Case Studies

Advancing with DomainMCF

An exploration company in Canada found that Maptek domain modelling technology provided a faster way to uncover the resource potential of a gold project.

Quantifying geological uncertainty

A simulation study that tested alternative methods of modelling intrusive pegmatites in a nickel
sulphide deposit affirmed the value of Maptek DomainMCF.

Using AI to find copper

Maptek machine learning application DomainMCF helped a copper miner plan infill drilling for its project in South Australia.

Seeing patterns in geology structures

An engineering geologist outlines the challenges of revisiting a gold deposit and how Maptek modelling tools were applied to control the complexity.

From challenge comes opportunity

For a New Zealand consulting firm, the Maptek Geology Challenge was a chance to trial new software that could ultimately improve outcomes for clients.

Improving on traditional modelling

Machine learning techniques trialled alongside traditional resource modelling at an underground metals mine demonstrates future benefits.

Data driven modelling in a production environment

DomainMCF can change the way an operating mine uses geological and geotechnical models to keep information up to date in a production environment.

Modelling marble reserves

Applying machine learning to model marble reserves resulted in faster results and more uniform quality classifications to guide extraction.

Machine learning for fault identification

Machine learning engine for domain modelling is able to identify faulted geology in record time.

Domain modelling delivers accurate results

The new Maptek geological domain modelling process employing machine learning has delivered accurate shapes and volumes in much shorter time.