Map Layers Guide
What each layer on the GeaSpirit map shows, where it comes from, how to read it — and, just as important, what it does not mean.
How to read GeaSpirit maps
1 · Data
What has actually been measured or reported — mines, volcanoes, springs, plate boundaries.
2 · Signal
What an analytical layer detects by combining data — for example the prospectivity screening layer.
3 · Interpretation
What you infer by reading several layers together. GeaSpirit gives you the data and the signal; the interpretation is yours.
Data ≠ discovery · Signal ≠ deposit · Prospectivity ≠ probability · Priority ≠ certainty
Three kinds of layer
A source measurement or map, shown as-is.
Calculated by GeaSpirit from one or more sources.
An interpretive output built for prioritisation.
Mineral Prospectivity — in depth
Mineral Prospectivity is a screening layer that highlights areas where the available evidence is comparatively more favourable for further mineral investigation.
The score is not a probability
A prospectivity score of 33 / 100 does NOT mean a 33% chance of finding a deposit. It means that, according to the evidence the model uses, this cell scores relatively modestly compared with stronger areas. We show it as a 0–100 screening score, not a percentage, precisely to avoid that misreading.
What one grid cell means
Each value represents an area, not an exact point. A 0.25° cell is roughly 25 km across (varying with latitude), so the score is regional prospectivity — a place to look harder, never a drilling target.
Colour scale
- Strongest — converging evidence
- Elevated
- Moderate
- Low–moderate
- Emerging / weaker
Colour represents the model score only. It does NOT represent deposit size, grade, economic viability, reserves, or the probability of a commercial discovery.
What “evidence fusion” means
Evidence fusion means the layer combines several independent signals into one screening surface, instead of relying on a single map. GeaSpirit learns, from 166k known mines, how strongly each control predicts mineralisation, then fuses them.
- Plate boundaries (by type)
- Cenozoic volcanoes
- Thermal springs
- Impact structures
- Known-mine density
Illustrative interpretation
Prospectivity score 33 / 100
This area shows some evidence of mineral interest, but it is not among the stronger areas identified by the current model. It may justify contextual review alongside other geological evidence, but the prospectivity layer alone does not justify fieldwork or drilling.
Prospectivity score 82 / 100
This area is comparatively strong within the current screening model and may deserve closer investigation. Even so, a high score does not confirm mineralisation, grade, tonnage or economic viability.
Oil & Gas — in depth
Two layers carry hydrocarbons, at two different scales, and the difference between them is the single most important thing on this page. A petroleum province is a basin-scale assessment domain. An oil or gas field is one accumulation. Reading one as the other is how a map that says “this region was studied” gets mistaken for a map that says “something was found here”.
Petroleum is not mineral evidence
GeaSpirit is not a hydrocarbon exploration platform and does not become one by carrying these layers. A field’s presence, its absence, the distance to it and the density of fields around it all carry weight zero in every GeaSpirit mineral model, and no prospectivity weight was changed to add them. They are here because a century of petroleum work produced some of the densest descriptions of the deep subsurface that exist — basin geometry, stratigraphy, faults, traps, depth, thermal history, fluid migration — and that description stays useful when the question is a completely different one.
Province is not field
A province can span a thousand kilometres and contain many petroleum systems and hundreds of fields; the USGS defined 1,023 of them and formally assessed 121. A field is a single documented accumulation with a name, an operator and a licence. GeaSpirit carries 545 of those, from the only two national regulators that publish at field level under terms permitting redistribution. Nothing in the province layer marks a discovery, and nothing in the field layer describes a basin.
Documented, and modelled — not the same claim
A single province popup mixes two kinds of statement, and they are tagged so they cannot be read alike. Documented is what the assessment recorded as already found by its date. Assessed / modelled is a statistical estimate of what had not been found yet. One is a record; the other is a projection, and no amount of confidence in the source turns the second into the first.
The units, and the mistake they caused
The assessment publishes in millions and billions, not billions and trillions, and the two are a thousand apart. GeaSpirit briefly displayed the raw numbers under converted labels, so West Siberia appeared to hold 1,270,049 TCF of gas — roughly two hundred times the proved reserves of the entire planet — and it read as a fact because it had a source line under it. The store now keeps the raw value under a key that names the raw unit, and the popup divides and says which number it is showing.
- MMBO — million barrels of oil. 139,913 MMBO = 139.913 BBO.
- BCFG — billion cubic feet of gas. 1,270,049 BCFG = 1,270.049 TCF.
- MMBOE — million barrels of oil equivalent. 182,864 MMBOE = 182.864 BBOE.
