The research, led by Melek Ural of Fırat University together with Sedat İnal of the Mineral Research and Exploration General Directorate and Mustafa Eğri of Pamukkale University, focused on four key areas: Aşvan (Muratçık), Fatmalı, Üçağaç, and Ulupınar (Birvan). These zones sit along the contacts where the Upper Cretaceous Baskil Magmatic Suite—dominated by gabbro and diorite—intruded the Paleozoic Keban Metamorphics, a sequence of marbles, schists, and graphitic shales. Where hot magmatic fluids met carbonate country rock, they generated classic contact-metasomatic skarn systems rich in magnetite and ilmenite, the iron oxides that make these deposits economically interesting.

The technical heart of the study lies in ASTER band ratioing. The Advanced Spaceborne Thermal Emission and Reflection Radiometer captures reflected sunlight in the visible and near-infrared (VNIR) and short-wave infrared (SWIR) regions, and different minerals absorb and reflect light at diagnostic wavelengths. The team applied three ratios: B2/B1 to enhance ferric iron (Fe³⁺) minerals such as hematite and goethite, which absorb strongly around 0.52–0.60 µm but reflect more in the 0.63–0.69 µm range; B5/B4 to highlight iron silicates and hydroxyl-bearing minerals through the Fe–OH absorption near 2.2 µm; and B4/B5 to detect lateritic zones, the weathered surface caps that form when skarn ore is exposed to tropical-style chemical weathering. Statistical thresholds were derived from the histograms of each ratio image, isolating the brightest anomalous pixels that deviate from the background population.

To validate these spectral anomalies, the researchers collected four representative rock samples (MEU series) and cross-referenced them with six previously analyzed skarn samples (MS series) from earlier work in the same region. Petrographic thin sections revealed the alteration paragenesis in detail: albitization, carbonatization, and sericitization in feldspars, chloritization in biotite, and uralitization in pyroxenes, all accompanied by widespread hematitization. The primary ore assemblage is dominated by magnetite and ilmenite, with martitized magnetite—magnetite rims replaced by hematite—characteristic of endoskarn zones, while ilmenite and hematite alteration dominate the exoskarns hosted in the marbles.

X-ray diffraction analysis confirmed the mineral phases, identifying magnetite, hematite, ilmenite, and pyrite in the intrusive rocks, along with albite, quartz, diopside, andradite, grossular, tremolite, actinolite, ferro-actinolite, nontronite, vermiculite, and jarosite in the skarn assemblages. The presence of nontronite (an iron-rich smectite) and jarosite (a hydrous iron sulfate) is particularly telling: these minerals form during low-temperature hydrothermal cooling and acidic near-surface oxidation, providing direct mineralogical evidence that the Keban system experienced intense retrograde overprinting after its primary high-temperature mineralization event.

The geochemical data reveal a striking chemical gradient across the skarn system. Total iron content, expressed as FeO, rises sharply from 1–15 percent in the dioritic/gabbroic endoskarn contacts, through 14–24 percent in the exoskarn alteration zones, up to 45–52 percent in the high-grade massive skarn ore bodies. Sample MEU-004, from the Aşvan ore field, recorded 52.77 percent Fe₂O₃ with a pronounced loss on ignition of 8.99 percent and severe alkali depletion (Na₂O down to 0.11 percent, K₂O to 0.05 percent), signaling advanced hydrous alteration and leaching. Mobile trace elements such as copper (up to 145.42 ppm) and zinc (up to 185.32 ppm) are enriched, while resistant elements like cobalt (65.04–95.28 ppm) and nickel (25.08–180.32 ppm) accumulate at the surface—exactly the pattern expected when sulfide-bearing hydrothermal fluids are followed by supergene weathering that strips away silica, calcium, magnesium, and the alkalis.

The multi-stage evolution of the Keban skarn system emerges clearly from this integrated evidence. Stage one was high-temperature prograde skarn formation, in which anhydrous minerals like andradite, grossular, and diopside crystallized at temperatures estimated for comparable regional systems at 473–572 °C. Stage two was retrograde hydrothermal overprinting, when the system opened to mixing of magmatic and meteoric fluids, precipitating hydrous silicates and sulfide ores at shallower depths. Stage three was supergene lateritization, when tectonic uplift exposed the deeper skarn ore to erosion and hot, humid weathering conditions generated a goethite-dominated lateritic cap above the primary mineralization. Jarosite in the samples points to primary pyrite and chalcopyrite that underwent intense oxidation, confirming that pyritic/sulfidic processes were active at depth, not just oxide-facies magnetite.

The most striking validation came from a chronological comparison. The ASTER image used in the study was acquired on 28 September 2003, but mining operations at the two iron sites commenced in 2012 and 2016. Because the deposits were still covered by natural soil and vegetation in 2003, the ferric iron spectral anomalies were largely masked at the exact pit locations. Yet the detection of candidate anomaly pixels immediately surrounding today’s active open pits indicates that the sensor was able to capture near-surface micro-leakage signatures of alteration—faint spectral traces of buried mineralization leaking upward through the overburden. This temporal mismatch, the authors argue, is not a weakness but a demonstration: the methodology functions as a predictive tool for discovering unexposed, blind mineralization, not merely a way to map already-excavated pits.

Quantitatively, four of the ten field samples (40 percent) spatially overlapped with at least one classified ASTER band ratio anomaly. The highest overlap was obtained at the B4/B5 laterite ratio, with four samples coinciding with anomalous pixels, while the B5/B4 iron silicate ratio overlapped with one sample and the B2/B1 ferric iron ratio with none. The authors caution that these overlap ratios were not interpreted as formal classification accuracy measures or Kappa statistics, given the small, targeted sample set, but rather as quantitative indicators of spatial agreement supported by independent petrographic and mineralogical evidence. Notably, sample MEU-001, containing 10–15 percent disseminated magnetite and hematite within silicates, corresponded to a distinct laterite anomaly, whereas sample MEU-002, petrographically richer in primary magnetite, coincided directly with the ferric iron classification.

The implications extend well beyond Keban. Iron ore remains a vital raw material for the global metallurgical and mining sectors, and exploration methods are evolving toward remote detection and predictive capability. Integrating satellite spectral data with field geochemistry reduces the need for costly, time-consuming, and physically demanding conventional fieldwork while enabling focus on overlooked targets. The approach has been validated globally—from Bingham Canyon in the United States to Sarcheshmeh in Iran, and across the Tethyan Metallogenic Belt where ASTER’s SWIR and TIR bands have captured regional alteration trends tied to polymetallic deposits. For future work, the authors recommend ground-based geophysical surveys such as magnetics and resistivity, along with exploratory drilling, to establish subsurface continuity of the skarn and laterite anomalies. Analyzing garnet compositions via LA-ICP-MS would be a logical next step to refine hydrothermal fluid paths and validate the regional satellite anomalies at mineral scale. What the Keban study ultimately proves is that the ground beneath our feet keeps secrets, but the light it reflects tells stories—and sometimes, a satellite reading from two decades ago can point miners to ore they have not yet found.

Subject of Research: Earth Sciences

Article Title: ASTER-based mapping of iron skarn mineralization in Keban (Elazığ), Eastern Türkiye: Insights from mineralogical, geochemical, and spectral validation

Article References: Ural, M., İnal, S., & Eğri, M. (2026). ASTER-based mapping of iron skarn mineralization in Keban (Elazığ), Eastern Türkiye: Insights from mineralogical, geochemical, and spectral validation. Environmental Earth Sciences, 85(17), Article 433. https://doi.org/10.1007/s12665-026-13162-2

Image Credits: AI Generated

DOI: 10.1007/s12665-026-13162-2

Keywords: remote sensing, ASTER, iron skarn, mineral exploration, Keban, Türkiye, geochemistry, spectral validation, ASTER-based, mapping, iron, skarn

The core challenge the researchers faced is that SFTS measures only magnetic field components in the air. Unlike magnetotellurics or controlled-source audio magnetotellurics, where apparent resistivity can be derived directly from the ratio of orthogonal electric and magnetic fields, the airborne tipper system has no electric field measurement to lean on. The team therefore defined full-zone apparent resistivity through an implicit function relating the tipper response to subsurface resistivity. Because the tipper contains Bessel functions and altitude terms that resist simplification, no closed-form expression exists, so the algorithm iteratively solves for resistivity using a binary search. The approach exploits a key numerical property: across half-space resistivities spanning 0.1 to 10,000 ohm-meters and frequencies from 8 to 8,192 hertz, the amplitudes of the horizontal tipper components change monotonically with resistivity, which guarantees that a bisection strategy will converge reliably at every measurement point and frequency.

Depth assignment posed a second, equally thorny problem. The detection capability of SFTS extends beyond the plane-wave region, and in the near and transition zones the electromagnetic field behaves as a non-planar wave, so the classical skin depth formula borrowed from plane-wave theory cannot be applied. The researchers instead adopted the concept of effective skin depth, defined as the depth at which the field amplitude from the grounded source decays to 1/e, roughly 37 percent, of its surface value. Because the vertical magnetic field component penetrates deepest among the three measured components, it was used to compute the apparent depth. Numerical experiments over offsets from 1 to 15,000 meters showed that effective skin depth first increases and then decreases with offset distance, and that once the receiver enters the plane-wave region the value reduces to the familiar frequency-dependent skin depth.

