Prospectivity Modelling
Reduce exploration uncertainty
Data-driven prospectivity modelling is a powerful exploration tool that enables explorers to extract greater value from their exploration data, enhancing geological understanding and supporting the generation of data-driven exploration targets.
At Datarock, we specialise in combining geoscience expertise with advanced data analytics to integrate diverse exploration datasets and develop predictive models that uncover hidden mineral potential.
Datasets
We work with all types of exploration datasets at regional, continental and global scales:
- Geochemistry
- Structural mapping
- Geology mapping
- Synthetic Aperture Radar (SAR)
- Multi/Hyperspectral
- Radiometrics
- Magnetics
- Topography
- Gravity
- Seismic
Geochemistry
Structural mapping
Geology mapping
SAR
Multi/Hyperspectral
Radiometrics
Magnetics
Topography
Gravity
Value
Incorporating prospectivity modelling into your exploration strategy offers several key advantages:
- Enables objective decision-making grounded in data and geoscientific principles
- Quantitative ranking of exploration targets based on transparent criteria
- Reduces risk by identifying the most prospective areas and improving target confidence with quantified uncertainty
- Reveals data gaps, guiding where additional information is needed to strengthen future exploration efforts
Importantly, prospectivity modelling is a great way to test and contrast traditionally used model and mineral systems driven targeting workflows.
Use cases
Target search
Searching for complex multivariate signatures of a feature of interest in geoscience data.
Applications
- Identify and prioritise exploration targets
- Rapidly assess new regions of interest
- Test exploration models
Domaining
Data-driven domaining to find clusters of common responses in geoscience data.
Applications
Anomaly detection
Ore bodies are anomalies in the Earth’s crust; often presenting as subtle expressions in exploration datasets. Locating and quantifying anomalous features in these data can help identify ore body signatures.
Applications
- Target generation
- Data exploration
Computer vision–driven prospectivity
Datarock has developed innovative computer vision techniques for regional targeting and prospectivity modelling, extracting further value from complex textures in geophysical and remote sensing data.
Applications
- Analyse and quantify complex geophysical datasets
- Interpret geophysical data in a manner similar to human experts
Hyperspectral processing and analysis
Hyperspectral data from airborne and satellite platforms is becoming a powerful tool in greenfield exploration, offering extensive spatial coverage and detailed spectral information. These datasets are often large and complex, requiring advanced analytical approaches to extract meaningful insights. Datarock specialises in processing and modelling hyperspectral data to accurately map surface mineralogy and detect subtle signatures associated with mineralisation.
Applications
