We look at modern TSF management practices centered at the digital twin of the site, seamlessly integrating monitoring and modeling.
Overview
Speakers
Pieter Neethling
Segment Director for Mining Operations – Seequent
Duration
22 min
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Learn moreVideo Transcript
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(gentle music)
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<v Janina>Hello and welcome everyone.</v>
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Thank you very much for joining us today
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at our Seequent presentation.
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My name is Janina Elliott.
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I am Seequent’s Global Central Technical Lead,
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and I’m joined today by Jennifer Biddlecombe,
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our Senior Account Executive for North America.
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And the two of us are part
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of Seequent’s tailing solution team,
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and have the immense pleasure to moderate today’s talk
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on The Role of Dynamically Updated Digital Twin
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in a Modern Tailing Storage Facility.
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At the end of the talk, we will make sure to address several
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of your burning questions regarding the resolution.
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But in case there isn’t enough time,
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rest assured that we will provide you with an answer
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just after the webinar via a personalized email.
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So with no further ado, I’d like to introduce our colleague,
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team leader and speaker for the day, Pieter Neethling.
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Now, Pieter, as the Segment Director for Mining Operations,
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Pieter is strongly focused
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on making Seequent’s Geoscience Portfolio more relevant
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to production geologists and environmental experts.
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And through his focus growth, and this focus growth,
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he aspires to solve essential operational challenges
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centered on safety and productivity workflow improvements.
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Now, Pieter has more than 30 years of experience
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in the mining industry with varying roles in operation,
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including lead positions in consulting
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and mining technical services
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at multiple top tier organizations.
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But a special interest and passion of Pieter’s
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has always been the safe development and maintenance
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of tailing storage facilities.
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And this is the focus for his talk today.
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Okay, over to you Pieter, here we go.
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<v Pieter>Thank you for the introduction Janina.</v>
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Hi everyone.
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Today I’m going to talk to you about the value
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of a dynamically updating digital twin,
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and the role it might play in mitigating potential failures
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of tailings storage facilities.
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Before I progress with the presentation,
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I would like to make a statement
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of confidentiality and disclaimer.
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Please note that the presentation
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is for informational purposes only,
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and it’s not a commitment
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to deliver software features or functionality.
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And now for some context for why digital twin
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becomes so important.
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The mining sector is increasingly exposed to environmental,
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social and governance compliance.
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And the need to comply
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with the associated regulatory frameworks
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has necessitated a shift in the way the industry
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manages risk and adheres to responsible mining practices.
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Investors also want to ensure that their money is used
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in a sustainable and responsible fashion,
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as evidenced by the signatories
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to the Principles for Responsible Investment.
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Greater transparency entailings management disclosure,
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and working with industry
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and community regulatory and financial stakeholders
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to promote the application of consistent disclosure
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that informs better tailings than stewardship,
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has become a key operational objective.
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These social economic and political risks,
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along with the need to digitally transform the industry,
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means everyone is talking about tailings.
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Recent events have reminded us
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that more work needs to be done
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to increase dam resilience and due diligence.
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To truly be able to learn from a failure event
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and fulfill the ultimate goal of the global standard,
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it is essential that there is complete transparency
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regarding the chain of events.
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All data analysis and decision-making processes
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need to be clearly understood.
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However, to achieve this objective is easier said than done,
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with people, processes and technology challenges
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core to mitigating the risks
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and embedding a cohesive safe tailings management solution.
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Let’s take a look at some of the challenges.
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Complexity comes in many forms and here are a few examples.
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Monitoring and understanding of data and systems
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for some of the largest man-made structures on earth,
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and that these are evolving structures
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makes this inherently challenging.
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The changing factor of safety, at a TSF as it evolves
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is a major concern.
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And scenario testing, to help predict potential failure,
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as a TSF evolves with time, is a significant pain point.
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The monitor to model to design workflows are by and large,
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still unnecessarily complex.
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This consumes resources and introduces risk.
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And finally, there are a host
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of multi-stakeholder collaborations to manage.
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Technical teams that we have engaged,
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believe it’s not just data and file incompatibility
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that is an issue.
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But also the lack of multidisciplinary interaction
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and comprehension that is a cause for miscommunication.
