Say hello to your new digital geologist
Accelerated discovery in ore grading
The GeoCore X10’s advanced analysis capability provides geologists and metallurgists with a large amount of information in record time. The quick non-destructive scanning process lets you work faster while you explore “what-if”-scenarios and arrive at your conclusions.
Combine X-ray high-resolution 3D imaging and accurate geochemistry analysis in a way that’s never been possible before. Learn about your drill cores’ chemical composition, mineral makeup, geological structure, texture and density in one easy scan. The GeoCore X10 is a tool for professional geologists who want to examine deposits in a much quicker way and with better results.
The GeoCore X10 replaces traditional lab services with accurate on-site analysis of rock drill cores. Geologists can now take advantage of almost instantaneous information to help find and extract valuable mineral resources
A batch of four cores completes in 60 minutes. And cores can be scanned directly after hole extraction – no cutting, pulverizing or prepping.
Bring the GeoCore X10 to your cores instead of the other way around. It’s designed for reliable on-site use.
Drill cores are scanned without any destructive preparation, which means that you can retain a complete core library for future reference.
The GeoCore analyses 100 % of the core’s inner material, not only the surface like many other technologies.
Senior Exploration Geologist
The GeoCore X10 is an outstanding addition to any geologist’s tool box. Its ability to provide both comprehensive chemical and structural information, in one quick scan, is a key component to the digitalization of the mining industry.
Master thesis opportunities – apply now!
We have a openings for master thesis projects focused on machine learning and AI. If you are an engineering/computer science student interested in advanced 3D image processing you can send your application to [email protected] or contact Mikael Bergqvist, Ph.D., at +46 70-173 17 70 for more information.
Segmentation of 3D tomographic data sets
Find efficient techniques for segmentation of 3D reconstruction data into smaller volumes, representing different minerals, using AI.
Apply machine learning to automatically find the boundaries of geological regions of interest by chemical content and the tomography textures of drill cores.
Encoding rules for geological classification
Using heuristics and machine learning to create decision models, for representing explainable geological classification rules.
Unsupervised geological feature extraction
Find geological features in 3d tomography data using unsupervised learning techniques on a large set of unlabelled data. These features could then be used to fingerprint data and train new models for use in geological exploration.