Assessment vintage: 2000
Almost every number in the province layer comes from the USGS World Petroleum Assessment of 2000. Known means cumulative production plus remaining reserves at that date — not current reserves, not today’s production. Mean undiscovered technically recoverable petroleum means the assessment’s central estimate of conventional petroleum that had not been found and that its assumptions judged recoverable with applicable technology. It is not a proved reserve, not a discovered resource, and says nothing whatever about economics. Technically recoverable and economically recoverable are different questions, and only the first is answered here.
Three provinces, read properly
West Siberian Basin — a large documented province
Known oil 139.913 BBO, known gas 1,270.049 TCF, mean undiscovered 182.864 BBOE. Read: an enormous quantity of petroleum had already been found here by 2000, and the assessment estimated a great deal more remained undiscovered. It does not say those are reserves available today, and it says nothing about minerals.
Provence Basin — zero known, and not a contradiction
Known oil 0, known gas 0, mean undiscovered 11.188 BBOE. Nothing had been found, and the geology was still assessed as capable of holding something. Zero known petroleum is not zero potential; it is an absence of discoveries, which is a fact about exploration history rather than about the rocks.
Rutbah Uplift — the same shape, much smaller
Known oil 0, known gas 0, mean undiscovered 0.369 BBOE. The same distinction as Provence at a fraction of the size. Comparing this number with West Siberia’s compares two estimates, not two discoveries — and a small undiscovered estimate is not evidence that a province is barren.
Half of this map is exploration history
This is the sharpest bias on the site and both layers carry it. The province map shows where petroleum was looked for and found, which makes it a map of commercial drilling history as much as of geology. The field map is worse: essentially all of it is the North Sea, because that is where two governments publish field data anyone may redistribute — not where the world’s oil is. Dense petroleum data does not mean better geology, and a blank region means an absent dataset, never absent geology and never absent hydrocarbons.
No petroleum data is not counter-evidence
A region with no fields may never have been explored, may have no public records, may have unsuitable hydrocarbon geology, or may simply have had no commercial drilling. Those are four different findings and the map cannot tell them apart. This follows the rule the whole platform runs on: NO_EVIDENCE_FOUND is not COUNTER_EVIDENCE. An absence of information can only ever be recorded as an absence of information.
Produced and formation waters
Some formation and produced waters carry lithium, bromine, iodine, boron or strontium, and that is genuinely interesting. It is also the point where a screening platform most easily starts inventing deposits, so the chain is stated rather than skipped: an element being present is not a concentration; a concentration is not a resource; a resource is not recoverable; and recoverable is not economic. GeaSpirit does not present brines as a mining opportunity without evidence specific to that brine.
What is public, and what is not
Public: province and field identity, country, basin, hydrocarbon type, status, the regulators’ published attributes, the historical assessment metrics, and the source and licence of each. Private, where it is held at all: well-level data, formation tops, wireline logs, core descriptions, pressure, temperature, fluid and produced-water chemistry, seismic interpretation, reservoir geometry and basin models. A dataset being ingested is not a reason to publish it, and the licence it arrived under decides that, not us.
What these layers cannot do
A 2000 assessment vintage. Uneven global exploration and a heavy commercial bias. Province-level generalisation where field-level detail would be better. Field coverage that is national, not global, and will stay that way until more regulators publish under terms permitting reuse. Differing national reporting standards. Proprietary subsurface datasets excluded on purpose. And estimates that were made under technical and economic assumptions which have moved since — a resource estimate is not a reserve, and neither is a promise.
Source and provenance
Provinces: USGS, Geologic Provinces of the World, 2000 World Petroleum Assessment — a work of the United States Government, public domain. Fields: Norway’s Sokkeldirektoratet under the Norwegian Licence for Open Government Data, and the United Kingdom’s North Sea Transition Authority under its Open User Licence. Licensed commercial datasets — S&P, Wood Mackenzie, Rystad — are not used and are not redistributed. Every attribute traces to the regulator that published it.
One layer is never the whole answer
A strong signal in a single layer should normally be checked against independent evidence before you draw any conclusion. GeaSpirit is designed to be read in combination.
Prospectivity + Geology + Geophysics + Mineral occurrences + Historical mining → better context
Every layer, explained
MinesDerived signal
- What is this?
- Every known mining asset GeaSpirit tracks — abandoned, historical, care-and-maintenance and active — mapped from open data.
- What does it measure?
- The presence and open-data profile of a mining asset, summarised by the GeaSpirit Score (0–100).
- What data does it use?
- Open sources — MRDS (USGS), OpenStreetMap, Wikidata and national geological databases — consolidated and de-duplicated.
- How should I read it?
- Each marker is one asset. Click it for its GeaSpirit Score and the open evidence behind it.
