SustainabilityFebruary 25, 2024

From Mining Data to Mining Intelligence

Mining intelligence, empowered by virtual twin experiences such as Dassault Systèmes’ GEOVIA Exploration Intelligence application, offers miners valuable insights and optimizes decision-making processes, ensuring sustainable and efficient resource extraction.
Avatar Josh LEE

By Mauro DELLEMONACHE, Chief Executive Officer, GEOVIA

Historically, mining data has been confined to departmental silos, limiting its utility for mining organizations at large. Mining data helps gain an understanding of the “what” in data. Mining Intelligence answers the “how” and “why” to provide a comprehensive view of data. Together they enable mining companies to perform, test, and interpret sophisticated analyses quickly.

Miners can at once respond to worldwide and mine-specific challenges with evidence-based decisions, cutting through silos and interlinking various departments. This enables enhanced collaboration and knowledge sharing, while ensuring knowledge is retained across the organization even during multiple staff changes.

How mining data and intelligence deliver value

Mining intelligence is a tool for interpreting data accurately to uncover hidden insights. By using mining Intelligence miners can build on solutions for specific localized problems with a broader system-based view in which the entire organizational operations are seen as a unified whole.

Mining intelligence leads to higher productivity and profits, balancing resource extraction with sustainability.

Miners can anticipate challenges, reduce operational downtime, and enhance safety measures by running predictive analytics on mining data. Automation of processes using data further streamlines mining operations, enhancing overall performance.

For example, by using mining intelligence, miners can develop accurate models predicting both rock type and the economic feasibility of drilling in specific locations during the resource estimation phase. During the operational phase, they can analyze huge amounts of data to accurately predict when a piece of equipment or machinery could fail, or determine how best to minimize truck queue and hang time.

During the resource estimation phase, companies can use mining intelligence to develop models that accurately predict both rock type and the economic feasibility of drilling in specific locations.

During the resource estimation phase, companies can use mining intelligence to develop models that accurately predict both rock type and the economic feasibility of drilling in specific locations.

Why virtual twin experiences are key to mining intelligence

Modern mining operations are intricate systems of systems, surpassing the capabilities of industry solutions to analyze them. To fully harness the potential of big data, it’s important to identify the different systems generating it, understand their functions, and delineate their boundaries and interconnections. This enables effective management of data flow between these systems.

This level of interconnected data management is achievable through virtual twin experiences. Unlike standard digital twins, virtual twin experiences offer a dynamic, live virtual representation of the real world.

Virtual twins help miners test different scenarios and conditions to observe and measure how they will work out in the real world.

The applications linked to this system of systems incorporate smart algorithms that empower AI techniques to suggest decision options based on past data, current behavior, and possible simulated outcomes based on those decision options.

Having a digital continuity between financial assumptions based on commodity prices, energy cost and so on as well as geology, terrain, and in-field operational information enables mining companies to achieve consistency in planning from short-term to long-term and vice-versa. This also helps avoid having contradicting decisions implemented at the same time in different parts of the mine, which can hurt Net Present Value.

The virtual twin enables three levels of data analytics: 

  1. Descriptive:   Examining what happened
  2. Predictive: Examining possible outcomes based on what happened
  3. Prescriptive: Prescribing roadmaps based on possible decision options to adjust to various evolving factors on the go, thereby permanently pursuing value in all operations

This approach minimizes waste and risk, and maximizes productivity by reducing unnecessary material re-handling.

GEOVIA’s intelligence capabilities: A competitive advantage

Dassault Systèmes’ GEOVIA Exploration Intelligence application can use mining intelligence to reveal unexpected possibilities or important new insights. It provides geologists and managers with a global, visual overview of all exploration activities, ensuring up-to-date knowledge of everything that has happened or is happening at the exploration site. Utilizing its embedded AI and ML capabilities, miners can more efficiently discover new mineral deposits and optimize the extraction of hard-to-reach resources sustainably.

Moreover, GEOVIA helps miners stay ahead of the competition by enabling and elevating data analytics capabilities uniformly throughout the organization. GEOVIA’S four Mining Intelligence apps — Exploration, Geology, Production, and Caving — help users aggregate and publish that data in any form, including spreadsheets, charts, and graphs.

They can share knowledge from data analytics projects quickly and easily with all stakeholders through a simple, web-style portal. While providing up-to-date data, the system retains all previous versions to ensure projects are traceable and auditable.

GEOVIA helps mining companies embrace advanced analytics and AI to uncover patterns, trends, and insights from large datasets, enabling more accurate and timely decision-making. Miners can ensure data quality and accuracy by conducting regular audits, and validation processes, and including data cleansing protocols to enhance the reliability of mining intelligence.

A crucial advantage is that GEOVIA helps promote cross-disciplinary collaboration between mining and data analytics professionals to bridge the skill gap. Moreover, it helps invest in a robust, scalable, and integrated data infrastructure that can handle diverse data types, ensuring seamless data flow from various sources.

Dassault Systèmes’ 3DEXPERIENCEPlatform achieves this with a multi-physics, multi-scale approach. Its virtual twin experiences are enhanced with analytics-driven smart methods and algorithms to continuously pursue value while adjusting to uncertainties, be they technical, mechanical, or market-related.

The gaming-like experience of the 3DEXPERIENCEPlatform helps bridge the skill gap between traditional mining professionals and data scientists, a crucial aspect for successful mining projects. It renders operational data more visible and actionable, empowering executives from mine managers to frontline workers at the same time.

The platform provides a robust, monitored infrastructure for data storage and computing operations, increasing efficiency and productivity with business continuity. Its superior security measures facilitate worry-free intelligence-driven operations.

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