What is Orebody Learning?

Orebody Learning™ is an artificial intelligence system that enables mining operations to learn about their orebody directly from operational experience and put those insights into tangible AI software solutions. It is powered by PETRA’s proprietary digital twin technology stack: Data Fusion Ore Tracking & Machine Learning. 


PETRA products & services utilising Orebody Learning™

MAXTA: for value chain optmisation  |  ROCKRay: for augmentation of drill samples

Orebody Learning™ uses machine learning algorithms to analyse geological data and gain insights into the mineral deposits within an orebody. An orebody is a natural concentration of valuable minerals that can be extracted economically from the Earth’s crust.

In the mining industry, orebody learning can be used to optimise the mining process and maximise the extraction of valuable minerals. By analysing geological data, such as geophysical surveys, drilling results, and geological maps, machine learning algorithms can identify patterns and relationships between different variables. These insights can then be used to build predictive models that can help mine operators make better decisions about where to mine and how to extract the minerals.


What is orebody learning?



Orebody Learning™ can be used to optimise many aspects of the mining process, including mine planning, mineral processing, and waste management. For example, by analysing geological data, machine learning algorithms can identify the areas of the orebody that are most likely to contain the highest concentrations of valuable minerals. This information can then be used to develop more efficient mining plans that focus on these high-grade areas, reducing the need for excessive drilling and excavation.

Additionally, Orebody Learning™ can be used to optimise the processing of ore, which is the process of separating the valuable minerals from the surrounding rock. By analysing the mineralogy of the orebody, machine learning algorithms can identify the most efficient processing methods, reducing the amount of energy and resources needed to extract the minerals.

Overall, Orebody Learning™ is an important application of machine learning in the mining industry, as it can help mine operators make more informed decisions about where and how to mine, reducing the environmental impact of mining and increasing the efficiency of the process.


Orebody Learning™ provides:

  • Site-specific models using a mine’s own data
  • High granularity block-by-block predictions
  • Updated block models as soon as new operational data has been provided
  • File formats which are platform agnostic, designed to connect with in-house or third party data platforms


Previously, orebody knowledge was limited to:

  • Grade & product quality
  • Geometallurgy
  • Geotechnical characterisation


The problem it aims to solve

What is orebody learning?

Many mining operations suffer from the inability to learn from experience, Orebody Learning™ using digital twin technology aims to bridge this gap.

Expanded orebody knowledge provides information about:

  • What is the best way to process the ore
  • What is the best way to blast the ore
  • How to be more energy efficient
  • How to predict material handling properties
  • How to predict recovery
  • How will certain geology blast
  • How quickly will diggers get through certain geologies
  • How will geology impact downstream performance


Orebody Learning™ powers PETRA products and applications

Considered the heart of all PETRA solutions, Orebody Learning™ allows us to create decision support tools to predict, simulate & optimise using a mathematical model of how your mine works.


Customer benefits

  • Increase profit margin/ recover benefits faster
  • Optimise the value chain for geological variability
  • Support operational decisions based on data driven models
  • Integrate with existing systems(software) and workflows
  • Get more value from existing data
  • Create a repository of geology linked to performance
  • Create 10’s of thousands of data records


How does this compare to other solution providers?

  • They rely upon 20th century empirical models for example Orica’s IES.
  • Provide low granularity 3D models using spatially limited rock testing data
  • Provide forward only predictions without a feedback loop
  • Force mining companies to use their data platform
  • Don’t use digital twin technology to improve orebody knowledge



Image showing conventional vs orebody learning

Image showing how orebody learning works Image showing how orebody learning works

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