When recovery depends on more than grade

When recovery depends on more than grade

BEYOND GRADE USING GEOLOGY-LED MODELLING TO PREDICT ORE BEHAVIOUR AND RECOVERY

Grade is only one part of resource evaluation. Recovery, hardness, deleterious elements and mineralogical variability can influence project economics, yet they are often harder to model because metallurgical test work is limited.

This article explains how geology-led geometallurgical modelling helps teams use sparse recovery data more effectively by first defining meaningful domains, then modelling abundant geological and mineralogical variables before estimating processing response. It outlines a practical workflow that combines geostatistics with supervised machine learning to support recovery forecasting, scheduling, blending, plant feed management and risk assessment.

Download the article now to discover how geology-led modelling predicts recovery from limited test work

Read the full article

Datamine lead Gen - Part 3 - 106.1

First Name

Last Name

Company

Job Title

Country

Work E-mail

Phone number with country area code

Tell us about your operation, challenges, and what you’d like to achieve.

We would like to send you information about Datamine and Aspermont services that may be relevant to you. By submitting your information, you confirm that you agree to this and that you also accept our terms and conditions, privacy policy, and cookie policy. You can opt out of receiving these communications at any time.

We occasionally send marketing messages on behalf of our partners. By submitting your information, you indicate that you agree to this and that you also accept our terms and conditions, privacy policy, and cookie policy. You can opt out of receiving these communications at any time.