A validação faz parte integrante do processo de modelagem geológica para garantir um modelo robusto.

Com o Leapfrog Geo e o Central, você pode criar fluxos de trabalho totalmente integrados para sua equipe. Inclua dados ou revise suas interpretações em qualquer fase do projeto, e essas mudanças serão aplicadas no final sem a necessidade de realizar nova configuração (scripting/programação) para atualizações e validações mais rápidas e tomadas de decisões eficientes.

A validação faz parte integrante do processo de modelagem geológica para garantir um modelo robusto. Com o Leapfrog Geo e o Central, você pode criar fluxos de trabalho totalmente integrados para sua equipe. Inclua dados ou revise suas interpretações em qualquer fase do projeto, e essas mudanças serão aplicadas no final sem a necessidade de realizar nova configuração (scripting/programação) para atualizações e validações mais rápidas e tomadas de decisões eficientes.

Junte-se a Jillian James (Geóloga de projetos) da Seequent para discutir:

Validação da sua base de dados de furos de sondagem;
Problemas de validação visual;
Uso de ferramentas estatísticas do Leapfrog para validar seu modelo;
Uso de filtros de consulta para testar áreas do seu modelo;
Upload para a Central, para revisão por pares e validação final.

Visão geral

Palestrantes

Jillian James
Geólogo de projetos, Seequent

Duração

23 min

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Vídeos

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Transcrição do vídeo

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<encoded_tag_open />v Jillian<encoded_tag_closed />Hi, everyone.<encoded_tag_open />/v<encoded_tag_closed /><!– wpml:html_fragment –>
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Thank you for taking the time to join me today
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for this Tip Tuesday on validating your Leapfrog Geo model.
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My name is Jillian James,
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and I’m a project geologist here in Seequent’s Perth Office.
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Seequent has a range of software
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for use throughout the exploration and mining value chain.
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Today, the focus will be on the functionality
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in Leapfrog Geo with a brief introduction
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to Seequent Central.
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The key aims of this session
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are to give you some tips and tricks
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on how to validate your Leapfrog Geo model
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and make validation an integral part of the modeling process
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rather than just an afterthought.
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In this session, we’ll cover:
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how to check the data feeding into your model is validated,
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tips on section by section validation,
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how you can use Leapfrog Geo statistical tools
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to validate your model,
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how you can use query filters to test areas of your model,
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for example, if you want to test where the model was barren,
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but the grades are above a certain value,
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where the model was mineralized,
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but the grades are below a certain value,
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and where the geology log does not match the model geology.
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Finally, we will look at how to upload your project
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to Central for peer review and final validation.
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The most important step in validating any geological model
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is to check that the data
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feeding into the model is validated.
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Remember, rubbish in equals rubbish out.
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Things you should check include looking to see
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that all the data is included in your project,
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including any unmineralized holes,
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understanding the impact that missing
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and null values may have on your model,
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and how the replacement rules are being implemented.
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Are there any extreme outliers, highs or lows,
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in your dataset?
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Does the data look to be in the correct spatial location
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relative to things such as development and topography?
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And are there any duplicate points or overlapping intervals?
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Leapfrog Geo automatically identifies and flags
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common data errors when data tables are imported.
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Until errors are corrected,
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the rows that contain those errors are excluded.
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For example, if the ID for a color
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contains an invalid coordinate,
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that color will not be displayed in the scene
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as its location is not known.
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This will also affect any downstream processing
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and it will ignore any data associated with this drillhole.
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We will now move into the software
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to look at this in more detail.
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This session will not cover building domains from scratch.
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So throughout the demonstration,
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I am going to make use of a project already created
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using the saved scenes to show the functionality.
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I’m going to use a dataset from a real underground goldmine
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that has since been mined out.
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Data locations and names have been changed
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to keep the project anonymous.
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Although I am demonstrating this functionality
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with respect to our underground narrow vein gold system,
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these validation tools can be useful
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in almost any deposit style or geological setting.
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If you need help with your individual project,
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please don’t hesitate to contact
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our friendly support team to assist you.
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I will begin with validating the drillhole database.
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Over in my project tree,
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you can see I have a diamond drillhole database here
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and I’ve imported all these various table types
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to build my database.
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The red exclamation marks here on my assay, geology,
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and vein codes indicate that there is possibly an error.
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The orange exclamation mark on my survey
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indicates there is a warning.
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The blue downward pointing arrow
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indicates that the data has been imported correctly
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and there is no errors to fix.
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To fix an error, I right-click on one of these tables
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that has an error and select fix errors.
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This will open up a new tab
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and it will show me where these errors are occurring.
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This assay table actually has no errors,
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but it has some invalid values handling.
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If we look at this AU_PPM one,
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we can see that some rules have been applied
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to the non-positive values.
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So by default, it is going to replace them with 0.01.
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However, other rules have been applied
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for other values with the general rule of thumb
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usually replacing them with half the detection limit.
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Leapfrog Geo identifies a range of common errors
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and all errors identified are grouped by type.
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You can click on any error
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and expand it to find out more information.
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Some errors will involve you
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going back to the original database and fixing them
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and some errors can be ignored within Leapfrog Geo.
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Once the errors in the database are fixed and validated,
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you can be sure your model will have the most up-to-date