Computing effective skin depth point by point would be far too slow for field-scale imaging, so the team distilled the physics into an explicit formula. By defining an induction number as the ratio of offset to skin depth, they showed that the normalized effective skin depth traces a nearly universal curve regardless of half-space resistivity. Fitting that curve with a rational function yielded a compact expression linking depth to offset and frequency, with fitted coefficients that reproduce the theoretical values to within 5 percent relative error. That accuracy, achieved at negligible computational cost, is what makes full-zone apparent resistivity-depth imaging of actual survey data feasible in practice.

To test the method, the researchers first turned to one-dimensional layered models representing common geological scenarios in mineral districts. In a two-layer model with a 200-meter-thick conductive cover of 100 ohm-meters overlying resistive basement, the imaging curves faithfully reproduced the upper-layer resistivity and detected the electrical interface at the correct depth, though electromagnetic reflection at the boundary produced artificial spikes. When the lower layer was conductive, simulating graphitic zones, clay alteration halos, or massive sulfide orebodies, the curves converged toward the true resistivity with depth. When the lower layer was resistive, representing quartz veins, unaltered granitic intrusions, or porphyry copper systems, the curves rose gradually but underestimated the true values, a reminder that electromagnetic methods are inherently less sensitive to highly resistive strata. Three-layer tests reinforced the pattern: the imaging resolved concave and convex resistivity trends qualitatively and located thin layers, but resolution weakened for resistive thin beds.

The real test came from three-dimensional synthetic models computed with a finite volume method on a staggered grid, using a secondary-field formulation solved iteratively with a quasi-minimal residual scheme. The first target was a single low-resistivity body, 2 kilometers square, buried with its top at 100 meters depth and 300 meters thick, with resistivity of 1 ohm-meter against a 100 ohm-meter background. That two-order-of-magnitude contrast mirrors real economic sulfide deposits such as those in the Huangshan-Jingerquan belt of Xinjiang, China. Cross-sectional imaging at 260 meters depth clearly delineated the conductive anomaly at its true central position, while slices at 20 and 500 meters captured the top and bottom electrical signatures. Longitudinal sections traced the lateral boundaries of the body and its vertical extent from 100 to 400 meters. One caveat emerged: distortions appeared on the side of the anomaly away from the source, a shadow effect inherent to single-source configurations.

A second model replaced the conductor with a 1,000 ohm-meter body representing porphyry copper, skarn, or quartz-vein-hosted gold mineralization. The imaging again located the anomaly and its boundaries, but the resistive response was noticeably weaker, with the apparent high-resistivity zone shifted away from the source. The most demanding scenario was a complex model mimicking a porphyry copper system: a high-resistivity core of 10,000 ohm-meters, corresponding to the potassic alteration zone and mineralized porphyry stock, embedded within a 3-kilometer-wide low-resistivity halo of 1 ohm-meters representing phyllic or argillic alteration envelopes. The algorithm resolved both features simultaneously, and remarkably, the electrical interface between the high- and low-resistivity anomalies was rendered more sharply than the boundary between the low-resistivity halo and the surrounding rock.

Robustness against field noise was assessed by adding 8 percent random noise to the synthetic tipper responses of the complex model. The noisy images showed local fluctuations and blurred boundaries, particularly near the interfaces between contrasting bodies, yet the central high-resistivity core remained identifiable at 260 meters depth and the overall high-low resistivity distribution was preserved at all tested levels. This preliminary noise test suggests the imaging pipeline can tolerate realistic measurement uncertainty, an essential property before any deployment on airborne platforms where wind, instrument attitude, and electromagnetic interference conspire against clean data.

The authors are careful to position the technique correctly. The fast imaging results are reliable for identifying lateral variations and anomalous boundaries but less accurate for determining true vertical depths and resistivity values, and the method performs best on conductive or strongly contrasting targets. It should therefore be regarded as a rapid qualitative screening tool rather than a replacement for full quantitative inversion. Within an exploration campaign, its role is to process raw tipper data on the fly, flag promising anomalous zones, and prioritize targets for field verification, geologically constrained interpretation, or expensive three-dimensional inversion. It also serves quality control, giving field crews an intuitive picture of subsurface electrical structure while instruments are still deployed.

Future work will tackle the known limitations head-on. The team plans systematic analysis of how flight altitude, attitude, and orientation errors degrade imaging accuracy, refinement of the apparent-depth formulation to reduce bias for resistive targets, and use of the fast images as starting models for full three-dimensional inversion, which could dramatically cut convergence time. If field trials validate the synthetic results, semi-airborne frequency tipper sounding could become a standard first-pass tool in the hunt for deeply buried sulfide and porphyry deposits, turning what was once a data-processing bottleneck into a competitive advantage for explorers working in the world’s most inaccessible terrain.

Subject of Research: Fast apparent resistivity-depth imaging for the semi-airborne frequency tipper sounding method in mineral exploration

Article Title: Fast and high-resolution imaging of semi-airborne frequency tipper sounding method for mineral exploration

Article References: Yin, M., Deng, J., Chen, H., Feng, M., Yu, H., Yuan, C., & Huang, J. (2026). Fast and high-resolution imaging of semi-airborne frequency tipper sounding method for mineral exploration. Frontiers in Earth Science, 14, Article 1970019. https://doi.org/10.3389/feart.2026.1970019

Image Credits: AI Generated

DOI: 10.3389/feart.2026.1970019

Keywords: semi-airborne electromagnetics, tipper sounding, mineral exploration, apparent resistivity, fast imaging, effective skin depth, binary search algorithm, massive sulfide deposits, porphyry copper systems, electromagnetic sounding, geophysics, resistivity-depth imaging

Now a team from the Oulu Mining School at the University of Oulu and the Geological Survey of Finland has developed and tested a methodological concept that could change how exploration is done in glaciated terrain. In a study published in Frontiers in Geochemistry, Pertti Sarala and Marja Lehtonen present an integrated workflow combining field-based heavy mineral concentration, portable X-ray diffraction (pXRD) and X-ray fluorescence (pXRF) analyzers, and automated laboratory mineral identification using field emission scanning electron microscopy with energy-dispersive spectroscopy (FE-SEM-EDS). The concept, developed during the European Regional Development Fund-funded Indika project between 2016 and 2019, was evaluated across four study areas in northern and central Finland, and the results show that it can accelerate exploration, cut costs, and reliably identify the indicator minerals that betray the presence of critical metal deposits hidden beneath the ice-carved landscape.

The key insight behind the work is that indicator minerals, minerals that are more abundant and more widely distributed in bedrock than the ore minerals themselves, can serve as practical proxies for mineralization. Heavy mineral analysis has long been a mainstay of exploration for gold, diamonds, and magmatic nickel-copper-platinum group element deposits, typically relying on large samples of 10 to 100 kilograms from which the heaviest grains, those with specific gravity above 3.3 grams per cubic centimeter, are separated by gravity-based concentration. But the method has a blind spot when it comes to critical metals. Many of the indicator minerals characteristic of rare earth element deposits, such as monazite, xenotime, pyrochlore, and columbite, are difficult to identify visually under a microscope, and some have densities lower than the minerals traditionally recovered in heavy mineral concentrates, meaning they slip through conventional enrichment processes entirely. Until now, no well-established method existed for their efficient separation from sediment samples.

To close that gap, the researchers systematically optimized sample handling and enrichment techniques. Till samples of roughly 12 liters, about 20 to 25 kilograms each, were collected in triplicate from hand-dug and tractor-excavated test pits, with parallel samples reserved for field testing, laboratory analysis, and reference. In the laboratory, samples were wet-sieved under a 1-millimeter size fraction and processed on a shaking table, chosen because an experienced operator can control the density of the resulting concentrate and the method is gentler on fragile mineral grains than a Knelson concentrator. Magnetite was then removed by weak and strong magnetic separation, and the heaviest fractions were isolated by heavy liquid separation using undiluted methylene iodide at 3.3 grams per cubic centimeter, which proved more effective than the lithium heteropolytungstate solution, which suffered from high sample loss and imprecise separation. The results demonstrated that indicator mineral separation can be significantly optimized through tailored processing, with the 63 to 150 micrometer heavy fraction providing the most reliable indicator mineral data.

The field-based component of the workflow proved equally important. At each sampling site, the researchers compared two concentrating techniques applied to subsamples of the same material: a spiral concentrator, also known as a Gold hound concentrator, and a Knelson concentrator. Spiral concentrates, weighing only tens of grams, were usually suitable for direct microscopic examination, while Knelson concentrates, weighing hundreds of grams, required further post-processing such as micro-panning or heavy liquid separation. Under field conditions, micro-panning emerged as the most practical and cost-effective method for isolating the heaviest mineral fraction, with magnetite typically removed from the concentrates to reduce the volume that must be examined. This parallel application of field and laboratory concentration methods allowed the team to evaluate which approach works best for different sample sizes, grain-size fractions, and specific gravity classes.

The analytical heart of the new concept lies in the portable instruments that bring the laboratory into the field. The researchers used an Olympus Terra portable XRD analyzer and an Olympus Innov-X Delta portable XRF analyzer to analyze concentrated till samples directly at sampling sites. The pXRF instrument, equipped with a 4-watt X-ray tube and a high-resolution silicon PIN diode detector, determined more than 40 elements in GeoChem mode with each measurement taking just 40 seconds. The pXRD analyzer, though producing diffraction patterns of lower quality than laboratory instruments due to its faster measurement speed and narrower angular range of 5 to 55 degrees, reliably identified the most common indicator minerals, including zircon, monazite, and xenotime, directly in the field. Measurement times ranged from approximately 15 minutes to more than an hour depending on the quality of the diffraction pattern obtained, with the clearest results achieved when peaks were well resolved and background noise was low.

