
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.
Maptek DomainMCF uses machine learning to generate domain boundaries direct from sample data for rapid creation of resource models. Geologists feed in drilling or other sampling data and obtain domain or grade models in dramatically less time than traditional resource modelling methods.
The Maptek Compute Framework moves away from complex software installed on desktop computers and shifts costs from capital to operating budgets. Faster, secure cloud processing is supported by flexible licensing.
Generate resource models in minutes or hours, depending on size, data density and complexity of the deposit.
Many operations only have the ability to update their resource models once or twice a year. Using DomainMCF, your project can be modelled in minutes with results comparable to classical techniques. You remain in control of the process without the onerous preparation work. New data can be added and models regenerated quickly to reflect the current data.
Streamline workflow - data errors are highlighted and the modelling job cannot be submitted until changes have been made to remedy these.
DomainMCF solves another challenge - having valid geological data to input into the resource model. Data validation is completed within DomainMCF before the modelling phase.
The new geological domain modelling process using machine learning is especially suited to large volumes of data such as later stage exploration projects and operating mines. Your operation will benefit from multiple solutions run in parallel using high performance cloud computing.
Improve productivity
Produce resource models up to 2000 times faster and more cost effectively than other solutions.
Maximise investment
Generate resource models with certainty and report investment options to stakeholders.
Reduce costs
Cloud based processing and machine learning save time for resource modelling.
Standardised process
Repeatable and reliable results with the ability to easily update resource models.
Manage risk
Identify potential projects and accurately interpret the volume of geological data for targeting high value projects.
Measure uncertainty
Provide mine planners and potential investors with a quantitative assessment of risk due to geological uncertainty.
Build on success
Apply professional expertise to interpretation and evaluation, supported by automated machine learning approach.
Minimal setup
Cloud processing solution without onerous start-up or customisation. Start generating models within minutes.
Maptek is looking for individuals or companies who are interested in finding a faster and better way to do resource modelling.
Don’t miss this opportunity to provide important feedback to steer product development and gain early access to new domaining/AI capabilities, while continuing to extend your own expertise.
Register to find out more about the DomainMCF Early Access program.
The new Maptek geological domain modelling process employing machine learning has delivered accurate shapes and volumes in much shorter time.
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