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Our conversations with senior management
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find a common thread
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where reporting on all of their storage facilities
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that are at varying ages, conditions and locations,
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particularly where there is little standardization
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in how the structure is being monitored is a major issue.
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They agree that their teams waste a lot of time struggling
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to get the data into a useful and consistent format.
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Managers are therefore not fully confident
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that they are delivering a comprehensive picture
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of all of the assets and the problems are not being missed.
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So how is Seequent helping tackle these challenges?
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The key to any solution is that it provides the means
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to work effectively as a team and ensure data transparency.
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These are the underlying principles that allow
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for a robust review and decision making process.
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But how is this accomplished?
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Firstly, all stakeholders in the project,
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were the modelers from different geoscientific groups,
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project managers, or third parties such as consultants
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and JV partners need to have access to the latest data
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in as near real time as possible.
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Secondly, everyone needs to work collaboratively
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from a single source of truth to create up-to-date models
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that facilitate the development of a digital twin.
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A robust monitor to model to design workflow
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bridges the gap between typically disconnected monitoring
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and technical analysis workflows.
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The sequence TSF solution, a continuous modeling paradigm
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is established that solves the data management
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and multi-stakeholder conundrum,
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and centers activities on as-built performance
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and failure prevention with good communication,
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a key success factor.
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Core to our solution is Seequent Central,
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a cloud hosted model and data management system,
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with web based visualization capability
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that facilitates collaboration.
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Seequent’s modeling suite comprises Leapfrog,
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Oasis montaj and Geostudio,
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all of which addresses the modeling and analytical needs
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of geologists, geophysicists and geotechnical engineers.
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Seequent works to provide the best of breed solution
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by working with partners and their products.
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For example Esri.
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Modflow and Feflow for flow modeling
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are examples of industry standard products
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Seequent’s TSF solution works with.
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In combination, the outputs define a live digital twin
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and completes the monitoring to modeling
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and design workflow.
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Let’s take a look at the role of our expert applications
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in a little more detail.
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Geophysical methods from the ground, air and satellite
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provide efficient remote sensing of TSFs.
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Geophysical methods are a great way to see non-intrusively
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into the subsurface and provide information
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on say water content.
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These methods can easily be repeated at regular intervals
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over the same area,
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giving a great reference point for monitoring changes.
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Permanently in place systems are also on the market.
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These dense data collection techniques are superb
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for filling in between physical measurements.
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Like piezometers, basically guiding the construction
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of the 3D digital twin and making it more accurate.
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The geological model forms the foundation
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of the digital twin, where continuous assessment
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of the altered rock, tailings depositions,
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along with the structural discontinuities
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can impact the physical structure.
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The geological model with the hydrogeological
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and geotechnical analysis are inseparable
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from a robust workflow, and to fully understand changes
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in the foundation characteristics of the structure.
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More specifically, it is typical
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that geotechnical model domains
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and their associated soil and rock designed parameters
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are attributed to geological model domains.
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This generally means a geotechnical model
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is only as good as its geological model,
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with the geological model playing a significant role
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in informing geotechnical design parameters.
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In summary, an accurate representation
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of the geological conditions
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is fundamental to developing optimized tailings solutions,
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particularly at the design stage.
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This adds significant value and cost savings,
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both at construction and during ongoing maintenance
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over the lifetime of the tailings facility.
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What is key to the stability of tailings?
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Water management is one of the biggest challenges
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for managing the tailings facility,
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especially those using wet transport and deposition.
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The hydrogeological extension provides an efficient
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and robust workflow for transferring the model
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in the digital twin to Modflow and Feflow,
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including importing results back into the digital twin.
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This saves time and effort
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as well as facilitates a regular update
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of the forward-looking analysis for TSF behavior.
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Geotechnical analysis is the key
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to understanding factors of safety and reliability.
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Geotechnical analysis is an integral part
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of modern TSF design and management.
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The analysis is used not only to provide insights
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on deformation, consolidation
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and stability at the design stage,
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but to adapt the design to actual conditions
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during construction based on the interpretation
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of monitoring data.
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As such, the key benefit of geotechnical analysis
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within the digital twin lies in the ability
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to make informed decisions about the immediate
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and forward looking performance of the facility.
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A dynamically updated digital twin of the physical system
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ensures knowledge transfer
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throughout the history of the site,
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meaning that decisions are intentional rather than reactive.
