How Farmonaut screened a large greenstone-belt licence with satellite data alone — ranking 155 gold target zones before a single drill rig, boot, or trench touched the ground.
Region: West African gold belt
Method: Multispectral + SAR + DEM
Scale: District / portfolio
This case study has been anonymised. The concession name, licence holder, coordinates and precise location have been removed at the client’s request; only country-level context (West Africa) is retained. All quantities are satellite-derived Exploration-Target estimates — a conceptual screening output, not a Mineral Resource or Reserve under JORC, NI 43-101, S-K 1300 or SAMREC, and not a substitute for drilling.
Early-stage gold exploration across a district-scale licence is a numbers problem before it is a geology problem. A single greenstone-belt permit can span tens of thousands of hectares, most of which will never host economic mineralisation. The traditional route — walking grids, cutting trenches, collecting soil and stream-sediment samples, then drilling — is thorough but slow and costly, and it burns most of the budget narrowing the search rather than testing real targets. Satellite gold exploration in West Africa flips that sequence: it screens the whole licence from orbit first, so field teams and drill metres are spent only where the data already points.
This is the anonymised story of one such screening. Farmonaut processed a full district-scale area of interest through its satellite mineral-detection pipeline and returned a ranked inventory of 155 gold target zones, a conceptual grade and tonnage envelope, and a synthetic drill-and-pit planning pack — the raw material a geologist needs to design a field campaign with confidence. Below we walk through the challenge, the method, the findings, and what it means for time, cost and ESG.
“155 gold target zones ranked from orbit — before a single metre was drilled.”
The challenge: too much ground, too little time
The licence in this study sits within a classic West African greenstone belt — the same broad geological setting that hosts many of the continent’s largest gold mines. That is both the opportunity and the problem. Prospective structure is everywhere; economic mineralisation is not. A team that tries to sample the whole area uniformly will spend a year and a large budget just to decide where to look properly.
- ⚠ Cost front-loading — ground geochemistry and trenching consume budget long before any drill target is confirmed.
- ⚠ Access & season — vegetation, laterite cover and wet-season access windows slow field mobilisation.
- ⚠ Signal vs noise — artisanal workings, old pits and barren alteration can all look “interesting” on the ground without being economic.
- ⚠ Investor pressure — boards and financiers want a defensible, ranked target list quickly, not a year-two update.
The brief to Farmonaut was straightforward: screen the entire licence remotely, flag every credible gold-associated anomaly, rank them by prospectivity and detectability, and hand back a target list plus a conceptual economic frame that a drilling programme could be built around.
Satellite screening does not replace drilling — it decides where drilling earns its keep. The value is in eliminating barren ground cheaply so the expensive tools are reserved for ranked, evidence-backed targets.
Want this for your own licence? Get a quote for a satellite mineral-intelligence report. You supply a polygon and the target mineral; we handle the data.
How satellite gold exploration in West Africa actually works
Every mineral and alteration mineral reflects and absorbs light in a characteristic way. Gold itself is not detectable from space — but the alteration halos, host rocks, iron staining, clay minerals and structural corridors that accompany gold systems are. Farmonaut fuses several public Earth-observation datasets and reads those spectral and terrain fingerprints, then combines them into a single prospectivity surface.
The sensor stack
| Data layer | What it contributes to a gold screen |
|---|---|
| Multispectral optical | Iron-oxide, clay and carbonate alteration indices; vegetation stress and bare-earth extraction. |
| Shortwave-infrared bands | Sericite / argillic clay alteration typical of hydrothermal gold systems. |
| Radar (SAR) | Structure and surface roughness that see through cloud and complement optical data. |
| Digital elevation model | Faults, lineaments, drainage and landform — the plumbing that focuses mineralising fluids. |
| Thermal & surface indices | Moisture, flow accumulation and surface context to separate real anomalies from noise. |
These layers are normalised and merged into a composite gold prospectivity index — a weighted blend of multiple sub-scores covering alteration, structure, host-rock favourability and detectability. Conceptually:
alteration ,
structure ,
host-rock favourability ,
detectability
)
→ per-pixel score → ranked anomaly polygons
The exact weighting and aggregation are proprietary, but the principle is deliberately conservative: an anomaly has to light up across several independent lines of evidence to survive. Single-sensor artefacts are filtered out. Each surviving polygon is then assigned a per-pixel grade estimate, a signal-strength class (Strong / Moderate / Weak / Marginal) and an Exploration-Target confidence class (Class A / B / C).