- What does a high value mean?
- A higher GeaSpirit Score means stronger, more consistent open-data signal — a better candidate to look at first.
- What does a low value mean?
- A lower score means thin or conflicting open data, not that the site is worthless.
- What does it NOT mean?
- The score is not a valuation, a reserve estimate, or a promise of economic mineral.
- Spatial resolution
- Point locations at source precision; coverage is global but uneven between countries.
- Main limitations
- Reporting bias is real — well-surveyed regions look denser. An empty area is not proof there is nothing there.
- Use with other layers
- Cross-check a promising asset against prospectivity, geology and historical mining before drawing conclusions.
- Source / provenance
- GeaSpirit asset database (open data), continuously curated.
- Last data/model version
- Rebuilt each release; the current build tag is shown in the footer.
Technical details
328,183 assets. The GeaSpirit Score is a four-dimension open-data score (see Methodology). Provenance is traceable per asset; no operator-claimed figure is treated as verified unless open-data-backed.
TV-featured minesDerived signal
- What is this?
- Mines that have appeared in mining television shows, highlighted purely for context and interest.
- What does it measure?
- Whether a mine has been featured on screen (Gold Rush, Bering Sea Gold, Ice Cold Gold…).
- What data does it use?
- A curated overlay (tv_mines.json) plus (Show)-tag detection in the asset database.
- How should I read it?
- The spotlight marks a featured mine; toggle the layer to highlight them.
- What does a high value mean?
- Not applicable — this is a category/flag layer, not a score.
- What does a low value mean?
- Not applicable — this is a category/flag layer, not a score.
- What does it NOT mean?
- Being on television says nothing about a mine's geology, grade or economic potential.
- Spatial resolution
- Point locations; a small curated subset only.
- Main limitations
- Curated and incomplete; we never loose-name-match the full database, to avoid false positives.
- Use with other layers
- Use it as colour and context, never as an evidence signal.
- Source / provenance
- Curated tv_mines.json + database Show tags.
- Last data/model version
- Updated as new episodes and mines are curated.
Technical details
Matching is by curated identity, not fuzzy name search across the 166k+ database.
Strategic & quantum materialsDerived signal
- What is this?
- Assets whose commodities are strategic, critical or quantum-relevant.
- What does it measure?
- The presence of a strategic commodity on an asset (rare earths, Li, Co, Nb, Ta, graphite, etc.).
- What data does it use?
- The commodity fields of the GeaSpirit asset database.
- How should I read it?
- A marker is an asset carrying at least one strategic commodity.
- What does a high value mean?
- Not applicable — this is a category/flag layer, not a score.
- What does a low value mean?
- Not applicable — this is a category/flag layer, not a score.
- What does it NOT mean?
- A tag does not confirm quantity, grade, or that the commodity is currently recoverable.
- Spatial resolution
- Point locations; a global subset of the mines layer.
- Main limitations
- Commodity tags come from the source data and can be incomplete or approximate.
- Use with other layers
- Pair with prospectivity and geology to see where a strategic commodity sits in a favourable setting.
- Source / provenance
- GeaSpirit asset database commodity attributes.
- Last data/model version
- Rebuilt each release.
Technical details
A filtered view of the mines layer, not a separate dataset.
Rare earthsObserved data
- What is this?
- Known and prospective rare-earth (REE) host sites from public data.
- What does it measure?
- Whether a site is a known REE host or a prospective/theorised host.
- What data does it use?
- ree_sites.json and ree_public_enrichment.json — public REE occurrences and geological context.
- How should I read it?
- Solid markers are known REE hosts; lighter markers are prospective hosts inferred from public geology.
- What does a high value mean?
- “Known” hosts are better-evidenced than “prospective” ones — start there.
- What does a low value mean?
- “Prospective” means geological context only, not a confirmed occurrence.
- What does it NOT mean?
- Prospective is not confirmed — and this is NOT the private, gated prospectivity dataset.
- Spatial resolution
- Point locations; global public REE hosts.
- Main limitations
- Public REE data is sparse and patchy; absence usually reflects a lack of surveying.
- Use with other layers
- Read alongside geology, tectonics and prospectivity for context.
- Source / provenance
- Public REE datasets + conservative GeaSpirit enrichment.
- Last data/model version
- Rebuilt each release.
Technical details
Prospective flags are conservative geological-context inferences, not model targets.
VolcanoesObserved data
- What is this?
- Cenozoic volcanoes from open catalogues.
- What does it measure?
- The location of volcanoes active during the Cenozoic.
- What data does it use?
- Open volcano catalogues (Cenozoic subset).
- How should I read it?
- Each marker is a volcano location.
