Prospecting & the exploration pipeline

Exploration is a funnel. You start with a whole region, narrow it to a few targets, and test those with the drill. Almost everything gets thrown away along the way, so the skill is in discarding cheaply and trusting only data you can defend.

By the end of this module, you will be able to
  • Name the stages of the exploration pipeline, and explain why so few prospects survive it
  • Describe how desktop study and field mapping decide where to look first
  • Explain how geochemistry tracks a deposit through streams, soils and rocks
  • Say what satellites can see, and how drilling turns a target into numbers
  • Explain how resources and reserves are classified, and why the reporting rules exist

The exploration funnel

The modules on ore deposits, magmatic, hydrothermal and sedimentary deposits explained how nature concentrates metals. Exploration is the practical business of finding those concentrations. It runs as a sequence of steps. Each one costs more per square kilometre than the last, so each step's real job is to decide where the next, more expensive step is worth spending money.

  1. Area selectionPick a region whose geology could host the deposit type you want.
  2. ReconnaissanceCheap, broad surveys: regional maps, stream samples, airborne data.
  3. Target generationNarrow down to a few square kilometres where several clues overlap.
  4. Target testingThe first drill holes. Is anything there?
  5. Resource definitionDrill on a closer grid to measure tonnes and grade.
  6. FeasibilityCan it be mined, processed and sold at a profit?
  7. MinePermits, finance, construction, production.
~1 in 1,000prospects that are explored end up as a mine (a widely quoted rule of thumb)
10–20 yrsis a common time from discovery to first production
Mostexploration money is spent on targets that turn out to be nothing
AREA STILL IN PLAY WHAT YOU DO THERE ~10,000 km² ~100 km² ~1 km² <1 Reconnaissance stream samples, one per ~5–10 km²; airborne surveys; old maps Target generation soil grids (~100 samples per km²), mapping, ground geophysics Target testing a handful of drill holes; each one can cost tens of thousands of dollars Resource definition dozens to hundreds of holes on a close grid
The funnel in numbers (orders of magnitude only; they vary a lot between projects). Each step keeps roughly a hundredth of the area, and the spending per square kilometre climbs steeply, from one sample per several square kilometres to many drill holes per hectare. That is why each cheap stage exists: to decide where the expensive one goes.

The odds are brutal because a mine needs many things to be true at once: enough metal, at a high enough grade (concentration), shallow enough, in a shape that can be mined, in rock the metal can be extracted from, near roads and power, with permits, finance and community consent. Exploration is the process of finding out which of those fail, as cheaply and as early as possible.

Desktop study and field mapping

The cheapest data is data someone has already collected. A desktop study gathers published geological maps, old reports, academic papers and records of past mining before anyone goes into the field.

In India the starting point is the Geological Survey of India (GSI). Its online portal, Bhukosh, serves geological maps alongside data from two nationwide programmes: the National Geochemical Mapping programme (systematic stream-sediment and soil sampling) and the National Geophysical Mapping programme (gravity and magnetic surveys), plus newer national airborne surveys. The National Mineral Exploration Policy (2016) aimed to make this baseline data public and to draw private explorers in. In 2023 the government named 30 critical minerals, from lithium to rare earths, and began auctioning blocks for them.

Old workings are another classic clue. Miners in India dug for gold, copper, lead and zinc centuries ago. Modern operations such as the Hutti gold field in Karnataka and the Zawar zinc–lead mines in Rajasthan sit on ground worked in ancient times. Old pits, slag heaps and village names that refer to metals all point to mineralised ground.

Then you go and look. Field mapping means walking traverses (planned lines across the country) and recording every outcrop, where bare rock pokes through soil. At each one the geologist notes the lithology, measures the orientation of layers, faults and veins (the structures from Folds, faults & deformation), and looks for alteration: rock that hot fluids have changed chemically, often bleached, clay-rich or stained.

Kit

Hand lens

A 10× magnifier for identifying minerals and textures in a fresh rock face. It is the most-used tool in geology.

Kit

Compass-clinometer

Measures the direction and angle of layers, faults and veins. Ore often follows structures, so their orientation tells you where to search next.

Kit

Hammer & GPS

Breaks off a fresh, unweathered sample, and records exactly where it came from. A sample without a location is worthless.