A credible satellite screen should tell you how confident it is, zone by zone — not just “hot” or “not hot”. Confidence classes and false-positive-risk flags are what let you drill the best targets first and defer the marginal ones.
The multi-filter detection cascade
The single most important design choice in a district-scale screen is the order of elimination. Rather than scoring every pixel once and calling the highest values “targets”, the pipeline runs a cascade: broad favourability first (is this the right host rock and structural setting at all?), then alteration and iron-oxide signatures, then structural coincidence, and finally detectability and false-positive checks. Each stage removes ground that cannot survive the next. By the time 155 zones remain from a licence of tens of thousands of hectares, every one of them has passed several independent tests — which is exactly why the survivors are worth a geologist’s time.
Signal strength, zone by zone
Not all anomalies are created equal, and a good screen says so. Every zone carries a signal-strength class — Strong, Moderate, Weak or Marginal — derived from how emphatically it stands out against its local background across the contributing layers. A Strong zone lights up unambiguously on multiple sensors; a Marginal one barely clears the threshold. This is what converts a flat list of 155 polygons into a workable ranking: the operator can read down from Strong to Marginal and draw the line wherever the drilling budget falls.
False-positive-risk flags
Remote sensing has well-known traps — artisanal workings, exposed bedrock, salt or clay pans, and man-made disturbance can all mimic a mineral signature. To keep those out of the drill plan, each zone is annotated with false-positive-risk flags that record why it might not be what it looks like. A zone with strong signal and zero flags is a clean target; a zone with strong signal but several flags is a “look before you leap” candidate for ground validation. Publishing the caveats alongside the ranking is what makes the output honest rather than optimistic.
A trustworthy screen is auditable: every zone shows its signal strength and its risk flags, so a geologist can see not just that it ranked highly but why — and can overrule the model where field knowledge says so.
See the underlying platform: Farmonaut satellite-based mineral detection turns a raw AOI polygon into prospectivity heatmaps, estimated location and depth ranges, and indicative quantities.
Results: 155 ranked gold target zones
Across the district-scale AOI, the pipeline flagged and ranked 155 discrete gold target zones. Aggregated across all zones, the satellite-derived Exploration-Target envelope came to roughly 2,146 kg of contained gold (about 69,008 troy ounces) within an indicative host tonnage of ~8.5 million tonnes at an AOI-wide weighted grade of 0.55 g/t. At a gold price of USD 4,037/oz used for the scoping frame, that maps to an indicative in-situ gross value near USD 279 million, or about USD 226 million on a recoverable basis at an industry-standard 81% blended recovery.
These are conceptual, satellite-derived Exploration-Target figures spanning a district-scale licence, not a resource estimate. Grade and tonnage are modelled from remote sensing and must be confirmed by drilling. The weighted grade is an AOI-wide average; individual high-priority zones can run materially higher, while much of the footprint is low-tenor. Treat the totals as a screening-stage envelope for prioritising fieldwork.
