Releases

A cornerstone of our company is innovation and development of technologies resulting in benefits for our customers, improving their practices and adding value to their projects.


Truncated gaussian kriging/plurigaussian kriging

It is a probabilistic method of the geological units ocurrence which considers relations contact between geologic units, is a more geological alternative than the traditional indicator kriging alternative. The technique is based on multigaussiano kriging and truncated Gaussian method.

Fuzzy remapping

This Methodology allows to correct inconsistencies or own errors of classification geological mapping according to the analysis of laws through recoding an algorithm allowing better define the units and therefore the estimated resources. The algorithm uses statistical classification techniques, geostatistics and fuzzy logic.

feed mineralogy modeling to calculate concentrate quality and/or (bio) leaching

It is critical in many projects the spatial distribution of mineral species as well as flotation processes as (bio) leaching. Through the coregionalization and cosimulation geostatistical techniques using laws soundings and mineralogical mapping of sulfides, GeoInnova makes estimates of mineral species, which can be incorporated into block models and mining planning, getting a characterization of species in feed impacting on quality of concentrate or varying potential (bio) leaching.

GAUSSIAN SEQUENTIAL SIMULATION WITH WASTE SUBSTITUTION

It is a simulation laws algorithm which can reduce calculation times at least 20% of the time used by current methods, allowing the addition of samples without the need to resimulate the orebody. The algorithm is based on the Gaussian sequential scheme and conditioning by kriging.

Deagglomeration with laws

Deagglomeration (declustering) traditional Techniques do not consider laws of samples only its spatial configuration, the deagglomeration technique with laws makes a declustering by cells considering the laws as an additional dimension, thus samples spatially grouped but quite different laws they are not redundant in this new space. This technique is important to infer the real and unknown distribution of laws, used as input in different geostatistical algorithms.


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