One of the most valuable things to spot is a gossan: a rusty, spongy cap of iron oxides left where sulphide minerals have weathered at the surface. The sulphur and many metals wash away, but the iron stays behind as red-brown limonite and goethite. A gossan is the weathered top of a sulphide body, and it can sit directly above ore.

hostrock rain + oxygen ↓ Gossan rusty iron oxides left behind Leached zone acid water dissolves the metals and carries them down Water table Supergene enrichment metals redeposit where the oxygen runs out; can be the richest ore Primary sulphide unweathered ore, as it formed
How a sulphide ore body weathers near the surface (schematic, not to scale; the zones are typically metres to tens of metres thick). Rainwater carrying oxygen turns sulphides into sulphuric acid, which dissolves metals such as copper and zinc and carries them down. Iron is far less mobile, so it stays at the top as a gossan. Below the water table, the level below which the ground is saturated, there is little oxygen, so the metals come back out of solution. In copper deposits this supergene enrichment blanket can be several times richer than the ore beneath it.

Geochemistry: following the chemical trail

Weathering slowly releases metals from a deposit into the soil and streams around it, creating a dispersion halo far larger than the deposit itself. Geochemistry measures this halo. A deposit a few hundred metres across can leave a detectable chemical signal kilometres downstream.

Stream-sediment surveys are the classic reconnaissance tool. A sample of fine sediment from a stream is a natural average of everything upstream of it: its whole catchment, the area that drains to that point. One sample can screen tens of square kilometres. When a sample comes back high, you sample further up each tributary until the signal disappears. The source lies between the last high sample and the first low one.

28 34 8 9 7 10 52 75 140 9 Source: gossan rusty outcrop at the stream head Follow it upstream values rise towards the source outlet
Background, under 20 ppm arsenicAnomalous, 20–100 ppmStrong, over 100 ppmCatchment boundary (drainage divide)Streams; numbers are arsenic in ppm
A stream-sediment survey in map view. Most tributaries return background arsenic. Values rise up one branch, from 28 and 34 ppm on the main river (diluted by clean sediment from the other branches) to 140 ppm just below a gossan. Arsenic here is a pathfinder for gold.

Once a catchment lights up, the work gets more detailed. Soil grids sample the ground on a regular pattern, say every 50 m along lines 200 m apart, to map the halo directly above the source. Rock-chip samples test individual outcrops and veins.

Explorers rarely measure only the metal they want. Gold occurs at parts per billion and is patchy, so they also measure pathfinder elements: elements that travel with the ore but are more abundant or more evenly spread, so their halo is larger and easier to detect. Arsenic and antimony are classic pathfinders for gold. Molybdenum points to porphyry copper systems (see Hydrothermal deposits).

Worked example: background vs anomaly

Every rock and soil contains some arsenic. Say 500 stream samples across a district have a median of 8 ppm, and 95% of them are below 20 ppm. That spread is the background, the normal variation for this geology. A common rule of thumb is to set a threshold at a high percentile, here 20 ppm, or at the mean plus two standard deviations of the log values. Samples above it are anomalies worth following up. The threshold has to be set separately for each rock type, because a granite and a black shale, for example, have very different natural backgrounds. The explorer below lets you test both rules.

Try it · where does background end?

A synthetic soil survey over a 6 × 4 km district. Granite in the west has low natural arsenic; black shale in the east has naturally high arsenic. Somewhere in the granite a small gold deposit leaks arsenic into the soil around it. Set the threshold and see which samples get flagged.

GraniteBlack shaleFlagged as anomalousTrue halo

Things to try: with one threshold for the whole district, most flags land on the shale, which is simply rich in arsenic, while much of the real halo in the granite goes unflagged. Tick "separate threshold for each rock type" and the halo appears. Then widen the grid spacing until the halo slips between the lines. Simplified: values are random draws from a log-normal background (a spread typical of geochemical data) plus a smooth halo; real halos are stretched by slope, groundwater and soil type. For log-normal data, the "mean plus two standard deviations of the logs" rule lands near the 97.5th percentile.

In the field

Portable XRF

A handheld X-ray fluorescence gun gives multi-element readings in about a minute. It is great for steering sampling in real time. It struggles with light elements and can't see gold at typical grades, and readings on rough, wet or dirty surfaces are approximate.

In the lab

Fire assay & ICP-MS

Fire assay, the standard for gold, melts the sample with a lead-based flux. The molten lead collects the gold, and is then burnt off to leave a tiny bead of precious metal. ICP-MS dissolves the sample, ionises it in a plasma and counts the atoms of dozens of elements at parts-per-billion levels.