Validation of the field-based results came from the automated FE-SEM-EDS analyses performed at the Geological Survey of Finland in Espoo. Using a JEOL JSM 7100F field emission scanning electron microscope coupled to an Oxford Instruments X-Max 80 square millimeter EDS, the researchers analyzed between 10,000 and 20,000 mineral grains per preparation in automated runs, with EDS spectra generated from the center of the longest grain diameter for grains with a minimum size of 7 micrometers equivalent circular diameter. The method enabled accurate imaging, analysis, and quantification of the mineral grains in till samples, and revealed significant observations relevant to exploration, such as the identification of inclusions within indicator mineral grains and correlations between indicator mineral concentrations and associated mineralogy that can be used to assess the type and characteristics of the source rock. Variations in grain size and morphology may even indicate the length of glacial transport distance.

The case studies in northern Finland confirmed the robustness of the integrated approach across different geological settings. At the Mäkärä gold-rare earth element prospect in the Tana Belt, one of the most prospective regions for rare earths and gold in northern Europe, the indicator mineralogy demonstrated a highly enriched rare earth-bearing mineral assemblage dominated by monazite, columbite, and xenotime, supporting earlier assessments of the area’s high rare earth potential. At Kyörtesselkä near the Sokli carbonatite massif, a funnel-shaped multistage pluton enriched in niobium, tantalum, zirconium, rare earths, and uranium, the concentrates yielded columbite, monazite, pyrochlore, rhabdophane, ancylite, and xenotime, confirming the recognized critical raw material potential of the region. At the tailings of the former Rautuvaara iron-copper mine, which operated from 1962 to 1988, the analyses identified tungsten-bearing rutile with tungsten contents between 1.5 and 5 weight percent, along with monazite, cobaltite, and small amounts of gold, demonstrating that old mine waste can be re-evaluated as a potential source of critical minerals within a circular economy framework.

The comparison between portable and laboratory XRD analyses revealed both the power and the limitations of the field instruments. While pXRD identified the same major minerals as laboratory XRD in most cases, the reported abundances varied significantly not only between portable and laboratory analyses but also between different laboratories, making precise quantitative comparison difficult. Some minerals, such as biotite, chlorite, and calcite, were almost entirely absent from pXRD results, either because their diagnostic diffraction peaks lie outside the narrow angular range of the portable analyzer or because of the amorphous or metamictic state of the mineral. Conversely, pXRD could identify minerals that FE-SEM analysis missed, such as minerals with identical elemental compositions but different crystal structures that produce distinct diffraction patterns. The researchers concluded that portable analyzers are most effective when used as part of a multi-method exploration strategy rather than as standalone tools, with laboratory validation providing the necessary confirmation for critical raw material exploration.

The practical implications of the study are substantial. By enabling rapid screening of samples in the field, the portable analyzers allow exploration programs to prioritize only the most promising samples for costly laboratory analyses, resulting in significant cost savings and faster decision-making during exploration campaigns. The documented outcomes from the piloting at the Vuolijoki site, where a one-day sampling campaign traced the potential source of surficial boulders containing elevated rare earth concentrations, support industrial use and future exploration projects. As the European Union and Finland push to reduce dependence on imported critical raw materials, the ability to explore efficiently under meters of glacial cover could prove decisive in discovering the domestic deposits that high-technology industries need. The new concept has proven effective for discovering new sources of critical minerals, accelerating exploration, and reducing costs, offering a template that companies and research projects across the glaciated terrain of the Northern Hemisphere can now apply.

Subject of Research: Geochemistry

Article Title: On-site geochemical and indicator mineral analytical techniques in critical raw-metal exploration in the glaciated terrain

Article References: Sarala, P., & Lehtonen, M. (2026). On-site geochemical and indicator mineral analytical techniques in critical raw-metal exploration in the glaciated terrain. Frontiers in Geochemistry, 4, Article 1866020. https://doi.org/10.3389/fgeoc.2026.1866020

Image Credits: AI Generated

DOI: 10.3389/fgeoc.2026.1866020

Keywords: critical raw materials, indicator minerals, portable XRD, portable XRF, glaciated terrain, heavy mineral analysis, FE-SEM-EDS, rare earth elements, mineral exploration, Finland, On-site, geochemical

The story begins some 310 million years ago, when the late- to post-tectonic Variscan granites of the Castelo Branco Massif crystallized deep in the crust. The massif, which outcrops over more than 390 square kilometers in the Central Iberian Zone, is composed of several concentric S-type granitic facies, ranging from fine-grained muscovite-biotite granite in the core to porphyritic monzonitic granites toward the middle. Crucially, geochemical studies have shown that these middle facies are enriched in rare earth elements relative to the core and border granites. Within these rocks, tiny accessory minerals—monazite, xenotime, apatite, and zircon—host the bulk of the rare earth elements, thorium, and uranium, while ilmenite, the most abundant opaque mineral, carries titanium. Over millions of years, erosion dismantled these granites, and rivers sorted and concentrated the dense, weathering-resistant heavy minerals into alluvial deposits, the same natural process that has formed economically valuable placer deposits around the world.

The research team, led by Rute Salgueiro, collected twelve alluvial samples from granitic terrains near the eastern edge of the massif, deliberately targeting areas around late northeast-southwest tectonic faults where earlier geochemical surveys had identified anomalous rare earth, thorium, and uranium concentrations in stream sediments. The samples were sieved to less than three millimeters, panned in the field, and then treated in the laboratory with heavy liquids of density 2.89 grams per cubic centimeter to isolate the heavy mineral fraction. Magnetic separation then split each concentrate into two fractions: a magnetic and paramagnetic fraction dominated by minerals such as ilmenite, tourmaline, monazite, and biotite, and a diamagnetic non-magnetic fraction containing andalusite, apatite, anatase, zircon, rutile, and other light-colored minerals.

What the researchers found under the binocular microscope was striking. The magnetic fraction accounted for roughly 85 percent of the total heavy mineral volume, and within it, ilmenite reigned supreme with an average abundance of just over 50 percent of the entire sample. Titanium minerals as a group—ilmenite, rutile, anatase, brookite, sphene, and leucoxene—made up an average of 54.28 percent of the sample volume. The rare earth element minerals, though accessory, summed to about 12 percent, with monazite the most abundant at 4.97 percent, followed by apatite at 4.14 percent, zircon at 2.58 percent, and xenotime at 0.53 percent. Monazite and xenotime appeared as fine, hyaline, mostly subhedral grains with rounded shapes, their light yellow and green colors betraying their identity, while zircon displayed a range of crystal habits from colorless hyaline prisms to semi-translucent orange-yellow grains studded with dark red inclusions.

The chemical analysis, performed with a portable X-ray fluorescence spectrometer equipped with a rhodium tube and silicon drift detector, confirmed and quantified what the mineralogy suggested. Iron reached up to 31.09 percent and titanium up to 28.88 percent in the concentrates, reflecting the dominance of ilmenite. The non-magnetic fraction, dominated by zircon, showed astonishing zirconium contents of up to 207,018 milligrams per kilogram. Most importantly for the critical raw materials debate, the magnetic fraction yielded light rare earth element sums—cerium, lanthanum, neodymium, and praseodymium combined—reaching 4,557 milligrams per kilogram, alongside thorium contents of up to 1,969 milligrams per kilogram and uranium up to 244 milligrams per kilogram. The non-magnetic fraction, containing apatite and zircon, paradoxically hosted even higher uranium contents, reaching 448 milligrams per kilogram.

These numbers are not merely high; they are anomalous in a geologically meaningful way. Compared with the average composition of the granitic source rocks, the alluvial heavy mineral concentrates show enrichments of an order of magnitude or more for most elements, a result of natural sorting that concentrates dense, resistant grains in river sediments, further enhanced by laboratory separation. Compared with the North American Shale Composite, a standard geochemical reference, the samples are enriched in titanium, vanadium, yttrium, niobium, antimony, lanthanum, cerium, tantalum, tungsten, lead, thorium, and uranium by factors of ten or more, with zirconium in the non-magnetic fraction reaching a staggering thousand-fold enrichment. The light rare earth contents even exceed those of the anomalous stream sediments identified in earlier surveys, confirming that detrital monazite is the principal carrier of the light rare earth signal in the region.

The geochemical fingerprint also tells a clear story of provenance. Parallel elemental profiles between the alluvial concentrates and the parent granites—for example, elevated chromium, vanadium, zirconium, rubidium, cobalt, cerium, lanthanum, and titanium in both—point to a direct genetic link between the sediments and the Castelo Branco granitic rocks. The mineral assemblage incorporates the main heavy minerals identified in petrographic studies of the massif, including ilmenite, tourmaline, monazite, zircon, apatite, andalusite, and sillimanite. Interestingly, some minerals found in the alluvial samples, such as xenotime, garnet, brookite, anatase, and cinnabar, had not previously been recorded in the granitic rocks, likely because their low abundance in bedrock escaped detection at the scale of conventional petrography. The researchers also noted that biotite, abundant in the source granites, was underrepresented in the concentrates, probably because its lower density allowed grains to float during heavy liquid separation and its larger grain size was partly rejected during sieving.

