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GeoAnomalyMapper

AI-Driven Continental-Scale Mineral Prospectivity Engine

Python License: Proprietary

Commercial licensing available. Research use permitted. See LICENSE for terms.


What It Does

GeoAnomalyMapper uses a Physics-Informed Neural Network (PINN) to solve the gravity inverse problem at continental scale — converting Bouguer gravity anomaly data into subsurface density contrast models, then extracting ranked prospectivity targets.

Bouguer Gravity → Residual Separation → PINN Inversion → Dual-Pipeline Extraction → Scored Targets

The system runs a dual pipeline — finding both mass-excess anomalies (VMS, IOCG, skarns, Ni-Cu) and mass-deficit anomalies (epithermal gold, alteration halos, kimberlites) — validated against independent geochemical and MRDS datasets.


Validated Performance

Metric Result
Targets generated (continental US) 1,634
Tier 1 high-confidence targets 31
Geochemical enrichment vs. baseline 8.5x (32.4% hit rate vs. 3.8% random)
Negative control specificity 100% (zero false positives in barren regions)
Statistical significance >7 sigma

Independent validation used the NURE geochemical database (397,000+ sediment samples) — completely separate from training data. See docs/SCIENTIFIC_VALIDATION_REPORT.md for full methodology.


What You Can Buy

Regional Screening Packs — ranked prospectivity leads + evidence bundle per commodity/district. Suitable for early-stage teams selecting which districts to enter.

"Bring Your Own Data" Inversion Service — you supply higher-resolution gravity/mag, we deliver ranked anomalies, uncertainty maps, and an HTML+GeoJSON target package. Suitable for juniors with geophysics data but no internal AI inversion pipeline.

Automated Due Diligence Reports — submit coordinates, receive a go/no-go desk report: MRDS cross-check, geochemical coverage flags, density contrast evidence. Suitable for exploration managers screening incoming deal flow.

Commercial Software License — deploy the pipeline on your own infrastructure.

For pricing and availability, open a GitHub issue or contact via the profile.


Technical Summary

Core model: DensityUNet with physics layer implementing Parker-Oldenburg forward gravity. Loss function: data fidelity + structural coupling (EMAG2 magnetic regularization) + sparsity.

Resolution: ~2km continental grid. Optimized for district-scale targets (1–20km). Not suitable for resolving individual deposits <500m. Resolution limit is a documented design constraint, not a bug — the filter is calibrated to district scale by design.

Depth ambiguity: All gravity inversions are non-unique. Outputs are prospectivity indicators, not structural models. Ground truthing is required.

Deposit types detected:

  • Mass-excess: IOCG, VMS, skarns, magmatic Ni-Cu, dense intrusives
  • Mass-deficit: Epithermal gold systems, alteration halos, sediment-hosted Au, kimberlite pipes

Project Structure

GeoAnomalyMapper/
├── pinn_gravity_inversion.py  # PINN architecture (DensityUNet + physics layer)
├── loss_functions.py          # Custom loss (structure-guided TV + magnetic coupling)
├── train_usa_pinn.py          # Training pipeline
├── predict_usa.py             # Continental-scale sliding window inference
├── extract_dual_targets.py    # Dual-pipeline target extraction
├── phase2_validation.py       # MRDS cross-reference + confidence scoring
├── verify_skeptic_v2.py       # Forensic validation + negative controls
├── data/outputs/              # Target CSVs, scored lists
└── docs/                      # Scientific validation, forensic audit, methodology

Quick Start (Research Use)

pip install -r requirements.txt

python train_usa_pinn.py
python predict_usa.py
python extract_dual_targets.py data/outputs/usa_density_model.tif
python phase2_validation.py

Gravity input data: USGS Bouguer anomaly grid. Magnetic data: EMAG2. Both are publicly available. See setup_usgs_data.py for download helpers.


Known Limitations

  • Continental public grids (~2km) cannot resolve deposits smaller than ~500m.
  • Basin & Range regional gravity lows (Nevada) mask discrete epithermal anomalies at this resolution.
  • Gravity inversion is inherently non-unique (depth vs. density ambiguity).
  • Outputs are statistical prospectivity indicators — not drill targets. Field verification required.

The validation suite (negative controls, geochemical enrichment, forensic audit) documents exactly where the model works and where it doesn't. See docs/ for the full record.


License

Proprietary. Commercial use requires a license agreement. Research use permitted. See LICENSE for terms.


Acknowledgments

  • USGS for public gravity and MRDS data
  • NURE program for geochemical validation data
  • The geophysics and mineral exploration research community

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PINN-based continental-scale mineral prospectivity engine — gravity inversion to ranked exploration targets, 8.5x geochemical enrichment vs. baseline

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