The importance of being … consistent
The search for productivity improvements is pervasive in the mining industry and MRE software are no strangers to the quest for speed seen in all operational processes. But that quest, whilst valid and sound, should not come at the price of quality, optimality or consistency in the manner information is treated.
Minestis is an integrated Mineral Resource Estimation solution that ensures consistency all along the estimation workflow:
- Consistency between geological modeling and resource estimation thanks to a fully integrated approach.
“Minestis reconciles in a dynamic way the geological model and the geostatistical block model.” – Institut des Sciences de la Terre, Sénégal.
- Consistency between original data values and their normal score transforms. While benefitting from variographic analysis in the gaussian space (where the impact of outliers is greatly reduced, and the underlying variographic structure better revealed), users will only access the variogram in the real space for easier understanding and utilisation. Minestis navigates to and fro in a totally transparent manner for users, allowing them to implement change of support, kriging, uniform conditioning and simulations in record time, all this with very few mouse clicks.
“Minestis has given us the opportunity to explore the value of Recoverable Resource Estimates, specifically via Conditional Simulations, across a variety of industrial minerals. The structured workflow approach and tailored support from Geovariances has made these techniques accessible to a broad range of users and increased their use.” – Imérys, France
- Consistency when reporting resources. Once the estimation process is over, all results end up within a coherent single report combining local and global resources, over the whole deposit, a specific domain and/or a group of domains, for the support size of your choice (block or panel), for a given mineral or several correlated minerals, for the cut-off list of your choice, computed using any given methodology, kriging, uniform conditioning and/or simulations.
This ensures robust estimates are produced fast with no alteration of the level of confidence which can be put on the resources.