Beyond the headline minerals, the study documented a suite of elements with industrial applicability that could add future value to any exploitation. Niobium reached up to 1,339.5 milligrams per kilogram and tantalum up to 270.75 milligrams per kilogram, hosted in titanium oxide polymorphs, ilmenite, biotite, and possibly cassiterite. Tin contents in the non-magnetic fraction climbed to 5,122 milligrams per kilogram in one sample, hinting at cassiterite grains derived from the tin-tungsten mineralized quartz veins that cut the granite along late Variscan faults. Scarce scheelite, identified under ultraviolet light, accounted for detectable tungsten, while traces of cinnabar explained the mercury signal. These accessory phases mean that any future mining of the titanium and rare earth minerals could recover additional commodities as by-products, improving the economic case.

Perhaps the most compelling historical echo in the study is the region’s own mining past. Between 1980 and 1988, the Lardosa alluvial placer deposits on the Castelo Branco Massif were commercially exploited for cassiterite and ilmenite, a direct precedent that titanium-rich placers sourced from these granites can form and be mined. The new data indicate that the same natural concentration machinery that once produced economic tin and titanium placers is also enriching monazite and ilmenite across a potentially wider area. Worldwide, placer deposits have historically supplied rare earth elements through monazite and, more rarely, xenotime, typically recovered as coproducts of ilmenite extraction—a model that fits the Castelo Branco situation remarkably well, given ilmenite’s overwhelming abundance in these sediments.

The authors are careful to note that the potential for placer-type deposit formation depends on mineral grades, quality, and deposit volumes being sufficient for economic extraction, questions that require follow-up investigation. Nevertheless, the study demonstrates that two simple, rapid, and relatively inexpensive methodologies—semiquantitative binocular microscopy and portable X-ray fluorescence—can efficiently characterize heavy mineral assemblages and their geochemical fingerprints, offering a practical exploration tool for critical raw materials. As the European Union’s Raw Materials Act pushes for diversified and secure supply chains to meet its 2030 climate and digital targets, the unassuming river sands of Vale da Silveira stand as a reminder that the raw materials of the future may lie not in exotic remote deposits, but in the patient, million-year work of water and weathering acting on ordinary granite, quietly concentrating the elements of the green transition one grain at a time.

Subject of Research: Rare earth element and critical raw mineral characterization of alluvial heavy mineral deposits derived from the Castelo Branco granitic massif in central Portugal

Article Title: Insights into rare earth elements and other critical raw materials from Castelo Branco massif alluvial deposits (Portugal)

Article References: Salgueiro, R., Silva, T. P., Martín-Méndez, I., de Oliveira, D., Batista, M. J., & Inverno, C. (2026). Insights into rare earth elements and other critical raw materials from Castelo Branco massif alluvial deposits (Portugal). Frontiers in Geochemistry, 4, Article 1766699. https://doi.org/10.3389/fgeoc.2026.1766699

Image Credits: AI Generated

DOI: 10.3389/fgeoc.2026.1766699

Keywords: rare earth elements, critical raw materials, monazite, ilmenite, alluvial deposits, placer deposits, Castelo Branco Massif, Portugal, heavy minerals, portable X-ray fluorescence, granite geochemistry, mineral exploration

The research, published in Discover Geoscience by Dionisio Uendro Carlos, César Augusto Moreira, and Guilherme Libardi Maestrelo, introduces a moving-window ordinary kriging (MW-OK) algorithm designed specifically for airborne and ground radiometric data. Conventional interpolators such as inverse distance weighting and minimum curvature are fast and widely used, but they share a fundamental weakness: they do not explicitly account for the local spatial structure of the data. In practice, that means they can oversmooth short-wavelength variability, blurring exactly the sharp radiometric gradients that mark boundaries between rock units or zones of hydrothermal alteration.

Kriging, by contrast, is a geostatistical method built on a statistical model of how a property varies in space. Because radioactive decay is inherently a stochastic process, the authors argue, an interpolator that respects this randomness is desirable. Yet standard kriging typically relies on a single global variogram, the mathematical function describing spatial correlation, assumed to hold across the entire survey area. Radiometric variables rarely obey that assumption at regional scale. Lithological boundaries, weathering domains, and survey-related effects all conspire to make the spatial structure change from place to place, so a global model can over-smooth local features or produce biased estimates where the structure shifts.

MW-OK sidesteps this problem by abandoning the global model altogether. For every prediction node on the output grid, the algorithm defines a circular window of investigation, in this case with a radius of 750 meters, roughly 1.5 times the 500-meter flight-line spacing, so that each window intersects two adjacent flight lines. Within that window, the method assumes second-order stationarity holds only approximately and locally. An empirical semivariogram is computed from all unique pairs of samples in the neighborhood, binned into eight lag classes, with any bin containing fewer than three valid pairs rejected. An exponential model is then fitted to each local semivariogram by bounded non-linear least squares, yielding a nugget effect, partial sill, and range parameter tailored to that specific patch of ground.

The computational scale is striking. The study area, a 40 by 40 kilometer subset of the Sul-Riograndense Shield Aerogeophysical Project flown by the Geological Survey of Brazil in 2010, contains 50,374 measurement points. Because the algorithm estimates a local variogram for each measurement point, it effectively generates 50,374 variograms. Neighbor retrieval is accelerated with a k-dimensional tree using ball queries, and safeguards keep the local kriging systems well conditioned: a minimum of eight neighbors, a maximum of thirty, removal of duplicate coordinates to prevent singular matrices, and a tiny ridge term added to the kriging matrix diagonal for numerical robustness. If a non-linear variogram fit fails, the workflow falls back on physically sensible defaults derived from the local data variance and median nearest-neighbor spacing.

The fitted local variograms themselves carry geological information. For potassium, the nugget effect was essentially zero at the scale of the data support, meaning microscale variability and measurement noise are minor compared with the spatially structured component, and correlation decayed over a practical range of about 1.3 kilometers. Equivalent uranium showed an even longer continuity, around 1.7 kilometers, consistent with smoother spatial behavior, while equivalent thorium displayed a larger partial sill, indicating higher structured variance, with a moderate range near 1.5 kilometers. These parameters confirm that, within each window, the radiometric variability is predominantly spatially structured rather than random noise.

When the researchers applied MW-OK to the survey data, the resulting potassium, uranium, and thorium maps reproduced the broad patterns that geologists expect. Potassium enrichment above 4 percent traced the São Sepé Granite in the north, elevated values of roughly 4 percent marked the Ramada Granite in the southwest, and low concentrations coincided with the metatuff-dominated Bossoroca Complex and the sandstones of the Maricá Group. Thorium highs of about 21 parts per million again outlined the São Sepé Granite, with additional anomalies over the Cerro da Cria Granite and nearby rhyolites. But the kriged surfaces went further than the conventional minimum-curvature grids: they better represented local gradient variations near lithological contacts and revealed internal heterogeneity within the felsic bodies that the smoother deterministic algorithm muted. Notably, three east-west linear artifacts aligned with the survey tie lines, visible in the minimum-curvature uranium map, were suppressed in the kriged surface.

A key advantage of kriging is that it also delivers an estimate of its own uncertainty. The kriging variance maps for all three radioelements bore the clear imprint of the acquisition geometry: uncertainty was minimized along and near the north-south flight lines and increased in the gaps between them, telling interpreters exactly where the estimates are most reliable. To quantify how closely MW-OK matched the industry-standard approach, the team performed pixel-wise comparisons with the minimum-curvature grids. The agreement was remarkably strong, with coefficients of determination of 0.9938 for potassium, 0.9727 for equivalent uranium, and 0.9946 for equivalent thorium, and residual histograms tightly centered near zero. Ordinary least-squares fits revealed a subtle but systematic amplitude scaling, with slopes slightly below unity, suggesting MW-OK modestly attenuates the highest values while remaining close to the identity overall. The authors are careful to frame this as evidence of methodological consistency rather than broad superiority: the two methods agree at the domain scale, and their differences emerge primarily at local scales.

Beyond the three radioelement grids, the workflow generates the interpretive products that exploration geologists actually use. It computes standard radiometric ratios (K/eTh, K/eU, eU/eTh) and the F-parameter, a widely used proxy for hydrothermal alteration that relates potassium abundance to the uranium-to-thorium ratio. It also produces ternary radioelement maps in three complementary forms: the classical K-eU-eTh display, normalized ternaries, and compositional-data transformations using additive, centered, and isometric log-ratios that respect the closure constraint and reduce spurious correlation when treating the three elements as parts of a composition. In the study area, a historically significant gold district in southern Brazil where mineralization is hydrothermal and structurally controlled in quartz veins hosted by schists and granites, these products delineated the main lithological contacts and showed spatial correspondence with known gold-mineralized zones and areas of gold enrichment identified by stream-sediment prospecting.

Perhaps most importantly for the wider community, the entire workflow is open source and exports standard deliverables, including GXF grids, GeoTIFF rasters, KMZ overlays, and PNG figures, with proper spatial metadata, making it directly interoperable with both open-source tools such as Python, QGIS, and Google Earth and commercial platforms like Oasis Montaj, Intrepid Geophysics, and ArcGIS. The authors acknowledge the method’s limitations: effective spatial resolution remains constrained by flight-line spacing and sampling interval, computational cost grows with finer grids and larger neighborhoods, and sparsely sampled sectors can yield under-populated windows with unstable variograms, which the workflow mitigates through minimum-neighbor thresholds and k-nearest-neighbor fallbacks. Looking ahead, they plan to incorporate co-regionalized cokriging constrained by lithology and structure, and deep-kriging approaches, within the same moving circular-window framework. For now, MW-OK stands as a robust, locally adaptive alternative that offers incremental rather than transformative gains over deterministic gridding, but gains that could make the difference between a blurred contact and a clearly resolved exploration target.

