Urban soils are unlike any others. Excavation, backfilling, sealing, compaction, demolition, and the importation of exogenous materials create intricate mosaics of soil horizons and anthropogenic deposits over very short distances. Physical and chemical properties such as texture, bulk density, porosity, organic matter content, pH, nutrient availability, and contaminant concentrations can change abruptly both laterally and vertically. Trace metals and organic pollutants inherited from former industrial activities, traffic emissions, and construction materials are frequently distributed in localized hotspots, further increasing spatial complexity. This heterogeneity challenges conventional soil sampling strategies, which often fail to adequately represent the spatial organization of soil properties and associated environmental constraints, making accurate characterization essential for land-use planning and avoiding inappropriate uses.

Over the past two decades, near-surface geophysical methods have become valuable tools for investigating soil spatial variability because they provide rapid, non-invasive, and spatially continuous information at resolutions that cannot be achieved through conventional sampling alone. Techniques including electromagnetic induction, ground-penetrating radar, seismic methods, and gamma-ray spectrometry respond to different physical properties of the subsurface, such as electrical conductivity, dielectric permittivity, seismic velocity, or natural radioactivity, which are themselves controlled by soil texture, water content, porosity, bulk density, clay mineralogy, soil structure, and the presence of coarse fragments or anthropogenic materials. Among these approaches, ERT has received particular attention because it provides high-resolution two- and three-dimensional images of the spatial distribution of subsurface electrical resistivity. The method is based on injecting electrical current into the ground and measuring the resulting potential differences, from which the true resistivity distribution is estimated through inversion procedures.

Soil electrical resistivity is governed by several interacting factors, including water content, pore connectivity, texture, clay mineralogy, porosity, and the abundance of coarse fragments or anthropogenic materials. Because electrical current is transmitted predominantly through the pore water rather than the solid mineral phase, bulk resistivity is controlled by the amount and composition of the pore water, pore connectivity, and the geometry of the pore network, all of which are strongly influenced by soil texture, structure, coarse fragment content, compaction, and horizon development. Consequently, resistivity integrates the effects of several key soil attributes and provides a physically meaningful representation of subsurface heterogeneity rather than direct measurements of individual soil properties. This integrative nature is particularly advantageous in urban environments, where soil variability often results from multiple superimposed processes that cannot easily be disentangled using conventional point measurements alone.

The study site was a plot of approximately 1,000 square meters located on the IRD site in Bondy, within the Seine-Saint-Denis department of the Paris metropolitan area. According to the land-use plan of the city of Bondy, the site lies over a succession of alluvial deposits derived from the 1:50,000-scale geological map produced by the French Geological Survey. Historically, the area was known in the mid-18th century for its dense forest, as shown in the 1756 Cassini map, and later became a popular destination for Parisians seeking rural retreats. The site was significantly altered during the construction of the IRD research center in 1947, when many gardens, vegetable plots, and refuse areas were consolidated, and the topography was substantially modified through the import and leveling of various materials, subsequently covered with a layer of forest-origin topsoil that was initially uncontaminated.

The ERT survey was carried out along linear profiles using a SYSCAL Pro resistivity meter operating quadrupoles sequentially selected among seventy-two electrodes. Measurements were performed using two electrode arrays: a reciprocal Wenner-Schlumberger configuration, which is well adapted to detect vertical contrasts in electrical resistivity and offers a better signal-to-noise ratio and greater depth of investigation, and a Dipole-Dipole configuration, which better captures horizontal contrasts and yields more pronounced resistivity contrasts at shallow depths. Short transverse profiles of 26.25 meters were spaced every 6 meters, while long longitudinal profiles of 53.25 meters were spaced every 1.5 meters, with a unit electrode spacing of 0.75 meters for both sets. The total number of measurements collected was 1,870 for the Dipole-Dipole array and 2,282 for the Wenner-Schlumberger array. Data interpretation was performed using RES2DINV and RES3DINV software, and spatial variation maps of calculated resistivity as a function of depth were generated using Surfer software.