Portfolio at a glance
| Metric | Satellite-derived estimate | Basis |
|---|---|---|
| Target zones ranked | 155 | Multi-evidence anomaly polygons |
| Contained gold (in-situ) | ~2,146 kg / 69,008 oz | Sum across all zones |
| Indicative host tonnage | ~8.53 million tonnes | Conceptual envelope |
| Weighted average grade | 0.55 g/t Au | AOI-wide, tonnage-weighted |
| Indicative gross value | ~USD 279 M | @ USD 4,037/oz spot |
| Indicative recoverable value | ~USD 226 M | @ 81% blended recovery |
| Confidence classes | Class A / B / C | Exploration-Target tiers |
The strategic point of a district screen is not any single number — it is the ranking. The 155 zones are ordered by prospectivity, signal strength and detectability, so the operator can concentrate first-phase drilling on the highest-confidence targets and stage the rest. A handful of Class A zones typically justify the first drill campaign; Class B and C zones become the pipeline for later phases or for divestment.
Class A — drill-ready targets
Anomalies that light up across the most independent evidence lines with strong signal and few false-positive-risk flags. These are the first-phase drill candidates.
Class B — validation targets
Credible anomalies with moderate signal or one or two risk flags. Worth ground-truthing with mapping and geochemistry before committing drill metres.
Class C — pipeline / watchlist
Weaker or higher-risk anomalies retained for completeness. Low near-term priority, but they keep the exploration pipeline full and inform regional structure.
From anomalies to a drill plan
A ranked target list is useful; a target list wired into a drill-and-pit plan is actionable. Alongside the anomaly inventory, Farmonaut delivered a conceptual planning pack built from the satellite grade surface: a synthetic drillhole layout, a regularised block model, closed ore-body solids for the strongest zones, and a floating-cone pit outline with a conceptual production schedule. For this district-scale screen the pack included on the order of hundreds of synthetic drill collars and a multi-hundred-thousand-block economic model.
The drillholes, block model and pit in the planning pack are generated from the satellite grade surface, not from physical drilling. They exist so a mine-planning team can rehearse the full Leapfrog / Vulcan / Surpac / Datamine workflow on realistic geometry and decide where real holes should go. Every layer is labelled synthetic and carries Exploration-Target confidence codes — it is explicitly not Measured / Indicated / Inferred material.
The upshot for the operator is a ready-made scoping geometry. Instead of starting a drill programme from a blank map, the geology team starts from ranked targets, a grade surface, indicative depths and a conceptual pit — and spends its expensive field time confirming the best of them.
“Screen from space, then drill with intent — that is the whole economic argument.”
Impact: time, cost and ESG
The reason satellite screening keeps winning early-exploration budgets is simple arithmetic across three axes.
Time: months compressed to days
A district-scale ground reconnaissance and geochemical programme can take many months to design, mobilise and complete. The satellite screen returned a ranked, mapped target inventory in days, so the operator could move to targeted validation in the same season rather than the next.
Cost: up to 80–85% cheaper at the front end
By eliminating barren ground before mobilising crews, satellite screening cuts early-exploration spend by up to 80–85% compared with blanket ground surveys. Drill metres — the single most expensive line item — are reserved for ranked, evidence-backed targets rather than spent proving where not to look.
A ranked 155-zone target inventory delivered in days is a de-risking milestone that can be reached before a large field budget is committed. It converts an open-ended “explore the licence” story into a staged, prioritised drill programme — the kind of narrative that supports financing decisions.
ESG: no ground disturbance during screening
The entire screening phase is conducted from orbit, with zero ground disturbance — no access roads, no trenching, no vegetation clearing until targeted validation begins. For operators working near communities, forest or protected areas, that is a materially lighter early footprint.
