Kazakhstan holds some of Central Asia's largest copper endowments, split between Central Kazakhstan porphyry deposits like Bozshakol and Aktogay and Zhezkazgan-type sediment-hosted stratiform ore in the Chu-Sarysu basin. Decades of Soviet-era GKZ exploration data, once digitised and reprojected, let AI-driven prospectivity models rank new drill targets on already-mapped but underexplored ground.
Kazakhstan's copper endowment comes from two distinct geological settings, and knowing which one you are exploring changes the whole targeting approach. The first is the porphyry Cu-Mo belt running through Central Kazakhstan as part of the Paleozoic Central Asian Orogenic Belt. The second is sediment-hosted, stratiform copper in the Chu-Sarysu Basin, the style first defined at Zhezkazgan and often called Zhezkazgan-type in the geological literature.
The porphyry belt hosts Bozshakol (Pavlodar region, Ekibastuz district), Aktogay (near Ayagoz, in the east), Koksai, and the historic Kounrad system near Balkhash, one of the belt's earliest-worked deposits and now largely depleted. These are bulk, low-grade, high-tonnage systems: individually unremarkable copper grades, generally well under 1%, spread across ore bodies large enough to support decades of open-pit mining. They sit within the same porphyry province as Oyu Tolgoi in Mongolia, part of the broader Central Asian Orogenic Belt.
The Chu-Sarysu deposits are a different animal. Zhezkazgan-type mineralization occurs in Permian to Triassic red-bed sandstone and siltstone sequences, controlled by basin-margin redox fronts where copper sulphides precipitated out of basinal fluids moving through reduced host rock. Grades run higher than porphyry copper but continuity is far less predictable: ore shoots pinch, swell, and step between structural blocks, which is exactly the kind of geometry that rewards a dense historical drill-hole dataset over a handful of modern holes.
Both belts were mapped, sampled, and drilled extensively during the Soviet period, well before satellite positioning or digital core logging existed. That earlier work is the raw material for most of what follows on this page.
The direct answer: Soviet-era geological archives already contain decades of completed field work over Kazakhstan's copper terrain, so digitising them is a way to explore by desk before committing a rig to the ground. Regional geological survey between the 1950s and 1980s covered both the porphyry belt and the Chu-Sarysu basin with soil and stream-sediment geochemistry, ground magnetic and resistivity surveys, and thousands of exploration and appraisal drill holes, each logged with lithology, structure, and assay intervals.
That record was written up as GKZ-format protocol and reserve-estimation reports, most of which exist only as scanned paper, and some only as the original paper or microfilm, filed by deposit name or exploration-party number rather than by spatial coordinate. Positions in those reports are recorded in the Pulkovo 1942 datum, typically in local 3-degree or 6-degree Gauss-Kruger zones, not WGS-84, so nothing plots correctly in a modern GIS until it is reprojected. The practical result is that a hole drilled and logged as sub-economic in, say, 1971 is effectively invisible today unless someone locates the physical report, reads it, and re-enters the data by hand.
The scale of that backlog is not a CoreElement estimate. Kazakhstan's own national geological digitisation programme, run by the state, reported in 2026 that it had scanned more than 97% of the country's primary geological records, on the order of 250 terabytes of material, out of an archive of roughly five million items, with full digitisation targeted for the end of 2026. That figure is cited here only to show the size of the underlying archive; it describes a separate, government-run programme, not a CoreElement deployment or partnership.
Turning a shelf of scanned GKZ reports into a ranked drill target is a five-step pipeline, and skipping any one of the steps is where most legacy-data projects stall.
The archive-to-target pipeline is described in more detail on the Soviet archive digitisation page, and the underlying methodology, including how prospectivity layers are weighted and validated, is covered on the methodology page.
The direct answer: a GKZ-approved copper estimate is not a JORC or KAZRC resource until it is remapped, category by category, under a named competent person, because the two systems define confidence and economic viability differently.