- What does a high value mean?
- Not applicable — this is a category/flag layer, not a score.
- What does a low value mean?
- Not applicable — this is a category/flag layer, not a score.
- What does it NOT mean?
- Volcanism is geological context; on its own it does not imply mineralisation or a deposit.
- Spatial resolution
- Point locations; global.
- Main limitations
- Catalogue completeness varies; dating and classification differ between sources.
- Use with other layers
- Useful next to tectonics and prospectivity for epithermal and porphyry settings.
- Source / provenance
- Open Cenozoic volcano catalogue.
- Last data/model version
- Static open dataset.
Technical details
A Cenozoic filter of a global volcano catalogue; one of the prospectivity model's inputs.
Tectonic platesObserved data
- What is this?
- Plate boundaries, coloured by type.
- What does it measure?
- Where plate boundaries run and what type they are — subduction, ridge, rift, collision, transform.
- What data does it use?
- An open plate-boundary model.
- How should I read it?
- Each line is a plate boundary; its type controls which deposit styles are plausible nearby.
- What does a high value mean?
- Not applicable — this is a category/flag layer, not a score.
- What does a low value mean?
- Not applicable — this is a category/flag layer, not a score.
- What does it NOT mean?
- A boundary nearby does not place a deposit there; this is regional context.
- Spatial resolution
- Regional lines, not a local structural map.
- Main limitations
- Generalised geometry; local faults and structures are not shown.
- Use with other layers
- The backbone for interpreting prospectivity and volcano/thermal patterns.
- Source / provenance
- Open plate-boundary dataset.
- Last data/model version
- Static open dataset.
Technical details
Boundaries are typed for the prospectivity model's tectonic controls.
Heritage minesObserved data
- What is this?
- Historic and heritage mining sites.
- What does it measure?
- Mines flagged as historically or culturally significant (an Era facet over the database).
- What data does it use?
- Open data (Wikidata / OpenStreetMap) with an Era classification.
- How should I read it?
- A marker is a historically significant mine.
- What does a high value mean?
- Not applicable — this is a category/flag layer, not a score.
- What does a low value mean?
- Not applicable — this is a category/flag layer, not a score.
- What does it NOT mean?
- Heritage status is cultural-historical; it does not imply remaining economic mineral.
- Spatial resolution
- Point locations; curated and uneven.
- Main limitations
- Coverage depends on what open sources record as heritage.
- Use with other layers
- Historical mining is a strong contextual clue next to prospectivity and geology.
- Source / provenance
- Open heritage / historic-mine data.
- Last data/model version
- Rebuilt with the asset database.
Technical details
Modelled as an Era facet plus a badge, not a separate asset role.
Impact cratersObserved data
- What is this?
- Confirmed terrestrial impact structures.
- What does it measure?
- The location of confirmed meteorite-impact craters.
- What data does it use?
- An open impact-structure database.
- How should I read it?
- Each marker is a confirmed impact crater.
- What does a high value mean?
- Not applicable — this is a category/flag layer, not a score.
- What does a low value mean?
- Not applicable — this is a category/flag layer, not a score.
- What does it NOT mean?
- A few impacts host minerals (e.g. Ni-Cu at Sudbury) but most do not — this is context, not a target.
- Spatial resolution
- Point locations; global.
- Main limitations
- Only confirmed structures; eroded or buried craters may be missing.
- Use with other layers
- Rarely decisive; occasionally relevant to specific deposit styles.
- Source / provenance
- Open impact-crater database.
- Last data/model version
- Static open dataset.
Technical details
Confirmed structures only; suspected craters are excluded.
MeteoritesObserved data
- What is this?
- Recovered meteorite finds and observed falls.
- What does it measure?
- Where meteorites have been recovered.
- What data does it use?
- An open meteorite catalogue (finds and observed falls).
- How should I read it?
- A marker shows where a meteorite was recovered, not where anything formed geologically.
- What does a high value mean?
- Not applicable — this is a category/flag layer, not a score.
- What does a low value mean?
- Not applicable — this is a category/flag layer, not a score.
- What does it NOT mean?
- This is scientific and mineralogical context, not a mining target.
- Spatial resolution
- Point locations; global but recovery-biased.
- Main limitations
- Strongly biased toward deserts and ice, where meteorites are easy to find.
- Use with other layers
- Educational and mineralogical context; not part of prospectivity.
- Source / provenance
- Open meteorite catalogue.
- Last data/model version
- Static open dataset.
Technical details
Includes thumbnails and photos where available; no economic interpretation.
Mineral prospectivityModelled layer
- What is this?
- A screening layer that highlights where the available open evidence is comparatively more favourable for further mineral investigation.