The resistivity maps revealed significant variability both laterally and vertically. A linear anomaly observed at x = 5, extending down to approximately 90 centimeters depth, corresponded to a trench, with additional trench-like features visible near the center of the site radiating from a central manhole. At the surface, a first layer with resistivity around 50 ohm-meters corresponded to the topsoil layer distributed across the site. Below this, starting at approximately 25 centimeters depth, a second layer appeared with markedly lower resistivity values, indicative of coarse backfill material. In some areas, high-resistivity materials emerged with values reaching up to 315 ohm-meters, while at greater depths, intermediate resistivity zones of around 102 ohm-meters were detected in the southern and northeastern parts of the site, possibly corresponding to sandy pockets. The three-dimensional inversion enabled the generation of vertical resistivity profiles across the site with a spatial resolution of 37.5 by 37.5 square centimeters.

Two combined statistical analyses, Principal Component Analysis and Hierarchical Cluster Analysis, were used to classify all resistivity profiles by depth into four distinct groups, which served as the basis for the resulting classification map. While resistivity values were relatively similar across classes in the uppermost layer from 0 to 0.5 meters, they became highly discriminant between 0.5 and 2.5 meters depth. Class 1 showed both maximum and median resistivity values below 100 ohm-meters, whereas Class 4 reached a maximum resistivity exceeding 300 ohm-meters with median values around 220 ohm-meters. Classes 2 and 3 were intermediate, and Class 3 was notably distinct, characterized by a near-linear increase in resistivity with depth and high values beyond 2.5 meters. Following this typology, 30 auger surveys were distributed according to a proportionally stratified sampling design considering the surface area of each mapped resistivity unit, and soil samples were collected in each of the four soil categories at four different depths, totaling 120 samples.

The subsequent laboratory characterization showed that the ERT-derived classes corresponded to meaningful differences in measured soil characteristics. Soil texture was primarily controlled by depth, with only a weak effect of soil class, and the overall profiles exhibited a coarse texture with sand contents of 71 to 76 percent across layers. Classes C3 and C4 were relatively enriched in fine silt and clay, and significantly coarser textures occurred in layers B and C of soil class C4, which was also characterized by a relatively high sand content and low clay content in the surface layer. High concentrations of organic carbon and total nitrogen were observed in the surface layer corresponding to the added topsoil, with organic matter content decreasing markedly with depth to approximately tenfold lower organic carbon concentrations in the deepest layer. Both pH in water and pH in potassium chloride varied only with depth, showing an increase of approximately 0.5 pH units from the surface to the deepest layer, while cation exchange capacity, Olsen phosphorus, and most exchangeable cations were mainly driven by depth, positively correlated with soil organic carbon but negatively correlated with pH.

Mid-infrared spectroscopy revealed clear differences in organic matter composition among the ERT-derived classes, particularly for hydrophobic functional groups and polysaccharide-related compounds, suggesting that ERT may be more sensitive to qualitative differences in organic matter than to its total abundance. This interpretation is physically plausible because organic matter exerts a strong indirect control on soil electrical properties through its influence on aggregate stability, pore architecture, wettability, and water retention rather than through its intrinsic electrical conductivity. Hydrophobic organic compounds may reduce soil wettability and modify infiltration patterns, whereas microbial polysaccharides promote aggregate formation and enhance pore connectivity, thereby influencing the spatial distribution of soil water and the propagation of electrical current. Elemental composition determined by ICP-MS showed a strong and significant effect of depth for most elements, with significant differences among soil classes observed for several major elements including aluminum, iron, magnesium, and phosphorus, as well as for trace elements such as chromium and zinc. Trace elements, particularly lead, were detected at the site, but no significant differences among soil types were observed except in deeper layers, and variations in physico-chemical conditions, especially soil moisture, may influence trace element speciation and mobility, potentially affecting biota.

The findings carry broad implications for how cities understand the ground beneath them. Because the geoelectrical classes were established before soil sampling, the subsequent physicochemical measurements provided an independent assessment of whether the geophysical units corresponded to systematic differences in soil characteristics, and the significant differences observed when the physicochemical variables were considered jointly support the relevance of the spatial classification. ERT proved valuable not only for identifying spatial discontinuities but also for confirming the relative homogeneity of the site, thereby reducing uncertainty in soil characterization regardless of the degree of anthropogenic disturbance. The approach extends the use of ERT beyond conventional subsurface characterization by using continuous geophysical information as an operational decision-support tool for subsequent soil sampling, with broad potential applications including the optimization of soil quality and contamination monitoring programs, as well as the design of field experiments that account for pre-existing soil heterogeneity and thereby reduce experimental bias. Future studies should investigate the potential of time-lapse ERT, combined with complementary techniques such as electromagnetic induction, ground-penetrating radar, and digital soil mapping, to better characterize soil functioning, contaminant mobility, and temporal changes in urban environments, potentially opening new opportunities to investigate the links between soil structure, hydrological functioning, and carbon cycling in urban ecosystems.

