Geostatistics

We process and analyze large volumes of geological data to identify patterns, trends and spatial relationships that are not evident to the naked eye. This allows generating more precise interpretations of the subsoil and improving the coherence of the geological model, reinforcing decision making in exploration and mining design.

We apply geostatistical techniques to estimate resources and reserves with greater precision, reducing the uncertainty associated with the natural variability of the reservoir. This improves the reliability of calculations and provides a solid basis for the economic and operational planning of mining projects.

Through the analysis of the spatial distribution of the data, we identify areas with greater uncertainty and areas with unexplored mineral potential. This information allows you to design optimized research campaigns, concentrating efforts where they really add value and reducing costs.

Geostatistics enables us to generate predictive models that simulate different mining scenarios. We assess variability, mineral continuity and potential risks to define the most efficient, safest and most profitable mining plan.

We determine operating limits based on the spatial distribution of the mineral, geological variability and economic criteria. This ensures a mine design that maximizes resource value and decreases uncertainty during operation.

We integrate geostatistical results into short, medium and long-term planning models. This makes it possible to project more accurate productions, optimize mining sequences and ensure that operational decisions are supported by solid technical information.

We apply geometallurgy to predict the behavior of the deposit to be exploited, modeling the spatial variability of the mineral properties in aspects related to mining and metallurgical behavior (grade variability, by-products, contaminants, mineralogical composition...).

Through the geostatistical treatment of previous geochemical data, we define the environmental situation of the sites of future mining exploitations or urban and industrial facilities.

We generate detailed contaminant distribution maps using geostatistical interpolation. This representation allows you to visualize critical areas, define intervention priorities and base decontamination strategies based on data.

We quantify the confidence level of each estimate using advanced techniques that assess data variability. As a result, we provide more comprehensive assessments that enable the management of environmental risks and informed decision-making.

We apply geostatistical models to estimate the volume affected by contaminants in soils, sediments or groundwater. This information is key to correctly dimension remediation actions and evaluate environmental impacts.

We integrate maps, volumes and risk analysis to define realistic and profitable decontamination plans. This planning optimizes resources and ensures compliance with the project's environmental objectives.

We apply descriptive and multivariate statistical techniques to identify trends, associations and anomalies in the geochemical data. This initial analysis is essential to correctly interpret the information and guide subsequent work.

We produce geochemical maps that show the spatial distribution of specific elements or compounds. These maps are essential for interpreting geological, environmental or mineral processes, and for prioritising areas of interest.

Using the knowledge provided by geochemistry and geostatistics, we design sampling campaigns aimed at reducing uncertainties, improving the quality of the model and focusing research on those areas with the greatest potential or risk.