Remote sensing: seeing minerals from orbit

Every mineral reflects sunlight in its own pattern across the visible and infrared, like a barcode. That pattern is its spectral signature. Clays and micas formed by alteration absorb strongly near 2.2 micrometres because of the bonds in their hydroxyl (OH) groups. Iron oxides such as hematite absorb blue light and have a broad dip near 0.9 µm, which is why they look red. A sensor that measures reflected light in the right wavelength bands can map these minerals from orbit.

B2B4B8B11B12 0.51.01.52.02.5 Wavelength (micrometres, µm) high low Reflectance Kaolinite (clay) Hematite (iron oxide) clay dip near 2.2 µm iron-oxide dip near 0.9 µm, and dark in the blue
Schematic spectra (not to exact scale). The shaded bars are some of Sentinel-2's bands. Clays are bright in band 11 and dark in band 12, so the ratio B11/B12 highlights them. Iron oxides are bright in red (B4) and dark in blue (B2), so B4/B2 highlights them. Hyperspectral sensors replace five broad bars with hundreds of narrow ones and can tell individual minerals apart.
Multispectral

Landsat, Sentinel-2, ASTER

Free satellite images in about 10 to 13 bands, with pixels about 10–30 m across. Band ratios pick out clay and iron-oxide alteration. ASTER's extra shortwave-infrared bands (data from 2000–2008) are still widely used for alteration mapping.

Hyperspectral

Hundreds of bands

Airborne scanners and newer satellites record a near-continuous spectrum for every pixel. They can distinguish kaolinite from alunite or white mica, which helps map the zoning around a porphyry or epithermal system.

LiDAR

Laser topography

Laser pulses from an aircraft or drone measure the ground surface to within centimetres, even through forest. They reveal faults, old workings and landforms hidden by vegetation.

Remote sensing only sees the top few micrometres of the surface. Soil, vegetation and monsoon cloud all get in the way, which is a real limitation in much of India. To see deeper you need geophysics, covered in Geophysical methods.

Drilling: the moment of truth

Every surface clue is indirect. Only a drill hole brings back rock from depth, so drilling is where most targets die. It is also the largest cost in exploration. There are two main methods.

Reverse circulation (RC)Diamond core
What comes upRock chips, blown up the inside of the drill pipe by compressed airAn intact cylinder of rock, cut by a diamond-studded bit (commonly about 5–6 cm across)
Cost & speedCheaper and faster per metreSlower and several times more expensive
What you learnChemistry and rough lithology, metre by metreEverything: textures, veins, fractures and the orientation of structures, plus samples for assay and testing
Typical useFirst-pass testing and infill drilling of known zonesKey holes, deep holes, and anything that needs geology or geotechnical detail
Try it · hole angle and true width

A cross-section through a mineralised vein 15 m thick that dips about 50° east. Three holes are aimed at the vein at different depths. Change the angle of the holes and watch how long a stretch of ore each one cuts.

W E Gossan Collars sandstone beds (fine lines) cut across by the vein true width open at depth 50 m
Intercept: length of ore along the holeTrue width: measured at right angles to the vein

Holes are usually drilled from the hanging-wall side (the side the vein leans over), angled to cut the ore as close to a right angle as possible. Each hole is recorded by its collar (where it starts), its azimuth (compass direction) and its dip (angle below horizontal). The intercept is only equal to the true width when the hole crosses the vein at exactly 90°, so reports quote both, or explain the difference. Simplified: real holes bend and are surveyed as they go, and real veins pinch and swell. The vein here continues below the section; explorers call that open at depth.

Core is laid out in trays and logged: a geologist records lithology, alteration, veins, minerals and structures metre by metre, and photographs every tray. The core is then sawn in half. One half is sent for assay and the other is kept as a permanent record.

Assay numbers are only as good as the process behind them, so every batch carries hidden checks called QA/QC (quality assurance and quality control). These are commonly inserted at around one in every 20 samples:

Blanks

Material known to contain no metal. If a blank comes back with gold, something is contaminating samples or mixing them up.

Standards

Certified reference materials with a precisely known grade. They check that the lab is accurate, not drifting high or low.

Duplicates

A second split of the same sample. Comparing the pairs measures precision, and shows how much grade varies at small scale.