Subject of Research: A locally adaptive geostatistical interpolation method for processing airborne and ground gamma-ray spectrometric data

Article Title: A moving-window ordinary kriging approach for airborne and ground gamma-ray spectrometric data processing

Article References: Carlos, D. U., Moreira, C. A., & Maestrelo, G. L. (2026). A moving-window ordinary kriging approach for airborne and ground gamma-ray spectrometric data processing. Discover Geoscience, 4(1), Article 289. https://doi.org/10.1007/s44288-026-00674-4

Image Credits: AI Generated

DOI: 10.1007/s44288-026-00674-4

Keywords: gamma-ray spectrometry, kriging, geostatistics, radiometric mapping, mineral exploration, semivariogram, interpolation, gold prospecting, geological mapping, Brazil, open-source software, compositional data

A new study published in Discover Geoscience by Daniela Kuranaka, César Augusto Moreira and colleagues at São Paulo State University, the Federal University of Pampa and the University of the Republic has now taken up that challenge with an integrated toolkit that blends old-fashioned field geology with drone photogrammetry, ground magnetometry and gamma-ray spectrometry. Their results point to a specific culprit: a shear zone slicing through the Cerro da Cria Granite, where hydrothermal fluids appear to have altered the rock, destroyed its magnetite and left behind a potassium-rich fingerprint that matches the signature of structurally controlled orogenic gold systems worldwide.

The geological stage for this detective story is the South Brazilian Shield, a roughly 50,000-square-kilometre expanse of Precambrian crust that records more than two billion years of Earth history. Its present architecture was largely forged during the Brasiliano Orogeny, a protracted episode of mountain building between about 900 and 535 million years ago driven by the collision between the Kalahari and Rio de La Plata cratons. Within the Dom Feliciano Belt that resulted from this collision, the São Gabriel Terrane preserves the remains of Neoproterozoic intra-oceanic magmatic arcs, with zircon ages clustered between roughly 880 and 720 million years. Later, as the orogen collapsed, extensional tectonics opened the Camaquã Basin and unleashed felsic volcanism of the Acampamento Velho Formation, dated between 580 and 570 million years ago, while pre-existing structures were reactivated deep in the crust.

Three main rock units crop out at Cerro da Cria, and each tells part of the story. The Vacacaí Metamorphic Sequence comprises orange phyllites and metavolcanic rocks metamorphosed under low- to medium-grade conditions, relics of the ancient arc and back-arc environments. The Acampamento Velho Formation contributes brownish to reddish rhyolites with small quartz phenocrysts, products of the late post-collisional volcanism. Cutting discordantly across both is the Cerro da Cria Granite, a reddish, equigranular body of quartz, feldspar and biotite emplaced during post-collisional magmatism. Crucially, the whole terrane is threaded by regional northeast-southwest shear zones developed under dextral transpression, including the Palma–Vila Nova do Sul Shear Zone, which governed the elongation of the metavolcanic sequences and the emplacement of the granite itself. In such settings, these zones of weakness are exactly where mineralizing fluids tend to travel.

To test whether the stream-sediment gold could be traced back to a primary source, the team designed a campaign that covered approximately 70 hectares of the basin in just five days of fieldwork. A DJI Mavic 3T drone flew two missions at 80 metres altitude and 7.5 metres per second, capturing imagery that was processed in Agisoft Metashape into a high-resolution orthophoto and digital elevation model referenced to the SIRGAS 2000 geodetic system. On the ground, the researchers established a georeferenced grid with 25-metre spacing using differential GPS accurate to roughly half a metre, yielding 837 measurement stations. At each station they simultaneously recorded gamma-ray spectrometry with an RS-332 instrument equipped with a bismuth germanate detector, and total-field magnetic measurements with a GSM-19 proton precession magnetometer. A base station logged the Earth’s magnetic field every two minutes so that diurnal variations could be stripped from the rover data, isolating the signal of the subsurface.

The gamma-ray spectrometry exploits a simple physical principle: potassium-40, and the decay chains of uranium-238 and thorium-232, emit gamma photons of characteristic energies that scintillation crystals convert into measurable electrical pulses. The resulting maps of the three radioelements proved remarkably diagnostic. Potassium concentrations ranged from 0.00 to 3.80 percent, with the strongest anomalies in the central-western sector reflecting the granitic body itself, and a secondary enrichment zone of 0.97 to 1.51 percent in the northern part of the area interpreted as the influence of the shear zone. Thorium, spanning 1.17 to 10.90 eppm, broadly mirrored the potassium pattern, while uranium showed a more irregular, patchy distribution consistent with remobilization along microfractures and weathering profiles. The potassium-poor mafic metavolcanic units, by contrast, stayed below one percent, confirming that the radiometric contrast cleanly discriminates the main lithologies.

The magnetic data added a second, complementary layer of evidence. Total magnetic intensity across the survey area varied from 22,155 to 22,686 nanotesla, a 531-nanotesla amplitude, with the highest values in the east and southeast over the granite and lower values toward the northwest where the metasedimentary rocks of the Vacacaí Sequence begin. Mathematical processing, including reduction to the IGRF reference field and calculation of the Analytic Signal Amplitude and vertical derivative, sharpened the picture. The ASA, which ranges from 0.04 to 40.68 nanotesla per metre, highlighted strong magnetic contrasts in the northwestern and southeastern portions of the granite, while the vertical derivative, spanning -2.41 to 2.13 nanotesla per metre, revealed short-wavelength lineaments predominantly oriented east-west. These lineaments segment the granite and correspond to brittle-ductile fracture zones, some of which even express themselves in the topography captured by the drone.

When the datasets were overlaid, the story snapped into focus. In the northeastern sector of the basin, potassium enrichment coincides with structural features highlighted by the analytic signal, and the combination of radiometric anomalies with comparatively reduced magnetization is the classic signature of potassic hydrothermal alteration: fluids percolating along fractures and shear zones chemically transform and partially destroy magnetite, lowering the rock’s magnetic response while flooding it with potassium. The team interprets the increased permeability along these structures as the engine that drove potassium-rich hydrothermal circulation, accompanied by the concentration of oxides and sulfides. Field structural measurements reinforced the interpretation: 84 foliation measurements show a dominant northeast-southwest fabric produced by ductile deformation during the Brasiliano cycle, while 37 joint measurements cluster into four sets oriented northwest-southeast, east-west, north-south and northeast-southwest, recording late brittle reactivation. At one outcrop, a fault plane in graphite-talc schist with strongly stretched minerals defines the Cerro da Cria Fault, a sinistral strike-slip shear zone trending east-northeast to west-southwest that the authors identify as a principal control on fluid circulation and gold distribution.

This geophysical and structural fingerprint aligns closely with the metallogenetic model of orogenic gold systems, in which gold precipitates from hydrothermal fluids channeled through crustal shear zones during transpressional deformation. In the Southern Brazilian Shield, such mineralization is typically hosted in quartz veins and alteration zones within metavolcanic, metasedimentary and granitic rocks, commonly associated with pyrite and arsenopyrite. The spatial correspondence between the radiometric anomalies, the magnetic response and the mapped shear zone led the researchers to conclude that the Cerro da Cria shear zone, with potential regional continuity along the Palma shear system, is the most likely primary source of the gold now scattered through the basin’s stream sediments, having been eroded from higher ground and transported downslope into the drainage network. Notably, the data offered no direct evidence that the granite itself is the gold source; rather, it served as the structural host that the fluids exploited.

Beyond the specific discovery, the study makes a persuasive methodological case. Semi-regional ground magnetometry and gamma-ray spectrometry, combined with drone-based photogrammetry and structural mapping, delivered detailed coverage of 70 hectares in five days, demonstrating a rapid, versatile and high-resolution alternative to widely spaced airborne surveys that can miss small exploration targets. The approach converts a regional geochemical anomaly into a concrete, prioritized drill-ready target, and the authors recommend trenching orthogonal to the identified structures to obtain larger samples for grade estimation, with induced polarization and electrical resistivity tomography suggested for concealed targets. As global gold consumption reached a record 4,974 tonnes in 2024 amid sustained central bank purchases, techniques that can cheaply and quickly narrow the search in structurally complex shields are likely to become essential tools, and the quiet hills of Cerro da Cria may prove to be an early showcase of how modern integrated exploration finds what centuries of prospecting overlooked.

Subject of Research: Integrated geophysical and structural modeling to locate the primary source of a gold geochemical anomaly in the Cerro da Cria drainage basin, southern Brazil

Article Title: Geophysical modeling in a drainage basin with a gold geochemical anomaly, Cerro da Cria Region, Vila Nova do Sul, Rio Grande do Sul (Brazil)

Article References: Kuranaka, D., Moreira, C. A., Barros, M. F. S., Carlos, D. U., de Oliveira, J. P. P., Ilha, L. M., Kumaira, S., & Masquelin, H. (2026). Geophysical modeling in a drainage basin with a gold geochemical anomaly, Cerro da Cria Region, Vila Nova do Sul, Rio Grande do Sul (Brazil). Discover Geoscience, 4(1), Article 291. https://doi.org/10.1007/s44288-026-00669-1

Image Credits: AI Generated

DOI: 10.1007/s44288-026-00669-1

Keywords: gold exploration, geophysics, gamma-ray spectrometry, magnetometry, shear zone, orogenic gold, Brazil, drone photogrammetry, hydrothermal alteration, geochemical anomaly, structural geology, mineral exploration

The stakes are considerable. Chad is widely regarded as having substantial geological potential, yet more than 60 percent of its subsoil remains unexplored, according to the authors. The country sits within the Central African Pan-African Belt, a vast orogenic chain forged roughly 600 million years ago when the São Francisco-Congo cratons, the West African craton and the Saharan metacraton collided. In Chad this chain surfaces in several basement massifs, including Tibesti in the north, Ouaddaï in the east, Mayo Kebbi in the southwest, Guéra in the centre, and the little-studied Baïbokoum massif in the far south, which continues into Cameroon and the Central African Republic as part of the Adamawa-Yadé domain. Earlier work had dated syenites there to about 654 million years and associated granites to between 632 and 568 million years, but no systematic exploration map had ever been drawn.