Subject of Research: Urban soil science and geophysical characterization

Article Title: Exploring spatial variability in the physical and chemical properties of urban soils using electrical resistivity tomography

Article References: Ribler, C., Lerch, T. Z., & Robain, H. (2026). Exploring spatial variability in the physical and chemical properties of urban soils using electrical resistivity tomography. Frontiers in Soil Science, 6, Article 1924576. https://doi.org/10.3389/fsoil.2026.1924576

Image Credits: AI Generated

DOI: 10.3389/fsoil.2026.1924576

Keywords: electrical resistivity tomography, urban soils, soil sampling, organic matter, trace elements, geophysics, Exploring, spatial, variability, physical, chemical, properties

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

Seismic anisotropy is not a niche curiosity. It arises naturally in shale, fractured reservoirs, and layered sedimentary sequences, and it measurably distorts the paths and arrival times of seismic waves. When anisotropy is ignored, calculated traveltimes and ray paths become biased, which degrades earthquake localization, velocity analysis, and the seismic imaging workflows that underpin oil and gas exploration. Transversely isotropic media provide a workable mathematical representation of many such formations. Geophysicists classify them by the orientation of their symmetry axis: vertically transversely isotropic models describe horizontally layered strata, horizontally transversely isotropic models approximate vertical fracture sets, and tilted variants capture dipping beds and tectonically deformed rocks whose symmetry axes vary in both inclination and azimuth.

Ray tracing itself is a mature technique. Under the high-frequency approximation, valid when wavelengths are much smaller than the scale of medium variations, the wave equation reduces to first-order ordinary differential equations that describe how rays propagate. Compared with full-wavefield simulation, ray tracing demands far fewer computational resources while delivering exactly the kinematic quantities, ray paths, propagation directions, and traveltimes, that many seismic-processing workflows require. The trouble is that in anisotropic media the phase velocity, the speed of wavefront motion along its normal, generally differs from the group velocity, the speed and direction of energy propagation. Any credible anisotropic ray tracer must treat phase velocity, group velocity, slowness, and symmetry-axis orientation consistently.

Conventional Hamiltonian ray tracing in anisotropic media is built on elastic stiffness parameters. The Christoffel equation supplies the eigenvalues and eigenvectors associated with the quasi-P, quasi-SV, and SH wave modes, and the eigenvalue of the selected branch is used to construct the Hamiltonian and its derivatives. This machinery becomes especially cumbersome for tilted transversely isotropic media, because the stiffness tensor is defined in a local symmetry-axis coordinate system and must be rotated into global coordinates through a Bond transformation. After rotation, most entries of the global stiffness matrix become nonzero, and the algorithm must repeatedly assemble, differentiate, and decompose the Christoffel matrix at every integration step. Wave-mode singularities and near-degenerate directions can further complicate the numerics. Exploration applications, moreover, usually describe anisotropy through symmetry-axis velocities and Thomsen parameters rather than a complete stiffness tensor, so conversion between parameterizations adds yet more algebraic overhead.

The new method, developed by Jianen Xiao and Ning Qin, takes a different route. Instead of constructing the Hamiltonian from a Christoffel eigenvalue, it builds the ray equations directly from the analytical quasi-P-wave phase velocity of the transversely isotropic medium and its spatial and directional derivatives. The phase angle is computed from the wavefront-normal direction and the local symmetry axis, so the same equations represent isotropic, vertically transversely isotropic, and tilted transversely isotropic media within a single framework. In the isotropic limit, the directional phase-velocity derivative vanishes and the system reduces to the conventional isotropic ray equations, an elegant continuity that reflects the underlying physics. Because the analytical phase-velocity expression directly connects commonly used anisotropic parameters to directional speed, the method avoids repeated Bond transformations and Christoffel eigensystem calculations altogether during ray integration.