- What does it measure?
- A relative, model-based prospectivity signal per grid cell — not a probability of discovery.
- What data does it use?
- A Weights-of-Evidence model over open layers — plate boundaries by type, Cenozoic volcanoes, thermal springs, impacts, and known-mine density — learned from 166k known mines.
- How should I read it?
- Colour and score run blue (emerging) → red (high) on a 0–100 scale. Higher means the model sees more converging favourable evidence, so it deserves earlier attention.
- What does a high value mean?
- A high score (e.g. 82/100) means the cell is comparatively strong within this screening model — worth closer, independent study.
- What does a low value mean?
- A low score (e.g. 33/100) means comparatively modest evidence; it may still merit contextual review, but not fieldwork on its own.
- What does it NOT mean?
- The score is NOT a probability: 33/100 is not a 33% chance of finding a deposit. It says nothing about grade, tonnage, economics, or exactly where to drill.
- Spatial resolution
- A 0.25° grid — each cell is roughly 25 km across. It indicates regional prospectivity, never a drilling target.
- Main limitations
- Model-dependent; it assumes the input layers are independent (only approximately true); it inherits their uneven coverage; the public view is deliberately coarse.
- Use with other layers
- Treat it as a first filter. Confirm a strong cell against geology, mineral occurrences and historical mining before concluding anything.
- Source / provenance
- /data/prospectivity.json, built by GeaSpirit's Weights-of-Evidence engine and back-tested on a held-out split (lift vs random is shown in the legend).
- Last data/model version
- Prospectivity engine v2 (data-driven WofE); rebuilt each release.
Technical details
A WofE posterior (sigmoid of the prior logit plus the sum of learned weights) on a 0.25° raster. The deposit-type label comes from genetic rules (porphyry Cu-Au-Mo, epithermal Au-Ag, VMS Cu-Zn, carbonatite REE-Nb, orogenic gold). Weights, thresholds and the ranked frontier targets are not public.
Thermal springsObserved data
- What is this?
- Thermal (hot and warm) springs from open data.
- What does it measure?
- The location of thermal springs.
- What data does it use?
- Open thermal-spring datasets.
- How should I read it?
- A marker is a thermal spring, which can indicate an active hydrothermal system.
- What does a high value mean?
- Not applicable — this is a category/flag layer, not a score.
- What does a low value mean?
- Not applicable — this is a category/flag layer, not a score.
- What does it NOT mean?
- A spring nearby is indirect context, not evidence of a deposit.
- Spatial resolution
- Point locations; global, curated.
- Main limitations
- Coverage varies by country; classification differs between sources.
- Use with other layers
- One of the prospectivity model's inputs; useful next to volcanoes and tectonics.
- Source / provenance
- Open thermal-spring data.
- Last data/model version
- Static open dataset.
Technical details
Used as a hydrothermal proxy in the prospectivity model.
Paleo-tectonicsModelled layer
- What is this?
- Deep-time paleogeographic reconstructions, such as paleo-coastlines.
- What does it measure?
- Reconstructed ancient geography, for interpretive context.
- What data does it use?
- Published paleogeographic reconstructions.
- How should I read it?
- Lines show where ancient coastlines and features are reconstructed to have been.
- What does a high value mean?
- Not applicable — this is a category/flag layer, not a score.
- What does a low value mean?
- Not applicable — this is a category/flag layer, not a score.
- What does it NOT mean?
- Reconstructions are models, not observations; do not read them as precise.
- Spatial resolution
- Coarse, time-averaged lines; global.
- Main limitations
- Real uncertainty grows with age, and different models disagree.
- Use with other layers
- An interpretive backdrop for deposits whose formation was controlled by ancient geography.
- Source / provenance
- Published paleogeographic reconstruction data.
- Last data/model version
- Static reconstruction dataset.
Technical details
Rendered as coarse rings and lines; interpretive only.
Petroleum Provinces — Subsurface ContextObserved
- What is this?
- The world’s petroleum provinces as defined and assessed by the USGS — 1,023 provinces, 121 of them formally assessed. It shows where hydrocarbons have been found and studied, at province level, not at field level.
- What does it measure?
- How thoroughly the deep subsurface of a region has been investigated. A petroleum province is one of the very few places on Earth where basin geometry, stratigraphy, faults, traps, depth, temperature, pressure and fluid migration have all been mapped — usually across decades of seismic surveys and wells.
- What data does it use?
- USGS, Geologic Provinces of the World, 2000 World Petroleum Assessment — a work of the United States Government, public domain. Field-level coverage is a separate layer below, built from national regulators — Norway (SODIR, NLOD) and the United Kingdom (NSTA) — and added country by country rather than claimed globally. A rights-clear GLOBAL field dataset (Global Energy Monitor, CC BY 4.0) is distributed through a request form and is not ingested.
