this filter, a few things happen.

We see our original power spectrum here in black,

and we can automatically see

the filtered power spectrum in red.

We can also see the filter response here in blue.

What’s even better is that we have an automatic preview

of our filtered results.

So if we want, we can make changes to our filter.

We can make this a low pass filter.

We can adjust the filter cutoff wavelengths,

and we can really kind of play an experiment with our data

unlike we’ve been able to before.

So I’m just going to apply a 1, 500 meter wavelength cutoff,

and remember I’m going to apply it as a high pass.

And what this is doing is passing through

all of the short wavelength and near surface content.

And you can see that we’re extracting a lot more texture

and a lot more fabric from our magnetic data.

If we want to do even more,

I can add another filter so we can stack our filters

and run them sequentially.

So now I’m going to do a derivative.

So what we’re looking at here

is now the sequential application of the residual filter

and the derivative filter.

What’s great is I can look at a single one of these,

if I want to interrogate a specific area,

I can zoom in if I want,

I can zoom into an area of interest

and I can look at the derivative product,

or I can look at them combined.

When I’m ready, I can just click Okay,

and create that product.

And the whole process runs pretty quick.

Again, this is a pretty large project area.

So now we’ve created a higher order interpretation product.

We’ve stripped away some of the deeper structure,

we’re focusing on near surface structure.

We’ve really highlighted all the lineaments

in this dataset,

and we’re getting a lot more of the fabric

which is going to be useful in our next step.

So the next thing that we’re going to do

is we’re going to do some grid texture analysis.

So inside of Oasis montaj,

there’s an extension called the CET Grid Texture Analysis.

And what this allows us to do is extract the fabric

and lineaments from our magnetic data.

So we have a number of options.

We can select the highs or the lows,

the peaks and the troughs,

or perhaps we’re interested in the edges,

the contacts of the magnetic structure.

Following this, we have a number of ways to refine this.

So we can say we’re only interested

in lineaments in the Northwest direction

or the South direction.

We can do some thresholding.

So maybe we want to say,

we only want lineaments of a certain length.

Maybe we only want lineaments that are major,

so of a certain amplitude.

So we can really do some quality control and clean up

some of the structure.

So the grid that I’m showing you now,

this pinkish-blue grid is the extracted fabric,

the extracted lineaments from our magnetic datasets, right?

So we’ve extracted so much more information

than just working

with just a total magnetic intensity dataset.

And what’s great is we can now display this information

as lineaments on my map.

So now these are actual vector lines.

We can take these, we can export them into other packages

if we want,

we can now create higher order products.

Now really I’ve seen people do it and I’ve done it myself.

We’ve drawn these by hand

and you can imagine how long it would take

to do this by hand.

the CET tool and the grid texture tool

allows this process to be automated

and reproducible among your team.

So you can say, “Hey, I’m looking for something

that’s at least a kilometer long,

and has this characteristic and this direction,”

Not using an automated texture analysis tool

is just takes a long time.

So one of the cool things

that we can do with our grid texture analysis

is we can create what we call a structural complexity map.

So we can seek within our project area,

we can look for areas

that have a high density of lineaments.

And also areas that have contacts

or overlapping lineaments, or faults or dykes

and those intersections that have a wide degree

of angular variation.

So for example, in here we can see it’s quite complicated.

We have faults and lineaments

that are intersecting at various angles.

And we know that in mineral exploration,

these are often areas

where we may want to look for minerals.

So using the Grid Analysis extension,

we can create this heat map.

The colors that are are red or hot in color represent areas

that are structurally complex.

And you can see here, this area that is blue

has a very low structural complexity.

Again, just overlaying the known mineral occurrences

within the project area.

I can zoom in to the Eastern side of the project block here,

and I’m just going to turn off the trendlines,

just so it’s a little more obvious.

We can see all of the known mineralization from the project,

from the Saskatchewan government.

We have all our gold occurrences, copper occurrences.

We have some pearl, we have some on the edges here,

which is okay, we have copper and zinc.

Again, there’s a pretty high correlation

even this sort of weakly structurally complex area.

We have some correlation

between the known mineral occurrences

and the structural complexity map.

Again, we’re just trying to begin

to vector our exploration efforts.

So what else can we do with our data?

How can we take this really to the next level?

Well, what we can do is perform a geophysical inversion.

Within Oasis montaj, we have VOXI.

and VOXI is our geophysical modeling tool.

It allows us to easily set up

and run geophysical inversions.

We can also integrate other information such as geology

or geophysics or other geoscience information

to connect these calculations

to our real-world magnetic measurements.

So within VOXI, we can import our magnetic data.

We can very easily build a subsurface mesh,

and once we’re ready to run the inversion,

I can just click this green button to run the inversion.