Mathematically, the formulation retains the canonical Hamiltonian structure. The slowness vector points along the wavefront normal with a magnitude equal to the reciprocal of phase velocity, and its evolution along the trajectory determines the ray path and accumulated traveltime. In anisotropic propagation, the derivative of the Hamiltonian with respect to slowness contains a first-order directional derivative of phase velocity, a term that captures the geometry of the phase-velocity surface and distinguishes anisotropic from isotropic behavior. The spatial evolution can equivalently be written using group-velocity components, which account for the fact that energy propagation direction differs from the wavefront normal. The resulting first-order equations are integrated with a fourth-order Runge-Kutta scheme, updating ray position and slowness simultaneously at each step.

The authors validated the approach through three groups of numerical experiments. In homogeneous isotropic, vertically transversely isotropic, and tilted models on a 101 by 101 by 101 grid with 10-meter spacing, ray-traced traveltime contours agreed closely with analytical solutions, fast-marching reference traveltimes, and wavefronts simulated with a pure quasi-P-wave finite-difference equation. In the anisotropic cases, wavefronts became elliptical rather than circular because phase velocity varied with direction, and traveltime errors remained below 5 milliseconds. Additional tests with symmetry-axis tilt angles of 30 and 60 degrees confirmed that the method tracks wavefronts accurately as the symmetry axis rotates. Notably, the study did not include a matched comparison against an independently implemented Christoffel-based ray tracer, which the authors acknowledge would allow runtime and accuracy differences to be quantified under identical conditions.

A layered model then tested the transition from isotropic to anisotropic layers on a 301 by 301 by 301 grid. Rays traced in isotropic and anisotropic versions of the model coincided within the isotropic uppermost layer and gradually diverged after entering the anisotropic region, exactly as physics dictates. The ray-traced traveltime field matched the simulated wavefronts across layer interfaces and within the anisotropic region, supporting the method’s validity in heterogeneous layered media. The final and most demanding test used the SEAM Foothills benchmark, a geologically realistic model with irregular structures and strong velocity variation, discretized with 439 by 180 by 180 grid points at 25-meter spacing. The local tilt angle was derived from the velocity field using plane-wave destruction filters, which estimate local structural slopes, while the azimuth angle was fixed at zero so symmetry-axis variation was confined to the inline-depth plane. Despite the strong heterogeneity and complex interfaces, ray-traced traveltime contours closely followed the simulated quasi-P wavefronts throughout the model.

The distinction between ray tracing and full-wavefield modeling is worth emphasizing. A finite-difference method propagates the complete wavefield on a spatial grid through successive time steps, capturing waveforms, interference, reflections, diffractions, and finite-frequency effects at a cost that scales with grid points and time steps. The new ray tracer, by contrast, integrates high-frequency quasi-P-wave characteristics only along selected rays, so its cost depends primarily on the number of rays and integration steps rather than the entire space-time grid. It does not reproduce complete waveforms or finite-frequency scattering, and the finite-difference simulations in the study served only as independent references for the calculated wavefronts. The authors also note that sequential integration can accumulate numerical errors from Runge-Kutta truncation, parameter interpolation, and phase-velocity derivative evaluation, so long ray paths, sharp interfaces, and rapidly varying symmetry axes may require smaller steps or adaptive integration.

Within these boundaries, the phase-velocity-based formulation offers a transparent and practical framework for quasi-P-wave traveltime modeling, tomography, and ray-based imaging in heterogeneous transversely isotropic media. By replacing repeated stiffness-tensor rotations and eigensystem decompositions with a single analytical velocity expression and its derivatives, the method lowers the algebraic barrier that has kept fully three-dimensional tilted anisotropy out of routine ray-based workflows. As exploration moves into increasingly complex foothills and fractured terrains, tools that compute anisotropic traveltimes accurately and efficiently will only grow in importance, and this study provides a concrete step in that direction.