The Soviet system classified deposits into categories A, B, C1, and C2 by decreasing study detail and confidence, plus a P (prognostic) series for areas with no direct drill testing. Those categories correspond only loosely to CRIRSCO-family terms: broadly, C2 and C1 map toward Inferred, B toward Indicated, and A toward Measured or Proven. The correspondence is approximate rather than a lookup table, for three reasons that matter for anyone converting a historical copper estimate:
| Soviet GKZ category | Approximate CRIRSCO/JORC/KAZRC equivalent | What requalification typically needs |
|---|---|---|
| A | Measured Resource / Proven Reserve | Dense, verifiable drill grid; modern QA/QC applied to historical assay data |
| B | Indicated Resource | Confirmed geological continuity; competent person review |
| C1 | Indicated to Inferred Resource | Re-estimation with modern block modelling; drill-spacing review |
| C2 | Inferred Resource | Wide-spaced or single-hole data; supports geological continuity only |
| P1 / P2 / P3 (prognostic) | Exploration Target or Exploration Result | No resource status under CRIRSCO codes; new drilling required to test |
First, GKZ reports were reviewed collectively by a state commission, with no individual signing personal responsibility for the number, unlike the competent-person requirement under JORC, NI 43-101, KAZRC, and the rest of the CRIRSCO family. Second, GKZ cut-off grades were set administratively and could take a long time to revise, while CRIRSCO-family codes expect a cut-off grounded in current costs and prices. Third, and most important for old copper estimates, GKZ counted essentially all identified mineralization as reserves, including material with no reasonable prospect of economic extraction, where CRIRSCO-family codes require that test before anything is called a resource at all.
Kazakhstan's own code, KAZRC, joined the CRIRSCO family in 2016, and CRIRSCO-aligned reporting became mandatory for newly issued subsurface licences from 2024. Deposits already registered under the State Commission on Mineral Reserves were not required to reconvert, so most of the copper tonnage mapped during the Soviet period still sits in GKZ format unless a company actively chooses to convert it, typically to bring in a foreign joint-venture partner, list reserves on an exchange that expects NI 43-101 or JORC-standard disclosure, or support project finance under S-K 1300. The conversion path itself, deposit by deposit, is covered on the GKZ to JORC conversion page; KAZRC's own scope and reporting requirements are covered on the KAZRC standard page.
Two concrete things: faster, cheaper first-pass targeting on ground that has already been partly explored, and a reporting path a foreign board, lender, or joint-venture partner can actually assess.
Without digitised archives, a junior working a license block in central or eastern Kazakhstan effectively chooses between paying for fresh regional geochemistry and geophysics across the whole block, or drilling comparatively blind on structural inference alone. Digitised legacy data changes that trade-off, because decades of already-completed anomaly mapping and drill intercepts can be fused with whatever new data the company collects, instead of being re-generated from zero. That shrinks the area a first field season needs to cover and raises the odds that the holes drilled first are the holes that matter.
The second benefit is less about geology and more about capital. A historical GKZ estimate converted into a KAZRC- or JORC-recognisable category is a number a TSXV, ASX, or AIM technical due-diligence team can actually evaluate against its own standards, rather than a Soviet-era classification that carries little weight outside the CIS. A sample of what that converted output looks like in practice is available on the sample reports page.
CoreElement AI, founded in 2024 by Daniel Tonkopiy (CEO and Product Architect) and Zhambyl Suraganov (Cofounder), built one of its 22 modules specifically for this problem: OCR and digitisation of scanned GKZ reports, Pulkovo 1942 to WGS-84 reprojection of the underlying coordinates, and category mapping from GKZ A/B/C1/C2/P toward KAZRC and JORC equivalents, alongside support for NI 43-101, SAMREC, PERC 2021, and S-K 1300 reporting. As of May 2026 the platform has digitised 4,859 documents, and its AI-ranked targets carry a 76% drill hit rate across the projects processed to date. The company has run two pilot deployments with large enterprise mining operators in Kazakhstan.