3D blocky visualization of gold concentration with a color scale from less than 0.1 to 2.4 parts per million, showing high concentrations in red and lower in green, blue, and yellow.

Geospatial Modeling

Geospatial modeling plays a crucial role in modern mineral exploration by transforming complex datasets into structured, interpretable models that guide decision-making. By integrating geological, geophysical, and geochemical data within spatial frameworks, it enables exploration teams to better understand subsurface conditions and identify high-potential zones with greater accuracy.

Laptop displaying a 3D map or terrain model with a mountain range and a color-coded underground section.

Geospatial  Modeling

GeoSpectra combines a mineral systems framework with advanced machine learning to locate and optimize drilling targets and models the resources across the exploration lifecycle. 

3D scientific visualization with geological layers and drill data, showing elevation and depth along with axes labeled X, Y, and Z, and the logo 'Geospectra' in the top left corner.

AI-Driven Drilling Targeting

GeoSpectra integrates 2D structural, geophysical, geochemical, and geological datasets to identify and rank scout-drilling targets. As data is acquired, our semi-supervised machine learning algorithms merge the surface signatures with 3D borehole assays and lithological logs. By analyzing both  results simultaneously, our workflow models ore-body continuity—enabling exploration teams to precisely target infill drilling and accelerate reliable reserve estimation.

Why Choose Us

Advanced Machine Learning Integration

We leverage cutting-edge AI and semi-supervised models to enhance accuracy and reduce interpretation bias.

End-to-End Exploration Support

From early targeting to resource estimation, our models support every stage of the exploration lifecycle.

Scalable & Adaptive Models

From regional studies to detailed project analysis, our approach adapts to your exploration needs while saving time and costs.

A 3D block model showing gold concentration at Dalli South Hill, illustrating a strong gold anomaly on the western part of the South Hill diorite stock, with a legend indicating different abundance levels from absent to high concentration. Below the model, a table provides specific data on cut off, average, volume, tonnage, and gold content at various ppm levels.

Resource Estimation

Following precise drilling programs, GeoSpectra conducts resource modelling and reserve estimation, delivering robust, data-driven models to support  strategic decision-making. This integrated approach enhances targeting precision, reduces exploration risk, and improves discovery efficiency by maximising both resource tonnage and ore grade. 

Cross-section of a mineral deposit showing oxide ore, enrichment blanket, and sulfide ore layers, with labels DDH-08 and DDH-02.

Deposit Modeling

GeoSpectra models various sections of the deposit for decision making. In this picture, the porphyry deposit is divided into three distinct vertical zones: the upper Oxide Ore, where near-surface weathering and oxygen interaction altered primary minerals; the intermediate Enrichment Blanket, a high-grade layer formed where leached metals have precipitated; and the deep Sulfide Ore, which comprises the original, unaltered hypogene core.