Subject of Research: A phase-velocity-based 3D ray-tracing method for qP waves in transversely isotropic media that avoids repeated stiffness-tensor rotations and Christoffel eigensystem calculations

Article Title: A phase-velocity-based 3D ray tracing method for transversely isotropic media

Article References: Xiao, J., & Qin, N. (2026). A phase-velocity-based 3D ray tracing method for transversely isotropic media. Frontiers in Earth Science, 14, Article 1967527. https://doi.org/10.3389/feart.2026.1967527

Image Credits: AI Generated

DOI: 10.3389/feart.2026.1967527

Keywords: ray tracing, transversely isotropic media, seismic anisotropy, qP waves, phase velocity, eikonal equation, Hamiltonian ray theory, Runge-Kutta integration, traveltime modeling, SEAM Foothills model, geophysics, Frontiers in Earth Science

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 research, led by Yenesew Asradew Nibret of Injibara University together with Habtamu Tesfaye Ayalew of Woldia University and Fekadu Debebe of Injibara University, tackles a problem that is becoming urgent across fast-growing urban centers in Ethiopia. Population explosion, agricultural expansion, and industrialization are placing mounting pressure on scarce water sources, and the volcanic aquifers that many communities depend on are notoriously difficult to characterize. Unlike sedimentary aquifers, where water saturates the pore spaces between grains, basalt aquifers hold their water in secondary features — fractures, joints, and vesicles left behind by escaping volcanic gases. Drill in the wrong spot and a borehole can pass through hundreds of meters of essentially impermeable rock.

To find the right spots, the team combined three independent lines of evidence: vertical electrical sounding, borehole lithology logging, and gravity surveys. Vertical electrical sounding is a technique in which an electric current is injected into the ground through electrodes and the resulting voltage is measured to determine how resistive the subsurface layers are. Because water-bearing fractured rock, clay, and solid basalt all conduct electricity differently, the resistivity profile acts as a kind of fingerprint of the underground geology. The researchers inverted their sounding data with root mean square errors ranging from just 1.65 to 4.27 percent, a level of fit that lends considerable confidence to the resulting models of the subsurface.

The inverted resistivity models revealed a heterogeneous volcanic succession made up of topsoil, clay, fractured basalt, and massive basalt. Each of these units plays a distinct role in the hydrogeological system. Fractured and vesicular basalt layers, with medium resistivity values between 45 and 239 ohm-meters, emerged as the major aquifer zones. Their secondary porosity — the network of cracks and gas bubbles that water can occupy — and their enhanced permeability make them the productive heart of the system. Clay layers, by contrast, showed very low resistivity between 6 and 20 ohm-meters; clays conduct electricity well because of their charged mineral surfaces and bound water, but they hold that water tightly and act as aquitards, impeding flow. Massive basalt, with resistivity exceeding 322 ohm-meters, is effectively impermeable and forms the basement through which little water moves at all.

Borehole lithology logs provided the ground truth for this electrical picture. Where wells had already been drilled, the physical rock samples confirmed that the porous scoriaceous and fractured basalt layers were exactly the zones producing groundwater. This agreement between the geophysical inversion and the direct observations from drilling is critical, because it demonstrates that resistivity contrasts in this terrain are not merely geological curiosities but reliable predictors of water yield. For water managers deciding where to spend scarce drilling budgets, that correlation is worth a great deal.

The second pillar of the study was gravity. Gravity surveys measure tiny variations in the strength of Earth’s gravitational pull at the surface, variations caused by differences in the density of the rocks below. Dense, unfractured massive basalt pulls slightly harder than broken, fractured, and weathered rock, which contains voids and lighter infill material. After correcting the raw measurements for elevation, latitude, and other effects to produce Complete Bouguer anomalies, the researchers found values ranging from −219 to −204 milligal across the study area. Residual gravity anomalies, which isolate the signal of shallow density contrasts, ranged from −7.09 to +7.11 milligal. The low anomalies corresponded to fractured zones with favorable conditions for water collection, while the high anomalies marked dense massive basalt with essentially no groundwater potential.

To sharpen the picture further, the team applied derivative gravity methods — mathematical transformations of the gravity field that emphasize shallow, sharp density boundaries. The First Vertical Derivative highlights the rate of change of gravity with depth, making the edges of density bodies pop out. The Total Horizontal Derivative does the same for lateral changes, tracing the outlines of buried structures. The Analytical Signal combines both and is particularly useful because its maxima tend to sit directly over the edges of causative bodies, independent of the direction of magnetization or the inclination of the field. Together, these techniques allowed the researchers to delineate weak zones and fractures — the very structures that increase groundwater permeability and channel water through otherwise impermeable volcanic rock.