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accurate data feeding into it.
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Next, I can check that my drillhole data
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that I have imported is in the correct location
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to some of my features such as my topography
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and development drives.
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I can rotate in the 3D scene
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to check for any error in the survey data
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and ensure my drillholes are where I expect them to be.
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Using the slicer tool,
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I can then look at validating my model
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on a section by section basis.
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Here, I’m looking down on a Z section at the 852 RL.
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This shows that my mineralization model
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is following these development drives.
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If I step through a few more sections
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using the greater than or less than keys on my keyboard
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on a set step width,
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I can see the model changes at other RLs
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and how this matches my development.
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Alternatively, I can do this process
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on a vertical cross-section.
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Here, I am looking north through a slice of my model
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with development drives and drillholes.
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If I stepped through my model using the greater than
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or less than keys on my keyboard,
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you can visually validate that your model
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is matching those development drives
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and following any drillhole logging or assays.
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This method is one of the more traditional ways
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to validate a model and it can be quite time-consuming.
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Leapfrog also has some other unique tools
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that help you identify areas of your model
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that may require further investigation.
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The first tool I will show you
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is the correlation statistical tool.
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This shows you the correlation between the model geology
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and the log geology.
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To do this, you need to evaluate your mineralized model
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and your geological model onto your drillholes.
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You do this by right-clicking on your drillhole database
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and selecting new evaluation table.
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I have already completed this process
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and if I bring this evaluation of my mineralized domains
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into my scene and have a look,
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you can see it shows me
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where my mineralized domains are on my drillholes.
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Once I have a evaluation table set up,
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I then can come to their evaluation in my project tree,
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right-click and select statistics.
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This will bring up a correlation statistics table
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showing me my drilling lithology, my drilling length,
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my matching length, matching percent,
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non-matching length, and non-matching percent of my model.
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In this example,
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I’ve shown this for the mineralized vein system,
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but this can also be used to test an entire geological model
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to determine where more refinement is needed.
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Alternatively, you can create a merged table
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of your evaluated domains with your original assay data,
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and then look at the statistics
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to help validate your domains.
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You do this up here in the drillhole database,
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right-click on your drillholes and select new merged table.
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Again, I’ve already created this
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where I’ve merged my vein lithologies for my domain
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with my gold grades.
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I think can right-click on this table and select statistics.
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You then can choose which type of statistics
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you want to look at.
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Firstly, I’ll look at this table of statistics
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and this will open up a new tab showing you your domains
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with the mean grade, standard deviation, variance,
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and quantile data for each of your domain codes.
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You can also do this for a box plot.
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Again, right-click on your merged table, select statistics,
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choose the box plot option
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where you can view each of your domains as a box plot
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to get a visual indication of where any outliers are
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within your domains
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and the main grades of each of these domains.
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I’ve applied a log scale to this chart
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to help see this better
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as the status here is very negatively skewed.
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I can also have a look at the histogram of a single domain.
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This will allow me to examine the data distribution
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within the domain and check it’s forming a population
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that meets the assumptions of stationarity.
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This is where the mean and variance
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do not change across the domain
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and will enable it to be used in downstream estimation
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or numeric modeling.
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To do this, I come to the merged table, open it up,
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and come to the numeric data of interest,
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right-click and select statistics.
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This will open up a new tab
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showing us the histogram of the data.
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Here, I can apply a query filter.
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I’ve built one just for this 4,400 domain
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so I’m only looking at the data within that domain.
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I can then detach this
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and have a look at where some of the anomalous grades
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are occurring in my scene view.
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I will hide some of these estimation domains
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and demonstrate how you do this.
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So if I feel anything above this area was anomalous,
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I could highlight and then I could have a look in my scene
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to see if that is actually sporadic
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or is it forming another domain population.
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In relation to this 4,400,
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if I turn that on and turn down the translucency,
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I can see that this is pretty sporadic across my domain.
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I can reattach that tab
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and then I can also look at the histogram of the log
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or the cumulative histogram.
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Once you have a merged table
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of your evaluated domains with grade,
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you can then utilize query filters
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to test things in your model.
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Here in my scene, I have applied a query filter
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to show me where there are bearing grades
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included within my mineralized model.
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I’ve created this query filter
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by right-clicking on my merged table
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and selecting new query filter.