The team’s raw material was a single, almost cloud-free Landsat 9 scene acquired on 18 February 2025, with cloud cover of just 0.21 percent. Landsat 9’s Operational Land Imager captures light from the visible, near-infrared and shortwave-infrared parts of the spectrum in nine bands, plus a 15-metre panchromatic band that the researchers fused with the 30-metre multispectral data to sharpen the imagery. Before any interpretation, the raw digital numbers were converted to surface reflectance and corrected for atmospheric distortion using the QUAC algorithm, which the authors note typically recovers reflectance spectra within 10 to 15 percent of ground reference values. That preprocessing matters: without it, water vapour and aerosols can masquerade as mineral signatures.

With clean data in hand, the researchers deployed a battery of image-processing techniques, each probing a different aspect of how rocks reflect light. False colour composites using bands 7, 5 and 3 gave a quick visual first pass, rendering syenites in light pink, gneisses in green and shales in white. Principal component analysis then compressed the spectral information from six bands into statistically independent components; the first three components carried 92.86, 5.94 and 0.84 percent of the total variance, and the third component isolated anomalies linked to altered and ferrous minerals. Minimum noise fraction transformation performed a similar trick while explicitly separating signal from noise, which proved especially useful for low-reflectance units such as syenites and shales.

Band ratios delivered the most direct mineralogical clues. Ratios such as 4/2 highlight iron oxides like hematite and goethite, which absorb strongly in the blue and reflect in the red; 6/7 targets the hydroxyl and carbonate absorption near 2.2 micrometres produced by clays and micas; and 6/5 picks out ferrous minerals. On these ratio images the team mapped iron-oxide zones, ferrous occurrences, clay-rich alteration and broader hydrothermal halos across the pluton. To push identification further, they ran the constrained energy minimization algorithm on bands 7, 5 and 3 against laboratory spectra from the USGS library, matching pixels to biotite, chlorite, goethite, hematite, illite, ilmenite, kaolinite, magnetite, pyrite and rutile.

The final classification step used the Spectral Angle Mapper, an algorithm that treats each pixel’s spectrum as a vector and measures its angular distance from reference spectra, making it relatively insensitive to illumination differences caused by topography. With a fixed threshold of 0.1 radians, SAM successfully separated syenite, shale and gneiss, and a confusion-matrix accuracy assessment returned an overall accuracy of 80 percent with a Kappa coefficient of 0.80. The authors report that in subsequent tests the method reached full agreement with reference data, underscoring its reliability for lithological mapping in Precambrian terrain, where subtle mineralogical contrasts and limited exposure typically defeat conventional interpretation.

Structure proved just as important as chemistry. Using the panchromatic band and the PCI Geomatica line tool, the team extracted lineaments, the linear traces of faults, fractures and shear zones that often channel mineralising fluids. Rose diagrams revealed dominant NE-SW and E-W trends, with an additional NNE-SSW set, and the iron-oxide anomalies align along the NE-SW corridor. Fieldwork grouped these structures into three deformation phases: D1 trending NW-SE, D2 from N-S to NNE-SSW, and D3 from E-W to NW-SE. Because lineaments can also reflect roads, vegetation boundaries or artefacts, the researchers validated them against geological maps and ground observations before accepting them as tectonic features.

The ground truth came from weeks of mapping and dozens of thin sections. Mount Kongaoura, a NE-SW-trending ridge south of the town, is built of fine-, medium- and coarse-grained syenites cut by pegmatite and aplite veins and studded with microsyenodiorite enclaves. Under the microscope, the coarse syenites contain 40 to 50 percent alkali feldspar with pyroxene, amphibole and biotite, while the metamorphic country rocks include hornblende-biotite gneisses with granonematoblastic textures, biotite gneisses, amphibolites dominated by 50 to 60 percent amphibole, and striking mylonites. At Mbaïssaye, a N15E shear corridor within the syenite shows potassium feldspar porphyroclasts crushed into a matrix that climbs from 30 to 60 percent of the rock, direct evidence of the ductile shearing that accompanied fluid circulation.

Stitching everything together in a GIS, the team produced a synthesis litho-mineral map that revises the region’s geology and flags its most promising ground. The syenitic units emerge as the principal hosts of iron oxides and ferrous minerals, while the gneisses carry significant hydroxyl-bearing alteration, with mineralisation styles consistent with greisen, skarn and quartz-vein systems controlled by foliations, fractures and joints. The authors are candid about the limits: the absence of geochemical data constrains interpretation, and spectral methods detect alteration, not ore grades. Their next step is automated processing of the imagery followed by whole-rock geochemistry on a much larger sample set. Even so, the message is clear and quietly transformative for a country where exploration budgets are thin: a free satellite scene, a laptop and a hammer can now do the work that once required years of costly reconnaissance, and in Baïbokoum they have just redrawn the map.

Subject of Research: Remote sensing and field-based mapping of mineralisation potential in the Baïbokoum pluton, southern Chad

Article Title: Mapping and discrimination of mineralisation potential of the Baïbokoum pluton (Southern Chad), using Landsat 9 OLI images and field observations

Article References: Gustave, B. R., Ousmanou, S., Ngarena, K. M., Jules, T. K., Souleymane, A. N., Merlin, G. D., & Maurice, K. (2026). Mapping and discrimination of mineralisation potential of the Baïbokoum pluton (Southern Chad), using Landsat 9 OLI images and field observations. Discover Geoscience, 4(1), Article 292. https://doi.org/10.1007/s44288-026-00673-5

Image Credits: AI Generated

DOI: 10.1007/s44288-026-00673-5

Keywords: Landsat 9, remote sensing, mineral exploration, Chad, Baïbokoum, syenite, iron oxides, hydrothermal alteration, Spectral Angle Mapper, principal component analysis, lineaments, Pan-African belt

The study, published in the journal Solid Earth, was led by Hui Zhang and Jiayong Yan of the Chinese Academy of Geological Sciences, working from the State Key Laboratory of Deep Earth and Mineral Exploration. The team revisited a 200-kilometer-long deep seismic reflection profile acquired in 2019 along the Wuning to Ji’an section of the central Jiangnan Orogenic Belt, a crooked survey line that snakes from Jiugong Mountain in the north, across the Xiushui-Wuning Basin and the Jiuling Upheaval, and down through the Pingle Depression toward the Wugongshan Upheaval. Their central finding is deceptively simple: before the data are migrated into a subsurface image, the irregularly spaced explosive shots used to generate the seismic waves should be computationally repositioned and interpolated onto a dense, regular grid at 100-meter intervals.

Why does irregularity matter so much? Deep seismic reflection profiling works by detonating charges in boreholes and recording the echoes that return from rock layers as far as 30 to 100 kilometers beneath the surface. In an ideal world, shots and receivers would sit at perfectly uniform intervals along a straight line, allowing every reflected wave to be summed coherently. In the real world of the Jiangnan Belt, the northern section climbs through Jiuling Mountain, where the relative elevation difference reaches 1,000 meters and slopes commonly exceed 45 degrees, making it nearly impossible to position drilling rigs exactly where the survey design demands. The southern section, by contrast, crosses densely populated plains and hills studded with towns, villages, and factories, forcing further deviations from the plan.

The consequences of those deviations ripple through the entire processing chain. When shots and receivers sit at irregular positions, the common midpoint points where reflected waves converge scatter across a two-dimensional plane rather than lining up neatly along the profile. Uneven offset distributions, large gaps between traces, and spatial aliasing, in which steeply dipping wave energy masquerades as false signal, all follow. When such data are migrated, the process that repositions reflections to their true subsurface locations, the irregularities generate migration artifacts, phantom structures that can be mistaken for real faults or rock bodies. Previous contractor-processed versions of the Jiangnan data showed exactly these problems: low signal-to-noise ratios overall, and no clear reflections from the major faults that were the survey’s principal targets.

Zhang and colleagues attacked the problem with an anti-aliasing version of a technique called Matching Pursuit Fourier Interpolation, or MPFI. The method converts irregular seismic data from the space-time domain into the frequency-wavenumber domain using Fourier transforms, then iteratively identifies the strongest coherent spectral components and rebuilds the missing data from them. The crucial innovation is the use of priors: the energy of the low-frequency part of the signal, typically the 15 to 35 hertz band in this study, is analyzed at various dips, and those energy curves are used as weighting factors for the higher frequencies up to 100 hertz. Because genuine reflections and aliasing noise behave differently across frequency, the priors allow the algorithm to distinguish real signal from aliased energy that would otherwise be wrongly selected, a failure mode that has long plagued conventional frequency-domain interpolation of sparse land data.