The overarching conclusion of the study is deceptively simple but has profound implications: groundwater presence in this terrain depends on fracture intensity, connectivity, and aquifer thickness, not on lithology alone. Two adjacent boreholes drilled into chemically identical basalt can yield dramatically different amounts of water if one intersects a dense, connected fracture network and the other does not. This structural control means that the traditional approach of drilling where the geology looks promising on a map is insufficient. What is needed is a map of the fracture system itself — and that is precisely what the integrated geophysical approach delivers.

The methodological lesson extends well beyond the study area in Ethiopia’s volcanic highlands. Fractured basalt aquifers underlie vast swaths of the East African Rift, the Deccan Traps of India, the Columbia River Basalts of the United States, and Iceland, supplying water to hundreds of millions of people. In many of these regions, groundwater is the buffer against drought, and drilling a dry borehole is not just a financial loss but a setback for an entire community. A workflow that pairs electrical resistivity sounding, which senses the water and the clay, with gravity and its derivatives, which sense the density structure and the fractures, offers a way to reduce that risk substantially before a drill rig is ever mobilized.

There is also a sustainability dimension to the findings. Knowing where the productive fractured zones are, how thick they are, and how they connect is the first step toward managing them responsibly. An aquifer whose storage is confined to discrete fracture networks can be depleted quickly if pumping exceeds recharge, and contaminants can travel through those same fast pathways with little filtration. By identifying the aquifer zones and the impermeable boundaries around them, geophysical mapping provides the spatial framework needed for well placement, protection zoning, and long-term monitoring. As Ethiopian cities grow and climate variability intensifies, the ability to read the hidden fracture architecture of volcanic rock may prove to be one of the most valuable tools in the effort to secure water for the millions who live above it.

Subject of Research: Integrated geophysical mapping of fractured basalt aquifers for groundwater exploration in Ethiopia

Article Title: Integrated electrical resistivity and gravity geophysical investigation of structurally controlled fractured basalt aquifers for sustainable groundwater development

Article References: Nibret, Y. A., Ayalew, H. T., & Debebe, F. (2026). Integrated electrical resistivity and gravity geophysical investigation of structurally controlled fractured basalt aquifers for sustainable groundwater development. Discover Sustainability. https://doi.org/10.1007/s43621-026-04914-y

Image Credits: AI Generated

DOI: 10.1007/s43621-026-04914-y

Keywords: fractured basalt aquifer, vertical electrical sounding, gravity survey, structural control, groundwater exploration, sustainable groundwater development, hydrogeology, geophysics, Ethiopia, resistivity inversion, analytical signal, volcanic rocks

The technique at the heart of the study, known as Vertical Electrical Sounding, or VES, is elegantly simple in principle but powerful in practice. Two pairs of electrodes are driven into the ground: one pair injects a direct electrical current into the earth, while the other measures the resulting potential difference. Because water-saturated rocks conduct electricity far better than dry, compact ones, the measured resistance betrays the hidden architecture of the subsurface. Singh employed a Schlumberger electrode configuration, progressively widening the current electrode spacing to a maximum half-spacing of 580 meters, which allowed the survey to penetrate to depths of roughly 150 meters. At each spacing, apparent resistivity was calculated using the standard geometric formula for the array, and readings were carefully checked, repeated, and filtered to remove noise from poor electrode contact, cultural interference, and instrumental drift.

Seventeen sounding stations were spread across an area of approximately 248 square kilometers, a region bounded by latitudes 28.96567 degrees north to 29.145667 degrees north and longitudes 79.946660 degrees east to 80.20056 degrees east. The geology here is a geological jigsaw. Massive granite gneiss and crystalline bedrock, severely weathered, fractured, and jointed by millions of years of tectonic activity, sit alongside the Siwalik and post-Siwalik sedimentary successions, Doon Gravels, and Quaternary alluvial deposits. The Main Boundary Fault, one of the great tectonic discontinuities of the Himalaya, cuts through the region, separating the Lesser Himalaya from the Sub-Himalaya. This structural complexity means that groundwater does not behave in predictable, uniform ways: it accumulates along thrust planes, synclinal folds, tensile joints, and fault surfaces, and its productivity can change dramatically from one village to the next.