- Why does GeaSpirit include it?
- Not to look for hydrocarbons. Mineral systems and petroleum systems are different phenomena, but both are shaped by the same things: sedimentary basins, large faults, permeability, fluid circulation, stratigraphy, thermal history and deep structure. A century of petroleum exploration has produced some of the richest descriptions of the subsurface that exist anywhere, and that description remains useful when reading a completely different question. A depleted field can be a better geological archive than a producing one.
- What does it NOT prove?
- That a mineral deposit exists nearby. The presence of an oil or gas field is not mineral evidence, distance to one is not mineral evidence, and neither is the number of fields or how much they produced. GeaSpirit does not use proximity to a petroleum province in any mineral score, and no prospectivity weight was changed to add this layer. Equally, the absence of petroleum is not counter-evidence — it may mean only that nobody ever drilled there for hydrocarbons. Some deposit models (carbonate-hosted Pb-Zn, sediment-hosted copper, sandstone uranium, evaporite basins) do have a documented relationship with basin fluids, and for those the basin description may one day be relevant — but only where the geology is shown, never assumed.
- What bias does it carry?
- A severe one, and it must be read with it. This map shows where petroleum was looked for and found, which is a map of commercial drilling history as much as of geology. A basin with no assessed province may be geologically ordinary, or it may simply never have interested an oil company. Reading the blank areas as geologically uninteresting would be exactly the wrong conclusion.
- Public or private?
- The province map is public. Well-level information, formation tops, logs, seismic interpretation, pressure, temperature, fluid and produced-water chemistry and basin models stay in Private Intelligence where they are held at all, under the rights of whichever national source they came from.
Oil & Gas Fields — Subsurface ContextObserved
- What is this?
- Individual documented oil and gas fields — 545 of them, from two national regulators. A petroleum province is a basin-scale assessment domain and can span a thousand kilometres; an oil or gas field is one accumulation, with a name, an operator and a licence. The province layer above and this one answer different questions, which is why they are two layers and not one.
- What does it measure?
- Where subsurface investigation is at its most intense. A province says the deep geology of a region has been studied; a producing field says one specific structure has been drilled, logged, cored, pressure-tested and re-modelled for decades. Both are useful, at different scales: the province gives basin context, the field gives a local investigation footprint.
- What data does it use?
- Norway — Sokkeldirektoratet (SODIR) factpages, under the Norwegian Licence for Open Government Data: 142 fields with operator, status, hydrocarbon type, discovery wellbore and recoverable reserves. United Kingdom — North Sea Transition Authority petroleum field determinations, under the NSTA Open User Licence: 403 offshore and onshore fields. Neither regulator publishes a point for a field, because a field is an area, so each coordinate says which kind of centre it is: the centroid of the regulator’s outline, or the mean position of the field’s wellbores. Licensed commercial datasets (S&P, Wood Mackenzie, Rystad) are not used.
- Why does GeaSpirit include it?
- For the same reason as the provinces, one scale finer. A depleted field is one of the best-described volumes of rock on Earth — its stratigraphy, faults, seals, depth, temperature, pressure and fluid history are all on record — and that description stays useful when the question is a completely different one. It also makes the province layer honest: with fields on the map, nobody can read a province outline as if it marked a discovery.
- What does it NOT prove?
- That there is metal anywhere near. A field’s presence, absence, distance and density all carry weight zero in every GeaSpirit mineral model, and no prospectivity weight was changed to add this layer. It also proves nothing about the field itself beyond what its regulator published: a determination is a legal boundary, not a statement that the field is producing.
- What bias does it carry?
- The sharpest on the site, and the map looks wrong until you know it: essentially all of it is the North Sea. That is not where the world’s oil is — it is where two governments publish field data anyone may redistribute. Most producing countries either do not publish at field level or do not publish under terms that permit reuse. Empty regions here mean an absent DATASET, never absent geology and never absent hydrocarbons.
- Public or private?
- The field identities, boundaries centroids and the regulators’ published attributes are public. Well logs, formation tops, pressure and temperature measurements, fluid and produced-water chemistry, seismic interpretation and basin models are not, and stay in Private Intelligence under the rights of whichever national source they came from.
From map layers to Evidence Compass
Map layers let you explore individual evidence sources visually. Evidence Compass is GeaSpirit's private decision-support architecture that evaluates multiple evidence families together, separates Priority from Confidence, weighs counter-evidence, and suggests where further investigation may be justified.