Remote screening means the only boots that eventually reach the ground are heading for pre-ranked targets. Less speculative fieldwork translates directly into less land disturbance, fuel and community impact during the highest-uncertainty phase of a project.
| Dimension | Traditional ground-first | Satellite-first screening |
|---|---|---|
| Time to ranked targets | Many months | Days |
| Early-stage cost | Full field budget | Up to 80–85% lower |
| Ground disturbance | Grids, trenches, tracks | None during screening |
| Coverage | Sampled subset | Entire licence, wall to wall |
| Output | Sample points | Ranked zones + grade surface + conceptual plan |
Why this geology carries gold — and where screening fits
West African greenstone belts are among the most productive gold terranes on Earth. They formed billions of years ago as volcanic and sedimentary sequences that were later deformed, metamorphosed and cut by large fault systems. Gold-bearing fluids travelled along those faults and precipitated where the plumbing changed — at fold hinges, lithological contacts and structural intersections. The result is orogenic gold: mineralisation that is strongly controlled by structure, often in clusters along a belt rather than a single blob. That structural control is precisely what makes the setting so amenable to satellite screening — faults, alteration halos and host-rock contrasts all leave surface expressions a multi-sensor pipeline can read.
Understanding that model is what lets a screen be more than a heat map. When an anomaly sits at a structural intersection with the right alteration signature, it is telling a geologically coherent story; when a bright pixel sits on a barren flat with no structure, it is probably noise. A district-scale screen that respects the deposit model — as this one did — concentrates its 155 zones where the geology says gold should be, not merely where a single index happens to spike.
Ask any screening provider how their targets relate to the deposit model. Anomalies that align with mapped structure and known host rocks are far more drillable than isolated spectral spikes, however bright.
Where satellite screening sits in the exploration lifecycle
Satellite intelligence does not replace the exploration pipeline — it front-loads it, so every later, more expensive stage starts from a stronger position. A typical staged programme looks like this:
- Reconnaissance & screening (this stage) — satellite screening of the whole licence returns ranked targets, a grade surface and a conceptual plan in days.
- Ground validation — mapping, rock-chip and soil geochemistry over the Class A and B zones to confirm the surface story.
- First-phase drilling — scout holes into the highest-confidence targets, guided by the conceptual drill geometry.
- Resource definition — infill drilling on zones that respond, building toward a JORC / NI 43-101 Mineral Resource.
- Study & development — scoping, pre-feasibility and feasibility studies on confirmed resources.
The 155-zone screen delivered here is stage one — but it shapes everything after it, because it decides which ground ever reaches stages two and three. That is the leverage: a modest, fast, low-impact analysis that redirects the entire downstream budget toward the best ground.
Every stage a project skips over barren ground is budget preserved for real targets. A ranked screen at the top of the funnel is the cheapest de-risking dollar an early-stage gold project can spend.
What you actually receive
A screen is only useful if it lands in a form your geologists and mine planners can open and act on. For this district-scale study the deliverable set included, at minimum:
- 📊 A ranked anomaly inventory — all 155 zones with prospectivity score, signal-strength class, confidence class and false-positive-risk flags.
- 🗺 Prospectivity heatmaps and alteration overlays — the full-resolution, georeferenced imagery behind the ranking, ready to load in any GIS.
- ⛰ A per-pixel grade surface and estimated depth ranges across the AOI.
- 🔧 A conceptual 3D and mine-planning pack — here on the order of 460 synthetic drill collars, a block model of some 333,000 blocks, closed ore-body solids for the strongest zones, and a floating-cone pit outline — exportable to Leapfrog Geo, Maptek Vulcan, GEOVIA Surpac and Datamine.
- 📄 A written geological interpretation tying the anomalies to structure, alteration and host rock.
Everything is delivered georeferenced, so it registers directly against the operator’s existing project coordinates and drill database.
The economic assumptions behind the numbers
Transparency on assumptions is what separates a scoping estimate from a guess. The indicative values in this study rest on a small, stated set of industry-standard inputs: a gold price of USD 4,037 per troy ounce (the spot level used at the time of analysis), an 81% blended metallurgical recovery, and grade and tonnage modelled per pixel from the satellite prospectivity surface. Contained gold is an in-situ figure; recoverable value simply applies the recovery factor. No mining dilution, processing cost, royalty or discount-rate assumptions are baked into the headline — those belong to later study stages. Read the numbers as a relative, screening-stage frame for comparing targets and sizing a drill programme, not as a valuation.