The raw resistivity curves were interpreted using both manual curve-matching against theoretical master curves and computer-based inversion with the IX1Dv3.1 and IPI2win software packages. Initial model parameters were guided by field curve characteristics and available geological data, then refined iteratively until the calculated and observed curves agreed satisfactorily, with root-mean-square error values used to assess convergence. The resulting models revealed between six and nine distinct layers at each of the 17 sites. Crucially, these geoelectrical layers were calibrated against lithological logs from nearby wells, with alluvium, gravel, weathered and fractured zones, clay horizons, and compact bedrock each showing characteristic resistivity signatures. Low to moderate resistivity values typically pointed to saturated weathered or alluvial formations, while high-resistivity zones indicated compact, less-fractured bedrock with little room for water storage.

The numbers that emerged paint a vivid picture of the region’s water wealth. Aquifer thickness across the study area varies from 13.12 to 118.65 meters, with an average of 52.12 meters. Aquifer depth ranges from 29.84 to 142.27 meters, averaging 87.62 meters, with the deepest aquifer found at VES6 near Chandani village and the shallowest at VES17 near Banbasa. Aquifer resistivity values span 42.34 to 187.04 ohm-meters, averaging 111.65 ohm-meters. Most strikingly, of the 17 locations surveyed, 14 turned out to host promising groundwater zones, a remarkably high success rate that underscores how much exploitable water lies hidden even in seemingly hostile hard-rock terrain.

The spatial patterns are just as revealing as the averages. Thicker aquifer zones cluster in the northeastern, northwestern, and central parts of the study area, where thick weathered and fractured horizons within phyllites, quartzites, schists, and metabasaltic rocks offer enhanced storage and transmissive capacity. The middle of the study area hosts the single thickest aquifer, making it a particularly promising zone for development. Low-resistivity aquifers below 50 ohm-meters, represented primarily by station VES15, correspond to highly weathered and fractured rocks with strong groundwater saturation, while moderate values of 50 to 100 ohm-meters at five stations indicate weathered formations with moderate potential. Higher values between 100 and 200 ohm-meters at seven stations are associated with fractured granite, quartzite, phyllites, and sandy deposits that still hold moderate to good groundwater potential.

To visualize these patterns in three dimensions, Singh used ordinary kriging interpolation in Surfer software to produce continuous contour maps and 3D models of aquifer resistivity, thickness, and depth, while RockWorks 16 software generated geoelectrical and lithological fence diagrams showing the geographic distribution of underlying formations. Litho-resistivity cross-sections along two profiles, trending northwest to southeast, revealed how the subsurface changes laterally. The northwestern portion is dominated by compact phyllite, granite, and chlorite-schist formations with resistivity values exceeding 500 ohm-meters extending to depths of about 130 meters, indicating relatively unweathered hard rock. In contrast, the central and northeastern sectors show low-resistivity zones at depth, corresponding to weathered and fractured rocks where water has percolated into the broken fabric of the crust.

The study is candid about its uncertainties, and this honesty strengthens rather than weakens its conclusions. Resistivity interpretation in heterogeneous geological settings is inherently non-unique: porosity, saturation, clay content, fracture density, weathering severity, and pore-water chemistry all influence electrical response, so a single resistivity value can have multiple geological explanations. High resistivity might mean dry compact rock, or it might indicate fractured hard rock with localized water. Low resistivity might signal a water-saturated formation, or an impermeable clay layer. The pseudo-sections presented in the paper are interpolations of one-dimensional interpretations rather than true two-dimensional inversions, and the author cautions that they should be read alongside geological, geomorphological, and hydrogeological data to avoid overinterpreting apparent continuity. The limited number of 17 stations, dictated by challenging mountainous terrain, and the absence of comprehensive pumping test and hydrochemical data also constrain the resolution of the models.

