Mineral exploration software for ranking drill targets

How satellite evidence layers relate to deposit models

Each deposit type leaves a different mix of clues at the surface, so the weight a layer carries depends on the model you're testing.

Alteration minerals

Hydrothermal fluids leave minerals with absorption features in the shortwave infrared: sericite, kaolinite and alunite near 2.2 micrometers, chlorite, epidote and carbonates near 2.3. ASTER's six SWIR bands separate these groups well enough to sketch zoning, such as a phyllic zone inside a wider propylitic halo around a porphyry copper system. (Its SWIR detectors stopped working in 2008, so this layer comes from the archive.) Iron oxides in gossans show up in the visible and near-infrared bands of Sentinel-2 and Landsat.

Structure, thermal and magnetics

Orogenic gold is mostly controlled by shear zones and fault intersections, and its alteration is often too narrow to see from orbit. On greenstone belts, radar lineaments and terrain therefore carry more of the score, as in our greenstone gold case study from Zimbabwe. ASTER emissivity picks out quartz-rich rock such as silica caps over epithermal systems. EMAG2 magnetics has a grid spacing of a few kilometers, so it shows a buried intrusion or the edge of a belt rather than individual veins; an airborne survey, if you have one, will resolve far more. Our guide to remote sensing for mining covers the sensors in more depth.

How to read a prospectivity score and its confidence tier

The prospectivity score (the Gold Potential Index on gold licenses) is a ranking within your license. A high value means several independent kinds of evidence agree at that spot. It isn't a probability that ore is there. Before you rank a zone for fieldwork:

• Look at its shape as well as its peak. A coherent zone along a mapped structure beats a few bright pixels, and the Raster Inspector histogram shows the difference.
• Open "Why Detected?" and see which evidence carries the score. Radar, thermal and geophysics agreeing is stronger than one spectral ratio on its own.
• Check the false-positive risk in the Zone Table. Clay-rich farmland, mine waste, road cuts and dry lake beds can all mimic alteration.

Each zone also gets a confidence class, coded EXPL_TARGET_A, B or C in the block model. On the demonstration license, the 910 Class A blocks hold 95% of the contained metal. We'd start field checks on Class A zones and come back to B and C later, or sooner if one lines up with old workings you already know about.

Turning an Exploration Target into a drill program

Under the JORC Code, an Exploration Target reported publicly has to be given as ranges of tonnage and grade, with a statement that it is conceptual and that there hasn't been enough exploration to estimate a Mineral Resource (Clause 17 of the JORC Code 2012). NI 43-101 has a similar rule. Mining Pro works at that stage, and the P10/P50/P90 ranges in the Economics tool fit that way of describing a target.

The usual order is to field-check the Class A zones, trench or run ground geophysics on the ones that hold up, then drill the best. On engagements where clients tested our ranked zones, 90% were confirmed by ground or drill evidence, which makes the ranking a good guide to what to test first. The testing still has to happen, and feasibility studies come later still.

How Mining Pro fits with Leapfrog, Vulcan, Surpac and Datamine

Leapfrog Geo is widely used for implicit geological modeling, and Vulcan, GEOVIA Surpac and Datamine cover modeling, mine design and scheduling. All four do their best work with drillhole data. Mining Pro comes earlier, before there's drilling to model: you use it to decide where the first holes go, then take the results into the package your team already knows.

The Export tool writes DXF, OMF and Surpac STR/DTM files of the block model, pit limits and drillholes in real-world UTM coordinates. DXF imports into all four packages, Leapfrog also reads OMF, and Surpac reads STR/DTM natively. Because everything is in UTM the targets land over your topography, tenement boundary and any historical holes. When your own drilling comes in, the resource model is built from the real holes and our targets stay on as a reference layer. Chapter 15 of the course shows the import into each package.

Choosing mineral exploration software

The right mineral exploration software depends on how far along your project is and what data you hold. These are the questions we'd ask:

• Do you have drill data? If so, a geological modeling package is your core tool. If not, you need satellite mineral exploration software that ranks ground before drilling.
• Can you see why a target ranks where it does? A score you can't take apart is hard to defend to a board or a joint-venture partner.
• Does it export in your coordinate system and file formats?
• Does it keep to the reporting codes? Satellite results presented as resources cause trouble later with JORC or NI 43-101 disclosure.

The label "AI mining software" says little by itself, so ask what data a model uses and whether you can inspect its evidence (our article on AI in mineral exploration explains how these models are built). If you already have hundreds of drill holes and a resource to update, a full modeling package will do more for you than Mining Pro. It's most useful on early-stage licenses, portfolio screening and second opinions.

Getting started with Mining Pro

1. Watch Part 1 of the course (three chapters, 52 minutes) for the physics and math the rest of the platform builds on.
2. Open Mining Pro and follow the course on the 2D Map, starting with "Why Detected?" on the strongest zone.
3. Work through the Zone Table and Block Model before economics. A value figure only means something once you trust the zone behind it.
4. For your own ground, send the boundary, country and target minerals through the mining quote form. We reply within one working day with scope, price and timeline.

If you'd rather have our team prepare a finished document, ask for a satellite mineral detection report instead.