From maps to decisions
How GeaSpirit turns geospatial evidence into an auditable investigation pathway. The layers above tell you where to look. What follows is what happens after that, and it is three tools and one habit: replace inference with evidence, and say which of the two you are holding.
Mineral Prospectivity → Tailings Intelligence → Evidence Compass → Evidence Passport → Next Best Test
Not every asset travels the whole path, and most stop early. That is the point of having a path: it costs almost nothing to stop something at the first step and a great deal to stop it at the last.
POSSIBLE → SUPPORTED → MEASURED → QUANTIFIED → TESTED FOR RECOVERY
Almost everything in the world sits on the first two rungs. Very little reaches the fourth. Nothing reaches the fifth without physical laboratory work, which no amount of data can substitute for.
Three tools, one system
Residual Resource Intelligence and Next Best Test are engines the system uses, not further products competing with these three.
Tailings Intelligence
- What is this?
- A global inventory of real extractive-waste facilities, built from official national registers rather than from estimates — and a record, for each one, of what can honestly be said about what it contains.
- Does it call everything tailings?
- No, and that distinction does real work. A facility is classified as tailings, waste rock, quarry waste, processing residue, heap-leach residue, ore stockpile (never processed), slag, washing sludge, or other extractive waste — using the publisher's own word, which is kept verbatim beside ours. A sand-and-gravel washing pond and a lead-zinc impoundment sit in the same official inventories and look alike from the air.
- What does it connect?
- Where the evidence allows it: waste facility → source mine → geology → mineralogy → elements → measured chemistry → quantity → ownership → processing context. Where the evidence does not allow it, the chain stops and says where.
- How strong is the evidence?
- Every element on every facility carries one of six states, and they never merge: measured in the waste; carrier mineral seen in the waste; element reported at the source deposit; constituent of a documented source mineral; host-mineral supported; inferred from a verified deposit model.
- What does it NOT mean?
- “Germanium is associated with sphalerite” does not mean germanium has been measured in this waste. It means there is a documented mineral reason to go and look. The two statements are one click apart on the card and are never printed as the same thing.
- Two different confidences
- Whether the FACILITY is real and whether the ELEMENT evidence is strong are separate questions with separate answers. A facility can be verified from an official national inventory while the case for a particular element in it rests on a host-mineral relationship. Those two confidences are never fused into one.
- A worked example
- A facility is linked to a zinc-lead mine and the source reports sphalerite. Zinc has constituent-mineral evidence; germanium has host-mineral evidence; the waste chemistry is unknown. GeaSpirit can justify investigating germanium here. It cannot claim germanium is present at any concentration, and it does not.
Evidence Compass — the reasoning layer
- What is this?
- Not another map. It is the layer that asks why an asset deserves attention at all, by bringing separate families of evidence together and looking for where they agree and where they contradict each other.
- Priority is not confidence
- They are two axes, deliberately. High priority with low confidence means this could matter and critical evidence is missing — which is a reason to go and look, not a conclusion. High priority with high confidence means several independent lines agree. Low priority does not mean worthless; it usually means the evidence is thin. These are screening instruments, not probabilities of discovery.
- Counter-evidence
- The system keeps what argues AGAINST a hypothesis, not only what argues for it — together with what is missing and what contradicts. Favourable mineralogy with measured chemistry at background is not an open question; it is a weaker case, and the platform records it as one.
- Residual Resource Intelligence
- Four separate questions that are never collapsed into one number. Presence — is there evidence the element may be there? Retention — is there a reason the historical process would have left it behind? Concentration — do we know how much? Recoverability — is there evidence any of it could be recovered? Presence is not retention, retention is not concentration, and none of them is recoverability.
- RRI, worked through
- A mine processed zinc ore and sphalerite is documented; germanium can sit in sphalerite, so presence is supported. If the historical route suggests sphalerite remained, retention is plausible. With no assays, concentration is unknown. With no testwork, recoverability is unknown. The conclusion is therefore not “a recoverable germanium resource”. It is “a defensible candidate for further investigation”, which is a different sentence and a much more useful one.
Evidence Passport — from evidence to decision
- What is this?
- One auditable document per facility answering four questions: what do we know, what is inferred, what is missing, and what should happen next. UNKNOWN is a valid answer and appears constantly — a passport that had no unknowns on it would be describing a mine, not a waste facility.
- What is on it?
- Identity · waste type · source mine · geology · mineralogy · element evidence · measured chemistry · quantity and mass · indicative contained amount · historical process · retention · concentration · recoverability · owner · missing evidence · next best test · what would change the decision · provenance. Not every field is available for every facility, and the passport says which.
- Is there a score?