The team tested four regularization strategies on the Jiangnan dataset. The first simply filled gaps in the offset domain while leaving shot positions irregular, raising the fold, the number of traces summed at each point, from 80 to roughly 100 and producing moderate improvement. The second fully regularized all data in the offset domain, restoring common midpoint locations to their designed positions. The third repositioned irregular shots onto their pre-designed 200-meter grid in the shot domain. The fourth went further, regularizing the shots and then interpolating entirely new shot gathers to halve the spacing to 100 meters, doubling the fold to about 160. Quantitative analysis of power spectra, signal-to-noise estimates, and variance attributes showed a clear hierarchy, with the shot-domain methods consistently outperforming the offset-domain approaches.

The winning strategy, regularizing and infilling shot gathers at 100-meter intervals, raised the signal-to-noise ratio from approximately 1.5 to 2.5 in the shallow profiles, covering time windows of 0.5 to 6.5 seconds, and from roughly 2.0 to 3.5 in the deep sections between 5.5 and 11.5 seconds. Importantly, the effective frequency bandwidth remained essentially unchanged, meaning the gains came from genuine noise suppression and better coherence rather than artificial sharpening. The authors attribute the superiority of shot-domain processing to its physical logic: while offset-domain regularization merely shifts common midpoint positions and drags the underlying shot and receiver coordinates along with them, shot-domain regularization moves the actual shot points directly to their designed acquisition coordinates, a more faithful reconstruction of what the survey was meant to record.

The payoff became most dramatic in the pre-stack time migration images. Compared with the legacy stack profiles produced independently by two contractors, one processed in the field and one in-house, the newly processed sections revealed far clearer images of the region’s two dominant structures: the Yifeng-Jingdezhen Fault, a nearly vertical break extending westward into Hunan, and the Pingxiang-Guangfeng Fault, a crust-scale, northward-dipping fault that cuts through the crustal detachment surface down to the Moho and offsets it. The latter, identified as the southern boundary of the Qin-Hang belt and the northern boundary of the South China Block, is thought to act as a critical conduit for magma rising from depth. Major faults and their secondary fractures, the authors note, provided pathways for deep-source magmas and ore-forming fluids, and their reactivation promoted mineralization, which is precisely why sharper images of them matter for exploration.

The method does have limits, and the team is candid about them. Improvements were slightly weaker in the deepest sections, where signal attenuation with depth weakens the effective reflections that regularization depends on. The technique also performs best on crooked profiles whose lateral deviation stays within a quarter of the Fresnel radius of the target reflectors, a geophysical yardstick that ranges from roughly 100 to 700 meters for shallow targets and expands to 700 to 1,750 meters for deep crustal reflectors at 15 to 30 kilometers. Beyond that threshold, regularization risks distorting the wavefield and erasing small-scale geological features. Amplitude analysis at the survey line’s two major corners, with curvature angles of 19 and 4 degrees, confirmed that relative amplitude trends with offset were preserved, keeping amplitude-based interpretations trustworthy.

For a field that has long focused its innovation on velocity analysis and migration algorithms, the message of this study is that the humble step of data regularization, performed in the right domain before migration, can matter just as much. The work was supported by China’s National Science and Technology Major Project for Deep Earth Probe and Mineral Resources Exploration, the National Natural Science Foundation of China, and the China Geological Survey’s Deep Geological Survey Project. As demand grows for reliable images of the deep crust, both to reconstruct ancient supercontinents like Rodinia and to guide the hunt for buried metal deposits, the Jiangnan results suggest that the sharpest views of Earth’s interior may come not from new hardware, but from treating the data we already have with considerably more mathematical care.

Subject of Research: Shot-domain regularization of deep seismic reflection data in the Jiangnan Orogenic Belt, South China

Article Title: Enhancing 2D deep seismic reflection imaging using shot domain regularization: a case study from the Jiangnan Orogenic Belt, South China

Article References: Zhang, H., Yan, J., Liu, Z., Han, J., Wang, H., & Liu, J. (2026). Enhancing 2D deep seismic reflection imaging using shot domain regularization: a case study from the Jiangnan Orogenic Belt, South China. Solid Earth, 17(4), 689-709. https://doi.org/10.5194/se-17-689-2026

Image Credits: AI Generated

DOI: 10.5194/se-17-689-2026

Keywords: deep seismic reflection, seismic data regularization, Matching Pursuit Fourier Interpolation, Jiangnan Orogenic Belt, South China, signal-to-noise ratio, pre-stack time migration, mineral exploration, crustal structure, shot domain interpolation, tectonics, geophysics

Carbonatites are among the strangest rocks on Earth. They are igneous rocks composed of more than fifty percent carbonate minerals, yet they crystallise from molten carbonate rather than forming in oceans or lakes. They are volumetrically tiny, arising from extremely low degrees of partial melting of carbonated peridotite in the mantle, with melt fractions below roughly 0.05 weight percent. Despite their scarcity, carbonatites punch far above their weight economically: they host the highest rare earth element concentrations of any igneous rock type and have supplied the world with niobium, phosphate and light rare earths for nearly half a century. China’s Bayan Obo, the largest carbonatite-hosted rare earth deposit on the planet, illustrates the scale of what these rocks can deliver. With rare earth elements now classified as critical metals by most industrialised nations because of their indispensable role in green energy technologies, electric vehicle motors and wind turbines, every new carbonatite occurrence attracts immediate attention.

The Khaderpet carbonatite was discovered in 2002 by Rio Tinto Exploration during diamond-focused work on their 3-016 prospect in the Anumpalli Kimberlite Cluster. The plug intrudes an ultramafic lamprophyre known as aillikite, which itself was emplaced into Archaean granites, producing a distinctive granitoid breccia that geologists have likened to the carapace of a tortoise. Field relationships tell a clear story: the carbonatite contains angular clasts of the host granite but lacks any fragments of the lamprophyre, indicating that the carbonate magma arrived late, punching through the older breccia at the periphery of the complex. The rock weathers in the classic ‘panther skin’ pattern typical of carbonatites, and the surrounding granitoids display intense fenitisation, the brick-red alkali metasomatism produced by fluids exsolved from the carbonatitic magma. Caustic fusion of drill core from the prospect has even yielded good quality octahedral diamonds of transparent and grey varieties, adding a second commodity to an already unusual package.

Under the microscope, the Khaderpet carbonatite reveals an equigranular fabric dominated by calcite, which makes up ninety to ninety-five percent of the rock. The calcite grains display rhombohedral cleavage, twinkling relief and the high-order interference colours characteristic of carbonate under cross-polarised light. Scattered through this groundmass are accessory phases of considerable economic interest: euhedral fluorite crystals, apatite, phlogopite, garnet, magnetite and chromite, along with the rare earth bearing minerals monazite, titanite and allanite. These three minerals are the storehouses of the light rare earths, and their presence in thin section directly explains the exceptional whole-rock compositions. Flow banding in the finer grained portions of the rock, with aligned calcite crystals recording the movement of the magma, further attests to the intrusive, magmatic character of the body. Alteration of calcite to dolomite is common, particularly toward the rock margins.

The geochemistry is where Khaderpet truly stands out. Ten fresh outcrop samples analysed by X-ray fluorescence and inductively coupled plasma mass spectrometry show calcium oxide contents of 46.8 to 53.8 weight percent with negligible magnesium and iron, classifying the rock unambiguously as a calcio-carbonatite. Total rare earth element concentrations range from about 4100 to 4500 parts per million, of which the light rare earths contribute nearly everything, between 4092 and 4509 parts per million, while the heavy rare earths amount to a mere 19 to 24 parts per million. The ratio of light to heavy rare earths reaches values of 180 to 230, and the chondrite-normalised patterns show the steep, step-like profile typical of carbonatites worldwide, with a lanthanum-to-lutetium ratio of about 29 and an extraordinarily high lanthanum-to-ytterbium ratio near 282. Strontium concentrations of nearly 11,000 parts per million, barium around 900 parts per million, and elevated niobium, thorium and uranium complete the classic carbonatite trace element signature.

This extreme fractionation of light over heavy rare earths carries a profound petrogenetic message. It indicates that the Khaderpet magma formed by very low degrees of partial melting of carbonated mantle peridotite, followed by liquid immiscibility that separated the carbonate melt from its silicate sibling. Ratios of zirconium to hafnium, ranging from 85 to 115, and niobium to tantalum, from 110 to 270, show positive correlations consistent with a mantle origin. The primitive mantle-normalised trace element patterns display peaks for uranium, lanthanum, cerium and neodymium with troughs for rubidium and niobium, matching the fingerprints of metasomatised upper mantle sources. In short, the Khaderpet carbonatite is a genuine window into processes operating deep within the lithospheric mantle beneath the Eastern Dharwar Craton, a region whose thick lithospheric root has already proven fertile ground for more than 150 kimberlite and related intrusions.

Stable isotope analysis provides the final confirmation of primary character. Carbon and oxygen isotope measurements on five samples, performed at the Wadia Institute of Himalayan Geology, yield oxygen isotope values between 6.6 and 8.76 per mil and carbon isotope values between minus 7.45 and minus 6.33 per mil. These compositions fall squarely within the ‘primary igneous carbonatite’ box defined by decades of global data, overlapping the fields established for unaltered carbonatites from Precambrian terranes. Primary isotopic compositions essentially mean the rocks escaped crustal contamination and represent unmodified partial melts of the mantle. Combined with the petrography and trace element systematics, the isotope data leave little doubt that the Khaderpet carbonatite is a magmatic rock of deep origin, not a hydrothermal or secondary carbonate.