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The importance of a geotechnical digital twin
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was recently highlighted at Seequent Lyceum
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by a colleague of mine.
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He presented the findings
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of a retrospective numerical simulation
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of the construction history
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of the Mount Polley Tailings Storage Facility.
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The simulation, as seen in this video,
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incorporated a thin layer of clay
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that exhibited strength loss during deformation.
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The simulation revealed a repeating pattern
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at each stage of construction,
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the excess pore water pressure generation, dissipation
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and equilibration of the flow system.
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More importantly, each stage of construction
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was associated with a change in strength
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along the developing rupture zone.
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The strength varied between peak and residual
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right up to the point of failure.
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All it took was one additional bump
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at that stage of construction
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to cause full strength loss in the clay,
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resulting in a catastrophic failure of the entire facility.
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A key realization was that deformations of the TSF
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were negligible up to the point of collapse.
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As such, monitoring would not have been diagnostic
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of the impending failure,
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which highlights the need for a geotechnical analysis
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as an integral component of the digital twin.
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We can easily imagine how a dynamically updated digital twin
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with version control, multiple realizations of the geology
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and a single source of truth, whatever for the engineers
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to explore different physical phenomena
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as the facility evolved.
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Moreover, the digital twin could have been passed down
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from the outgoing to incoming engineers of record,
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allowing the knowledge transfer to be unbroken.
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So in summary, when we assess what is required
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to manage tailing storage facilities safely,
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and the requirements of the global tailing standard,
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teams have to think about holistic design.
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The digital twin becomes the basis for design
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used at all phases of the project life cycle.
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Development of the digital twin forces the engineers
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to understand the physical system
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and make informed decisions
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about the facility’s performance as it evolves.
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A comprehensive digital twin
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that consistently incorporates changing data
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and evaluates all spatial, numeric
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and intellectual information in a 3D plus temporal context
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helps to identify problems early.
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It can also help design targeted monitoring programs.
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Interpreting monitoring data is a significant challenge
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because it goes beyond plotting a time series
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and trigger thresholds.
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Again, that is only valuable if it’s interpreted
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in the context of the digital twin.
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A continuously updated digital twin
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enables an adaptable design that allows material changes
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in the design to be identified in the moment.
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Informed field decisions can be made
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to either alter the design
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or accept the current construction trajectory
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that meets the factors of safety.
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We truly believe a paradigm shift is required
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whereby tailings governance needs to shift
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from a dominantly reactive long-term modeling approach
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to a more strongly agile,
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even predictive short-term modeling method.
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To help prevent failure isn’t about one piece of data
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or a single technology.
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But it’s how you bring it all together that counts.
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Thank you for your time and attention.
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But just before I hand you back to Janina,
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please note that we have a host of additional information
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on tailings that you can source
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from our seequent.com website.
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Over to you Janina.
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<v Janina>Thank you very much, Pieter</v>
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and yeah that is wonderful.
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So I would like to address of course the audience
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in the last couple of minutes.
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And if you have any questions regarding Pieter’s talk
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please feel free to write them here in the question window.
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And in previous conversation with a few of the attendees,
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there were a few questions that were asked
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and we want to make sure that we address these as well.
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So I’m going to ask my colleague Jenny if she’s available
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to help me address those questions.
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(Jennifer chuckling)
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<v Jennifer>Hi everybody.</v>
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We’ve just got a couple of questions here Janina.
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What was meant by more agile
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rather than reactive workflow
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is one of the questions that just came up.
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<v Janina>Oh yeah okay.</v>
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Yeah so the way that tailings monitoring and governance
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is currently conducted is somewhat lengthy
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and not always linear process.
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So the flow of observational and measure data
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is often inhibited by lack of interconnectivity
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between technology,
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but also between those multidisciplinary teams.
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The consultants, the reviewers, the geotechnicians,
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the third parties,
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everyone involved is somewhat disconnected from each other.
[00:17:33.880]
And so that very nature of this aggregated process means
[00:17:37.610]
that we’ll never really sees the full real-time picture
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or the complete digital twinness if you will.
[00:17:43.490]
So to understand all of those influencing factors at play,
[00:17:46.870]
and because of that,
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one can only really react when or if a red flag goes up.