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I’ve previously built this so open this one up for you
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and you can see the syntax applied to build that query.
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We also have the easy build query function
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where you can come in and apply your query.
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Here, I’ve selected where my AU_PPM
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is less than or equal to 0.3
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and my estimation domains
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are within these four domains shown.
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We also have the advanced query filter builder
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that you can utilize for your project.
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Once I’ve built my query filter,
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I can drag and drop that in the scene
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and that query will be applied.
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You can also apply the query filter
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over here in your properties.
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If I zoom in and look around my project,
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I can now see areas that I need to go and investigate
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to understand why these barren grades have been included
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within my mineralized model.
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Next, I can use a similar process
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to test where I have mineralized grade
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that has not been included in my mineralized model.
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Here in the scene,
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you can see I have applied this query filter
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and I’ve built it by right-clicking again,
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selecting new query filter.
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And if I come into my prebuilt query filter, open that up,
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you can see I’ve done the reverse of our first one
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where I’ve said if it’s greater than or equal to 0.3
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and it’s not in our domains,
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then it’s considered mineralized outside of the domains.
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This is then being applied in my scene.
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And in this example,
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you can see there’s quite a lot outside my model.
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That is because there is actually quite a few
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unmodeled domains in this project.
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You can also use query filters to test areas of your model
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to see where geology code logged
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does not match geology modeled.
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To do this, I’ve created an evaluation of my host rock model
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and merged that with my geological lithology table.
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I’ve then built a query filter here
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to test where my end site is outside my model.
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If I have a look at my scene,
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I can rotate and zoom in on some of these areas,
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click on a hole and I can go and investigate
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why that is outside that geology unit.
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If I did want to examine a hole in more detail,
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I can use the drillhole correlation tool
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here under my drillhole database
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to examine in further detail.
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I right-click on this and select new drillhole set,
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which brings me out to a new drillhole set tab.
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I then select the pit color function,
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which will take me back to my scene view.
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I then choose my select drillhole button
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and choose the hole I’m interested.
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I then can click save
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and then it would appear here in my drillhole set layer
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where I can bring across my host rock
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model
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and my original logging.
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And then I can come in and identify
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why I have these different areas
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within my model versus my logging.
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The final validation step for any project
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is always to have your project peer reviewed
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by one of your colleagues.
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To do this, we are going to use Seequent Central.
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I will show you this briefly.
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However, we have another webinar on this
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that was completed earlier this year
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by one of my colleagues,
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so please feel free to check out this video recording
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on the Seequent website.
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To upload your project,
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you will need to be connected to the Central server.
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You can do so by connecting up here
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in your right-hand corner.
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Once you are connected, you select publish.
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You select which objects you would like to appear
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in your online web browser.
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Select next.
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Set your project workflow stage.
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I’m going to choose peer review for this one.
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Select next.
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Add in any revision notes for your colleagues
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and then select next to start the publish and upload.
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Once your project has finished publishing,
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it will say publish successful here in the dropdown menu,
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and it will be available for your colleagues to download
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if they have the right permissions and access to Central.
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It is also now available via the web browser
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for non-Leapfrog Geo users such as managers
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to review via Web-Verse and make comments.
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To do this, you can select go to portal
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and this will take you to the appropriate web browser
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where your project is stored.
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As you can see, it’s got the revision note
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saying please review this project.
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It’s got the stage of peer review
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and it’s got the user who uploaded that project.
[00:21:30.260] 
You can then select the project
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to view within the web browser,
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come to your geological model,
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open up your domains and have a look at these
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without needing access to a Leapfrog Geo license.
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Comments can then be made by clicking on this comment button
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and selecting add comments.
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These can be geo tagged on your domain
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and you can tag your colleagues here
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so they get an instant notification
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on any area to go and look at in further detail.
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That brings me to the conclusion of today’s webinar.
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If you require any further information,
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please refer to the Seequent website,
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which has many blogs, webinar recordings, and videos
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to help you with your learning.
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We also have a great series of free online courses
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to help up-skill which can be found
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under your MySeequent account.
[00:22:47.040] 
If you do need any additional help,
[00:22:49.520] 
please reach out to your local support team
[00:22:51.610] 
who will be willing to assist.
<wpml_invalid_tag original=”PHA+” />[00:22:57.670] 
Thank you.

Terça-feira técnica: Validando seu modelo geológico com o Leapfrog

A validação faz parte integrante do processo de modelagem geológica para garantir um modelo robusto.

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