Perhaps the most consequential finding is economic. On geochemical discrimination diagrams plotting strontium-to-barium ratios and barium against total rare earth content, the Khaderpet samples plot in the ‘mineralised’ field, the same territory occupied by the Weishan rare earth deposit in China. The total rare earth content of Khaderpet exceeds that of several better-known south Indian carbonatites and approaches the values recorded at Hogenakkal, although it remains below the concentrations at Samalpatti, Pakkanadu and the Kamthai deposit, which to date is the only carbonatite-hosted rare earth occurrence in India proven feasible for mining. A drone magnetic survey has delineated an areal extent of roughly 100 by 200 metres with an average depth of 40 metres for the intrusion, but previous exploration drilled only a single shallow hole targeting diamonds. The authors argue that detailed drilling, ore characterisation and beneficiation studies are now essential to establish the order of magnitude of the rare earth oxide resource and to determine whether profitable extraction is possible.

The broader context amplifies the stakes. India currently hosts more than fifty confirmed and suspected carbonatite occurrences, and the Geological Survey of India has expanded its critical mineral exploration projects from 65 in 2020-2021 to 195 in 2024-2025, with several alkaline and carbonatite complexes among the targets. Recent discoveries across the Dharwar Craton, at Gollapalli in Telangana, Gundlupet in Karnataka and Krishtipadu in Andhra Pradesh, suggest the craton is far more carbonatite-fertile than previously recognised. The Khaderpet occurrence carries a double dividend: if the rare earth potential is confirmed, the site benefits from well-developed roads, water infrastructure and abundant local labour, and development would create employment while adding to national rare earth production. The study also issues a practical warning for explorers: carbonatites can hide alongside kimberlites, so any investigation of mantle-derived exotic rocks in the Indian Shield should watch carefully for associated carbonate intrusions. A small plug in a farmer’s field may yet prove to be a strategic national asset.

Subject of Research: Geochemistry and economic potential of a light rare earth element enriched carbonatite intrusion associated with kimberlitic rocks in the Eastern Dharwar Craton, India

Article Title: Geochemical studies and economic perspective of light rare earth element (LREE) enriched carbonatite from Khaderpet, Eastern Dharwar Craton

Article References: Phani, P. R. C., & Sengupta, P. (2026). Geochemical studies and economic perspective of light rare earth element (LREE) enriched carbonatite from Khaderpet, Eastern Dharwar Craton. Discover Geoscience, 4(1), Article 308. https://doi.org/10.1007/s44288-026-00663-7

Image Credits: AI Generated

DOI: 10.1007/s44288-026-00663-7

Keywords: carbonatite, rare earth elements, LREE, kimberlite, Dharwar Craton, India, geochemistry, stable isotopes, monazite, critical minerals, diamonds, mineral exploration

The problem the researchers identified is called smoothing-induced weak annotation, or SiWA. In data-driven mineral prospectivity mapping, positive training samples are labeled locations where mineralization is known to occur. Ideally, the area or volume of each labeled sample would exactly match the footprint of the deposit it contains. In practice, at national and continental scales, this is nearly impossible. A single grid cell in a pan-Canadian study might cover more than five square kilometers, while the deposit inside it could occupy a tiny fraction of that space. The result is a positive sample that is overwhelmingly composed of barren ground, diluting the true geological signature of mineralization with noise from its surroundings.

Zhang and Parsa describe this with a simple analogy: a shoebox labeled as containing a tennis ball, when it actually holds a tennis ball buried among many other objects. The label is not wrong, but it is imprecise, and any learning system trained on it must guess which part of the box matters. In geostatistical terms, the annotated sample has a much larger support than the target it is meant to represent. When covariates are averaged over that larger area, the distinctive nonlinear fingerprints of mineralization are attenuated into the background, a process mathematically analogous to low-pass filtering a signal.

The theoretical consequences are striking. As the ratio of annotated area to deposit footprint grows, the averaging of many mostly negative subsamples invokes the central limit theorem, pushing the joint distribution of predictors and labels toward a multivariate normal distribution. The conditional expectation of the predictand then becomes a linear function of the predictors. In other words, smoothing artificially linearizes the relationship the machine learning model is trying to learn. The hypothesis the algorithm fits is no longer the true relationship between mineral-system evidence and mineralization, but a smoothed, linearized approximation of it. This mirrors a well-known effect in time-series forecasting, where averaging over windows longer than the autocorrelation timescale erases high-frequency, nonlinear patterns and erodes the advantage of nonlinear models.

To test these ideas empirically, the authors turned to two pan-Canadian datacubes, one targeting flake graphite and the other magmatic nickel, with or without copper, cobalt, and platinum-group elements. Both mineral systems host deposits believed to be small relative to the resolution of the data, making them naturally vulnerable to SiWA. The datasets contained 1,239 and 1,240 positive samples respectively, drawn from federal, provincial, and territorial geological surveys, ranging from minor occurrences to operating mines. The covariates included geological, geophysical, and geochronological layers such as crustal thickness, gravity and magnetic data, density models, and depth to the Mohorovicic discontinuity, all integrated on the H3 discrete global grid system at resolution 7, where each hexagonal cell averages 5.16 square kilometers.

The experimental design was deliberately rigorous. Rather than hand-picking a single algorithm, the researchers employed a deep ensemble workflow comprising 2,000 unique model configurations per target, spanning eight machine learning algorithms from logistic regression and naive Bayes to random forests, support vector machines, Gaussian processes, and neural networks, combined with 25 feature-space variants, five negative-labeling schemes, and two hyperparameter-tuning metrics. Smoothing was then applied exclusively to positive samples by expanding their labels into progressively larger neighborhoods of hexagonal cells, from the origin cell out to k-rings spanning an average centroid distance of 21.4 kilometers, roughly two orders of magnitude larger than the likely footprint of the deposits. Negative samples and covariates were left untouched, isolating annotation weakness as the sole experimental variable.

The results were counterintuitive and, in some ways, alarming. As annotation resolution decreased, apparent model performance actually improved, with both the area under the receiver operating characteristic curve and the weighted F1-score rising in an asymptotic fashion toward an elbow near k equals 3. At the same time, the prospective area shrank dramatically, with high-probability zones vanishing first, particularly in regions far from known positive samples. The sensitivity of the mapping outcome to annotation resolution proved to be on the same order as the sensitivity to the choice of machine learning algorithm itself, and an order of magnitude greater than the sensitivity to negative samples, tuning metrics, or feature dimensionality. In short, an aspect of study design often treated as innocuous turned out to rival the most heavily engineered component of the entire workflow.

The mechanism behind these trends became clear when the authors stratified their ensembles by performance. The lowest-performing quartile of workflows was dominated by simple, almost exclusively linear models such as logistic regression and naive Bayes configured with few features, and these models were the least affected by smoothing, retaining target areas most similar to the unsmoothed baseline. The highest-performing, most expressive nonlinear models, by contrast, lost nearly all of their advantage once smoothing was applied, contributing essentially nothing to the merged ensembles beyond the baseline. This is the signature of linearization: when the learnable relationship has been flattened by averaging, a linear model can capture it as well as a deep network, and the extra capacity of nonlinear methods is wasted. Meanwhile, workflow-induced uncertainty, measured as the dissent among the 2,000 equiprobable models, spiked precisely where positive samples were located, indicating that models shifted from broad agreement near known mineralization to fundamental disagreement as annotation weakened.

The implications ripple outward in several directions. First, the probabilistic meaning of a prospectivity map depends directly on annotation strength. If cells are coarser than deposit footprints, the chance of actually finding a deposit within any flagged cell is the model’s posterior probability multiplied by an annotation probability that can be vanishingly small; for the Canadian datasets, the authors estimate odds as poor as one in nearly 38,000 for the smallest targets. Field validation campaigns must therefore acquire far more samples to reach statistical significance when annotation is weak. Second, performance comparisons between studies conducted at different resolutions, on different targets, or in different regions are fundamentally incomparable unless annotation strength is explicitly controlled, a caution that strikes at the heart of the benchmarking and review culture in machine learning for geoscience. Third, and perhaps most practically, model complexity should be matched to annotation strength rather than maximized, because expressive models trained on heavily smoothed data learn relationships that are artifacts of the labeling strategy rather than properties of the Earth.

Solutions are not straightforward. Approaches developed in medical image segmentation and other weak-supervision domains, such as blending strong and weak labels, refining annotations, or rejecting noisy samples, assume that strongly annotated data exist somewhere in the pipeline, an assumption that fails at continental scales where deposit footprints are unknown and covariate resolution is costly to improve. The authors argue that the most reliable remedy, at least for now, is the one already familiar from time-series forecasting: choose simpler, more linear models when annotation strength is low, and never let model expressivity exceed what the data can support. Over the longer term, improving the resolution of primary and secondary datasets and profiling the geostatistical footprints of positive samples could reduce the severity of SiWA at its source. What is certain is that annotation quality, long a quiet afterthought in mineral prospectivity mapping, must now be recognized as a first-order control on what these powerful AI maps actually mean, and on whether the critical minerals they promise can truly be found.

Subject of Research: The effect of smoothing-induced weak annotation on data-driven mineral prospectivity mapping models

Article Title: The Effects of Smoothing-Induced Weak Annotation in Mineral Prospectivity Mapping

Article References: Zhang, S. E., & Parsa, M. (2026). The Effects of Smoothing-Induced Weak Annotation in Mineral Prospectivity Mapping. Natural Resources Research. https://doi.org/10.1007/s11053-026-10760-6

Image Credits: AI Generated

DOI: 10.1007/s11053-026-10760-6

Keywords: mineral prospectivity mapping, machine learning, weak annotation, geodata science, data quality, smoothing, critical minerals, graphite, magmatic nickel, uncertainty, geostatistics, mineral exploration