Maximize profitability with mine life cycle optimization through machine learning.  Classify and segregate mine materials with much greater efficiency.

LEARN MORE
  • Most mines generate millions to billions of tons of material representing multiple classes of ore, waste, and construction material which need classification or segregation
  • Classification and segregation criteria are often expensive to quantify and difficult to extend to the operational scale
  • Most mines collect abundant exploration and production borehole assay which goes largely unused
  • Borehole assay is an excellent proxy for extending classification and segregation criteria to the operational scale using machine learning

Consulting Services: Mining / Oil and Gas

Learn More

Mine Life Cycle Optimization Using Machine Learning

Learn More

DEEP LEARNING USING HYPERSPECTRAL MINERALOGY

A quantum leap towards rapid evaluation of alternatives throughout the project life cycle

FEATURED PROJECTS

Proyecto Touro

Atalaya Mining PLC - Spain

Life Cycle Geo is currently assisting Atalaya Mining PLC with materials characterization and environmental management planning at Proyecto Touro in north-western Spain. The characterization program is aimed at developing a detailed understanding of long-term environmental behavior (acid rock drainage, metals leaching) of waste rock and tailings. This information will be used to evaluate various mine planning and permitting alternatives towards the development of an environmental management plan that supports both operational and regulatory requirements.

Oil Sands Process Water Modeling

- Alberta, Canada

Evaluated geochemical processes affecting bitumen recovery at a large oil sands operation towards prediction of recovery efficiency and long-term site water quality. The evaluation included reaction path modeling of caustic titration, carbonate scaling, sodium/calcium cation exchange and gypsum/polymer flocculant addition in a centrifuge.

Tailings Storage Facility – Seepage Investigation

- Mexico

Served as technical lead for a large, multi-disciplinary seepage remediation investigation, design and operation program at an active gold mine. Worked interactively with multiple project teams and provided technical guidance for the water chemistry team involved with plume characterization, source material evaluation, attenuation studies, baseline evaluation, multivariate statistical analysis of large datasets and reactive transport modeling.