Treating a satellite scoping value as a project NPV. The figures here are deliberately un-discounted, pre-cost, in-situ-to-recoverable estimates for target prioritisation — the economic study that produces an NPV comes after drilling confirms a resource.
How to get this for your own site
The workflow behind this case study is available to any explorer, project generator or investor holding — or evaluating — a prospective licence.
- Send us your area of interest as coordinates, a KML/KMZ or a polygon, plus the country/region and target mineral(s).
- We select the data source (multispectral or hyperspectral), acquire it and run the detection pipeline.
- You receive a premium mineral-intelligence report — prospectivity heatmaps, ranked zones, estimated location and depth ranges, indicative quantities and geological interpretation — typically in 5–20 business days.
- Optionally add Premium+ TargetMax™ drilling intelligence: optimal drill angles, 3D subsurface models and the conceptual planning pack shown above.
Turn your licence into a ranked drill plan
Screen your whole area of interest from space before you spend a field budget. Farmonaut delivers ranked targets, grade surfaces and conceptual plans — georeferenced and drill-ready.
Explore the 3D angle: our satellite-driven 3D mineral prospectivity mapping shows how ranked zones extend into conceptual subsurface models — the same geometry used to build the synthetic pit in this study.
Frequently asked questions
Can a satellite actually detect gold?
Not the gold metal directly. Satellite gold exploration detects the alteration minerals, iron staining, host rocks and structural corridors that accompany gold systems, then combines those signals into a prospectivity ranking. Drilling confirms the gold itself.
Are the 155 zones a Mineral Resource?
No. They are satellite-derived Exploration Targets — a conceptual screening output for prioritising fieldwork. They are not a Mineral Resource or Reserve under JORC, NI 43-101, S-K 1300 or SAMREC, and grade and tonnage must be confirmed by drilling.
How accurate is the grade estimate?
The weighted grade of 0.55 g/t is a modelled, AOI-wide average and should be read as a screening-stage indicator with a range, not a point value. Individual zones vary widely. Its purpose is relative ranking and prioritisation, which is where satellite screening is strongest.
How long does a district-scale screen take?
Typically 5–20 business days depending on area size and mineral complexity — a fraction of the months a comparable ground-first campaign would need to reach a ranked target list.
Why is this case study anonymised?
At the client’s request, the concession name, licence holder and precise coordinates have been removed to protect commercially sensitive exploration ground. The geology, method and economics are presented in full; only the location identity is withheld.
What do I need to provide to get started?
Just your area of interest (coordinates, KML/KMZ or polygon), the country/region, and your target mineral(s). Request a quote here and we handle data selection and analysis.
Glossary
- Greenstone belt
- A belt of ancient volcanic and sedimentary rocks that hosts many of the world’s major gold deposits, especially across West Africa.
- Prospectivity index
- A composite score combining alteration, structure, host-rock and detectability signals into a single per-pixel measure of gold potential.
- Exploration Target
- A conceptual, early-stage estimate of the potential quantity and grade of mineralisation — explicitly not a Mineral Resource or Reserve.
- Blended recovery
- The share of contained gold expected to be recovered through processing; 81% is used here as an industry-standard scoping assumption.
- Floating-cone pit
- A conceptual open-pit outline generated by an optimisation routine on a block model — here built on the synthetic, satellite-derived model.
Disclaimer: This anonymised case study presents satellite-derived Exploration-Target estimates for screening and target-prioritisation purposes only. All quantities are conceptual, modelled from remote-sensing data, and are not a Mineral Resource or Ore Reserve under JORC, NI 43-101, S-K 1300 or SAMREC. Economic figures use a spot gold price of USD 4,037/oz and an 81% blended recovery assumption for scoping illustration only. Drilling and further study are required to confirm any mineralisation. Farmonaut provides mineral-intelligence analytics and is not a mineral producer, marketplace or regulatory body.
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