- No, and that is deliberate. One number would collapse “we know a lot and it is poor” into the same value as “we know almost nothing” — opposite situations that call for opposite next actions. What is shown is evidence completeness: how much of the document is filled in. It measures the document, not the asset.
- Quantity and mass
- A documented VOLUME, a measured MASS and an ESTIMATED MASS RANGE are three different things. Most registers publish a volume; turning it into a mass needs a bulk density, and where no density has been measured one is borrowed from the engineering literature as a range — so the mass is a range too. An estimated mass is not a measured tonnage, and a single tidy figure would claim a density nobody weighed.
- Measured chemistry
- Three distinctions that are easy to lose and expensive to lose. Solid-phase chemistry is how much of an element is in the material. Leachate chemistry is how much came out in a leaching test — an environmental question, typically orders of magnitude smaller, and never a grade. A value below the detection limit is neither a measurement nor a proof of absence; it is a ceiling.
- Indicative contained amount
- Mass times concentration gives a contained amount — five million tonnes at forty parts per million is roughly two hundred tonnes of the element. That arithmetic is the easy part, and it is also where most of the damage gets done. Contained is not recoverable. And a sample from one point cannot be extrapolated across an entire facility: a waste body is stratified by what was tipped and when. Where the sampling cannot speak for the whole body, the passport says so and the figure is marked indicative only.
- The steps, in order
- MEASURED CONCENTRATION → REPRESENTATIVE CHEMISTRY → CONTAINED INVENTORY → METALLURGICAL RECOVERY → POTENTIALLY ECONOMIC RECOVERY
- Historical process
- Three states, kept apart. A source may name the mechanism — leaching, flotation, smelting. It may only establish context: “mill tailings” says the material came out of a plant and says nothing about whether that plant floated, jigged or cyanided, and those leave completely different things behind. Or it may say nothing at all, which is the commonest case by a wide margin and is displayed as such.
- Next Best Test
- What is the smallest next piece of evidence that could change the decision? One answer, not a wish list. No chemistry → a representative multi-element assay. Chemistry from a single point → a multi-zone campaign. Carrier mineral unknown → XRD or automated mineralogy. Process unknown → recover the historical flowsheet, which is archival work and costs time rather than money. Recoverability unknown → metallurgical testwork. Quantity unknown → survey and density. GeaSpirit names the gap to close; accredited specialists close it.
- What does it cost?
- Every recommendation reads QUOTE REQUIRED. No price is shown because no supplier has quoted one, and a plausible-looking number is exactly how a screening tool turns into a liability. Real quotations can be integrated later; invented ones cannot be uninvented.
- What would change the decision?
- Each passport states what would make the asset advance and what would make it dropped. Representative chemistry confirming enrichment with a carrier mineral present would advance it; multi-zone chemistry staying at background would end it. A hypothesis that nothing could refute is not a hypothesis, and a platform that only ever produces reasons to continue is a sales document.
Negative results are results
When a hypothesis fails, what was expected, what was tested and why it was rejected are kept. Over years that record becomes something that cannot easily be bought: a systematic account of which kinds of opportunity look attractive and routinely fail, and for what reason. A failed hypothesis is evidence, not something to hide.
Prediction first, measurement later
A result is worth far more when it was written down before the measurement existed. GeaSpirit's blind validation set was sealed once and opened once, and when the underlying engine later changed, the result was retired to history rather than quietly re-run — because a benchmark you can repeat until it agrees with you is not a benchmark. The same discipline is what future asset-level predictions are built to follow: state the expected signal, the evidence behind it, and the criteria that would confirm or reject it — and only then go and measure.
What can be done from a desk, and what cannot
Remotely: global screening, data integration, reconciling a waste facility with the mine that produced it, geological and mineralogical interpretation, integrating published chemistry, assessing quantity, finding the gaps, prioritising candidates and defining the next test. That is most of the thinking, and it is why a small team can cover the world before owning a single instrument.
What cannot be done from a desk: taking a representative sample; measuring chemistry that has never been analysed; determining true recoverability without metallurgical testing; and proving a resource or reserve. Those need field geologists, accredited laboratories, mineralogical and metallurgical work, and engineering. GeaSpirit can specify and interpret that work. It cannot replace it.
Words that are not synonyms
Signal ≠ deposit
Evidence ≠ proof
Presence ≠ concentration
Contained ≠ recoverable
Recoverable ≠ economic
Estimated mass ≠ measured tonnage
Point sample ≠ facility-wide inventory
Prospectivity ≠ probability
Process context ≠ documented flowsheet
The screening results, priority rankings, candidate lists and the reasoning behind each recommendation are part of the authenticated console. This page explains what the system does; it does not publish what it concludes.