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So only when everyone works from a one source of truth
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and has insight into each other’s expertise
[00:17:59.270]
and forward thinking 3D models and design work,
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one can partake in a more agile and even predictive workflow
[00:18:07.000]
that mitigates the risks from the start
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and also identified issues before they truly turn
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into real problems.
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That’s the idea.
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<v Jennifer>Fantastic.</v>
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We’ve just got one other question here as well.
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How does the solution allow companies
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that adhere more closely to those new global standards
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that have recently been put together?
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<v Janina>Yeah, they’re the new global standard of</v>
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(indistinct chattering)
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Yeah then you have a close look at this document
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and believe me, we have.
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(Janina laughing)
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The headlines and that is really six chapters
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and they all ask to for the operator and everyone involved
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in the tailings facility to meaningfully engage people.
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To build an interdisciplinary knowledge base
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and to develop robust designs that integrate
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that knowledge base.
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And together develop an organizational culture
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that promotes learning, communication
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and really early problem recognition.
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That’s the key.
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And all of these aspects are truly fulfilled
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when an uninhibited and real time communication
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in 3D occurs.
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So when there’s interactive collaboration
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that can take place between everyone involved,
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and that’s exactly what our solutions are aiming to do.
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Our individual products integrated with each other
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and underpinned through Central.
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It really brings people and data together
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and promotes that intellectual exchange
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between subject matter experts, stakeholders
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and of course also the public to build a really clear
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and perpetual transparent view of everything
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that governs that side.
[00:19:54.430]
And so in that sense,
[00:19:56.100]
we really quite closely adhere to the global standard.
[00:20:01.600]
Yeah.
[00:20:02.460]
<v Jennifer>Thanks Janina, I think that was,</v>
[00:20:04.313]
that answered that really well.
[00:20:07.440]
I think that was all the questions.
[00:20:09.760]
So if anyone else who, oh, sorry,
[00:20:12.610]
let me just check there’s something else.
[00:20:17.150]
Does Leapfrog allow real-time data streaming into the model,
[00:20:21.360]
to say monitoring and visualize the phreatic surface?
[00:20:27.540]
<v Janina>Yeah, it depends on what kind of,</v>
[00:20:30.780]
very good question.
[00:20:31.613]
It depends on which format it comes in.
[00:20:33.270]
But ultimately in Central we have built a dynamic link
[00:20:36.410]
where you can bring in point information for example,
[00:20:39.250]
and link it dynamically and directly to Leapfrog.
[00:20:43.000]
So in Leapfrog you would be able to build a phreatic surface
[00:20:46.690]
or any kind of 3D surface
[00:20:48.970]
based on that xyz point information.
[00:20:51.510]
And as soon as that information in its raw form
[00:20:55.280]
is refreshed in Central,
[00:20:58.430]
in the Central data room and its repository,
[00:21:01.020]
then your Leapfrog project will automatically
[00:21:03.070]
be notified about it.
[00:21:04.600]
So in that sense you can just right click, refresh
[00:21:07.250]
and then your phreatic surface will rebuild
[00:21:09.920]
based on the new information.
[00:21:11.830]
And depending on how you set up your project,
[00:21:13.970]
you have an opportunity then to actively compare
[00:21:16.770]
what that surface looks like
[00:21:18.500]
relative to the previous interpretation, the previous model
[00:21:21.770]
and what those changes mean going down the roads
[00:21:25.110]
in terms of your hydrogeological assessment
[00:21:26.760]
of the site, yeah.
[00:21:29.946]
<v Jennifer>Fantastic.</v>
[00:21:31.170]
And if there is any questions about workflow
[00:21:34.430]
or if anyone would like to get in touch with us
[00:21:36.850]
about setting up those different workflows
[00:21:38.790]
to dynamically link that data then we’d love to talk to you
[00:21:42.950]
and perhaps have a look at what you’re working with
[00:21:45.860]
at the moment.
[00:21:47.180]
<v Janina>Thank you very much for joining</v>
[00:21:49.330]
and thanks Jenny, thanks Pieter for the great talk
[00:21:52.370]
and we hope to hear from you soon.
[00:21:54.440]
Have a great remaining conference.
[00:21:57.793]
(gentle music)