Standard, certified at 1.50 g/t gold 1.30 1.40 1.50 1.60 1.70 batch 12 fails Blanks, should contain no gold 0.0 0.5 1.0 fail above ~0.05 g/t batch 7 blank: 0.8 g/t 1 5 10 15 20 gold, g/t gold, g/t Assay batch
Warning limit, ±2 standard deviationsFail limit, ±3 standard deviations
A control chart plots each batch's check sample against fixed limits. On the top chart the standard wanders within its expected spread until batch 12, which fails: the whole batch is re-assayed. On the bottom, the blank in batch 7 returns 0.8 g/t gold, so something carried gold over between samples or labels were swapped. One point beyond the warning lines is normal; a fail, or a run of points drifting to one side, triggers an investigation. (Illustrative numbers.)

From drill holes to a resource you can report

With enough holes, geologists build a 3D model of the ore body and estimate its tonnes and grade between the holes. How much that estimate can be trusted depends on how closely spaced the holes are and how continuous the geology is. Reporting codes sort estimates by confidence. Australia's JORC Code, Canada's CIM Definition Standards (required under its NI 43-101 rules) and others are aligned with a common template set by an international committee, CRIRSCO. (India's own system is based on the UN Framework Classification.)

more knowledge and confidence Exploration results MINERAL RESOURCES Inferred Indicated Measured ORE RESERVES Probable Proved cannot become a reserve Modifying factors mining, processing, economic, legal, environmental, social
The resource/reserve matrix used by JORC and other CRIRSCO-style codes. A mineral resource is a concentration with reasonable prospects of eventual extraction. An ore reserve (a "mineral reserve" in some codes) is the part that can be mined at a profit once the modifying factors have been studied. Inferred is too uncertain to convert. Measured can become Proved (called "Proven" in Canada), or Probable if the modifying factors are less certain.

Why so much formality? Because exploration companies raise money from investors who cannot check the rocks themselves. The cautionary tale is Bre-X. In the mid-1990s this small Canadian company claimed an enormous gold discovery at Busang in Indonesia, and its share value rose to several billion dollars. In 1997 independent check drilling found almost no gold. The crushed core samples had been "salted" with gold from elsewhere. The fraud destroyed billions in savings, and it helped lead to Canada's NI 43-101 rules in 2001 and tighter codes worldwide.

Today a public report of resources or reserves must be signed off by a Competent Person (a "Qualified Person" in Canada). This is a member of a recognised professional body with relevant experience in that type of deposit, who is personally accountable for the numbers. Chain of custody, QA/QC and transparent methods are what make those numbers defensible.

The modern toolkit

Exploration now produces huge, mixed datasets: geology maps, thousands of assays, geophysical grids, satellite spectra and drill logs. Data integration layers all of them in a geographic information system (GIS). Prospectivity mapping then scores every map cell by how many favourable ingredients overlap, increasingly using machine learning trained on known deposits. The output is a probability map, not an answer: it ranks where to spend the next field season, and it is only as good as the data and geological ideas it is built on.

Try it · find it on a budget

The same kind of district, with a new hidden deposit, which could sit under either rock type. You have $600k. Move the cross-hair (tap or click the map, or focus the map and use the arrow keys), then choose what to spend on. The deposit is only about 400 m across, so a hole has to land within about 200 m of its centre.

Granite (background ~6 ppm As)Black shale (background ~18 ppm As)

How to read the clues: a stream sample averages its whole block, so compare it with the background of the rocks in that block, not with other blocks. A soil grid shows the halo; flagged dots use a separate threshold for each rock type. Simplified: blocks stand in for stream catchments, costs are illustrative, and a real programme would also use mapping and geophysics.

Exploration is a series of cheap tests that each throw away most of the map. The rare survivor earns the expensive test.
Why this matters at Alt Earth

This is the day-to-day work of mineral exploration, and it maps closely onto carbon removal. Carbon removal has to prove that something happened underground or in a soil profile that nobody can see directly. That is exactly the explorer's problem. Measuring how much spread basalt has weathered in a field uses the same toolkit: a sampling design that captures natural variability, geochemical analysis such as XRF and ICP-MS, blanks, standards and duplicates in every batch, and reporting that a sceptical third party can audit. The explorer's background-versus-anomaly thinking carries over directly to telling a real weathering signal from the natural variation between soil samples. Bre-X is a reminder of why verification registries insist on independent checks.