Geostatistics for Mineral Resource Estimation
Geostatistics is the most efficient and powerful framework to characterise, estimate and manage your mineral resource.
Geologists or mining engineers can apply geostatistics at all stages of the mine life cycle: from exploration to development, production and even for site remediation. Geostatistics offers a wide range of methodologies adapted to all commodities and styles of deposits.
Geovariances’ scientific rigour, continuous innovation and geostatistical expertise guarantee the quality of your evaluations at different stages of the development of your projects (feasibility studies, bankable studies, desktop reviews, etc.).
HEAR FROM OUR CUSTOMERS
"Great piece of software helping the Resource Geologist to investigate its dataset to take the best decision while estimating."
"I have had a chance to test some parts of Isatis.neo and am amazed at how the menus and many functionalities are nicely streamlined. Everything seems to be carefully and logically arranged, especially for new users. For the old Isatis users, I think it is just a matter of..."
"We've got excellent results with the clustering tool available in Isatis.neo. The domains created with Isatis.neo have been validated with the reconciliation of mined areas and the results of the technological studies."
Training very good in all aspects: organization, material, applicability of the methodology and technical knowledge of the consultant. We will certainly have more challenges and we know that we may count on you.
Geovariances technical support is personalized, which I really enjoy. Many software companies provide a totally impersonal "call center" type of support, which certainly discourages us to use the support and the software itself. Not Geovariances.
WHAT IS HAPPENING IN YOUR INDUSTRY?
Press Release: Geovariances launches the version 2020.06 of Isatis.neo, their user-friendly and comprehensive software solution in Geostatistics.
With this new version of Isatis.neo, Geovariances continue to implement advanced geostatistical techniques. In particular, we have added t...
Communiqué de Presse: Geovariances annonce la version 2020.06 d’Isatis.neo, sa solution logicielle en géostatistique, facile d’utilisation et complète
Avec cette nouvelle version d’Isatis.neo, Geovariances poursuit l’implémentation de techniques géostatistiques avancées. En particu...
The University of Chile uses Isatis.neo for their postgraduate diploma in Geostatistical Evaluation of Deposits
Students benefit from academic licenses of Isatis.neo to experience geostatistics techniques applied to resource evaluation.
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Co-kriging of log ratios: a worked alternative method | Clint Ward, Cliffs, Ute Mueller ECU
Local Uncertainty Benchmarking – A coal case study | Written by C. Mawdesley, D. Barry, O. Bertoli and R. Saha
Sensitivity study of the estimation variance approximation of a quotient | Comparison with Conditional Simulations in the Mn Deposit of Bangombé (Gabon)
Data classification using geostatistical hierarchical clustering for robust and dynamic domaining
Key Functionalities new module Studio RM 2016 | Presented by Olivier Bertoli at the UC2016 event organized in the UK by Datamine
How the use of stratigraphic coordinates improves grade estimation | Rubio, Ricardo Hundelshaussen, Koppe, Vanessa Cerqueira, Costa, João Felipe Coimbra Leite, & Cherchenevski, Pablo Koury. (2015) - Rem: Revista Escola de Minas, 68(4), 471-477. https://doi.org/10.1590/0370-44672015680057
Recoverable resource estimation for an underground manganese project using multivariate conditional simulation with scenario reduction
Production reconciliation of a multivariate uniform conditioning technique for mineral resource modelling of a porphyry copper gold deposit
Application of nonlinear geostatistical indicator kriging in lithological categorization of an iron ore deposit
Multivariate block simulations of a lateritic nickel deposit and post-processing of a representative subset