Enhanced domaining possibilities with AI

Tuesday, April 4th, 2023

Maptek has always been at the forefront of technological advance and is alert to exploit opportunities to help our customers.

Just when we were starting to feel comfortable with the ability of machine learning to solve problems, ChatGPT generated buzz around its powerful capacity to generate original text. AI is being embraced by a range of industries eager to explore the possibilities for automation in the digital world. We are monitoring developments in these spaces.

Maptek DomainMCF is leading a quiet revolution in the use of AI in geological modelling, with the impact being felt where it matters – on mine sites.

Since release in 2021 Maptek has continued to make DomainMCF even faster and easier to use.

Here are some of those enhancements:

  • User interface upgrades, including better predictions of job status and run time
  • Improved consistency and validation checks on data upload
  • More flexibility when using limit surfaces or solids
  • Separation of the training and predicting stage
  • Enhanced reporting and filtering of blocks with lower confidence
  • Improved download efficiency and speed
  • New download format which preserves model integrity
  • Improved data validation and preprocessing using Vulcan GeologyCore

Machine learning offers tangible benefits for resource modelling, including processing vast amounts of data and identifying patterns to help geologists unravel complexity.

By analysing historical data and incorporating new information as it becomes available, machine learning improves the accuracy of resource models. Providing insights in real-time accelerates the decision-making process and fast, provisional models can help mining companies respond quickly to changes in the market or operational conditions.

Machine learning offers opportunities to optimise resource utilisation, such as by identifying areas of high-grade ore that were previously overlooked. With DomainMCF users can now target areas of uncertainty by combining sample proximity with boundary confidence.

Customer feedback will continue to inform the Maptek machine learning development roadmap to ensure we deliver tools that enhance the decision making process.

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