What’s great about VOXI

is that it uses cloud compute technology.

So the calculations don’t happen on your machine.

Your data is encrypted and compressed

and sent to the cloud for calculations.

So normally performing a magnetic inversion on an area

like this may take one or two days on a single machine.

The results from this area were ready in about half an hour,

and it gave me more time to think about the results

and not about the calculations.

So we can use this magnetic data

to produce a 3D model of magnetization

or susceptibility of the subsurface.

In this case, I’m running a magnetization vector inversion,

and this is a specialized type of inversion

made available through VOXI.

So let’s take a look at some of these results.

So again, we started with our magnetic data,

we performed some data transforms

to extract a lot more of the fabric from it.

From after this, we did some lineation detections.

So here in 3D we can see all of the faults and lineaments

and trends throughout the project area.

Again, I’ve plotted in the known mineral occurrences

as these black dots.

And we’ve gone ahead and we’ve performed

a magnetization vector inversion,

or we could have also done

a magnetic susceptibility inversion.

And that’s going to give us a lot more information

about the orientation of the magnetic body

below the surface,

as well as this physical rock property,

magnetic susceptibility.

And we can integrate these results.

We can integrate the known mineral occurrences,

the structural complexity maps,

and our inversion results

to better vector our exploration results

in a greenfields environment.

So we covered a lot of ground today.

We started off, I showed you a great place

for you to download and access

all sorts of geoscience information.

Even if you just need a quick topography

for your project area, it’s a great place to start

along with some of the satellite imagery.

After that, we took a quick look

at the new Multi-Trend Gridding technique

and how it really excels

at visualizing potential field data,

especially data that has lots of multiple strike angles

that conventional gridding techniques really struggle with.

After that, we took a look at our new 2D Filtering tool,

which isn’t great interactive way to allow you to explore

and extract more from your magnetic data.

After that, we went into our Grid Analysis tool,

we extracted the fabric from our tool.

We created a number of lineament maps

we created a quick structural complexity map

and compared that to known mineralization.

And to wrap it up,

we imported this data into VOXI

and we performed a 3D magnetic inversion.

So I’d like to open up the floor now

to anyone if they have any questions.

So I just want to say thank you for your time.

And also if you’re interested in what you saw today,

and you want to talk about how these techniques

can be applied to your project, in your magnetic dataset,

feel free to reach out to me or any of my colleagues here

or at the PDAC.

<v Narrator>Hi, Geoff, thank you for that really</v>

comprehensive walkthrough of lots of different methods

and techniques that can be applied to our magnetic data.

I do have a couple of questions and comments here.

Start with a question.

The first question for you

is actually not related to magnetic data,

wondering what can be done

with the time domain electromagnetic data collected

with the survey in terms of improving understanding

of this exploration project.

<v Geoff>Yeah, that’s a good question.</v>

Yeah, so for those in the audience that are aware,

the geophysical survey that was collected,

the geophysical data that was collected was magnetic data,

but also time-domain electromagnetics.

The great news is inside of Oasis montaj

we have EM Utilities

that allow you to work with time-domain data.

So we can do some filtering of time-domain data,

some visualizations, calculate decay constants.

But better yet we also have VOXI, the geophysical inversion

and modeling engine inside of Oasis,

has the ability to work with time-domain data.

So we have the ability to do both inverse

and forward calculations in 1D and 2.5D.

So what you’re looking at now are the VOXI inversion results

from that TDEM, time-domain EM dataset in three dimensions.

So again, it’s all about trying to extract more

from the data that was provided.

So being able to do the inversion

and come up with a 3D conductivity model

will certainly help advancing exploration project.

Hope I answered that question.

<v Narrator>Yeah, thanks for that Geoff.</v>

I have another question here.

So this is the Grid Analysis tool.

You did a nice demo of the Grid Analysis functions

on the magnetic data,

but are you able to apply the grid texture analysis

on other types of geophysical data or geoscientific data?

<v Geoff>Yeah, good question, yeah, we can.</v>

So the Grid Analysis tool,

I mean, it doesn’t know that you’re inputting magnetic data.

I think it was originally designed

to work with magnetic data,

but really I could apply or use a Time-Domain Channel,

or apparent conductivity, Depth Slice

and feed that into the grid texture analysis tool

and extract those lineaments in the exact same way

that I applied it to the magnetic dataset.

So yeah, it could be applied

to really any type of gridded data.

<v Narrator>Great, yeah, so applications beyond</v>

just the magnetic data that we saw today, that’s great.

Okay, let me see if there are any other questions.

I think that was the last of our questions

here today, Geoff.

<v Geoff>Okay, well, great.</v>

I just want to thank everyone

for their time today, much appreciated.

And again, if you have any questions,

feel free to reach out.

Thank you very much.

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