Despite these caveats, the practical implications for the region are significant. The southern Bhabar and piedmont zones, with their thick alluvial deposits, favorable geomorphology, and recharge from both rainfall and the Sharda (Mahakali) River system, show relatively higher groundwater potential than the northern Himalayan foothill sectors. For borewell development, the study recommends prioritizing low-to-moderate-resistivity weathered and fractured zones, especially where aquifer sections are thickest. In areas with moderate slopes and high runoff, artificial recharge techniques such as check dams, recharge pits, and percolation tanks are advised, and time-lapse resistivity surveys combined with seasonal groundwater monitoring could track how aquifers respond over time. Hand pumps in the region currently show pre-monsoon water tables between 5.48 and 32.28 meters below ground level, with seasonal fluctuations of 0.85 to 1.22 meters, while exploratory wells at Tanakpur and Chandni discharge 2,683 and 3,100 liters per minute respectively, with transmissivity ranging from 7,484 to 14,140 square meters per day.

In an era when aquifers worldwide are being drawn down faster than they can replenish, studies like this one demonstrate that the first step toward sustainability is simply knowing where the water is. By translating faint electrical whispers from deep underground into quantitative maps of aquifer geometry, the Tanakpur survey provides exactly that foundation for a corner of the Himalayan foothills where every liter counts. The integrated VES-based framework, the author argues, offers an efficient and scientifically sound approach for groundwater exploration and management in data-poor hard-rock and alluvial terrains, and future work incorporating borehole, hydrochemical, and pumping test data will sharpen its predictive power further. For the communities of Champawat district, the message from beneath their feet is encouraging: the water is there, hidden in fractured stone and ancient gravels, waiting to be found and, above all, carefully managed.

Subject of Research: Geophysical characterization of groundwater aquifers in the Himalayan foothills using vertical electrical sounding

Article Title: Geophysical insights into aquifer characteristics of the Tanakpur area in Champawat district, Uttarakhand, India

Article References: Singh, S. (2026). Geophysical insights into aquifer characteristics of the Tanakpur area in Champawat district, Uttarakhand, India. Discover Geoscience, 4(1), Article 303. https://doi.org/10.1007/s44288-026-00636-w

Image Credits: AI Generated

DOI: 10.1007/s44288-026-00636-w

Keywords: groundwater, aquifer, vertical electrical sounding, electrical resistivity, Himalayan foothills, Uttarakhand, hydrogeology, geophysics, Schlumberger array, hard rock terrain, water resources, Tanakpur

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

The work, published in the journal Scientific Drilling, describes a series of active seismic experiments carried out in the Ossola Valley in support of the International Continental Scientific Drilling Program project known as DIVE, short for Drilling the Ivrea–Verbano zonE. Led by Andrew Greenwood of the University of Lausanne and Montanuniversität Leoben, together with colleagues from Switzerland, Italy, and Austria, the campaign was designed to characterize the subsurface at two proposed borehole sites, one near the town of Ornavasso and another at Megolo di Mezzo. The planned boreholes, each roughly one kilometer long, will penetrate the upper reaches of the lower continental crust, a zone that normally lies hidden many tens of kilometers beneath our feet.

The scientific stakes are considerable. Drilling is the only way to recover continuous fresh rock cores from the deepest, non-exposed portions of the Ivrea crustal section, and the DIVE project aims to answer long-standing questions about the composition, structure, and physical and chemical properties of the lower continental crust. The project also intends to explore potential microbiological niches in these deep rocks, probing for life in one of the planet’s most extreme rock environments. Phase I of DIVE targets two complementary sections of the lower crust, while a future phase II in the neighboring Sesia Valley aims even higher, with plans to drill through the crust–mantle boundary itself, the Moho.

Before any of that could happen, the team needed to know exactly what lies beneath the valley floor. Surface geology is mapped in exquisite detail in the Ivrea–Verbano zone, and the steep topography allows some downward extrapolation of structures, but the researchers needed to bridge a stubborn gap in scale between regional geophysical images, which resolve features on the scale of kilometers, and the centimeter-to-meter scale information that borehole instruments will eventually provide. Active seismic reflection surveying, in which a controlled seismic source sends waves into the ground and geophones record the echoes that bounce back from subsurface layer boundaries, was the tool of choice.

Conducting the surveys, under the project name MicrO-SEIZE, was no simple matter. The Ossola Valley is a deep glacial valley flanked by steep mountain slopes inclined at roughly 25 to 30 degrees and cloaked in dense vegetation. The valley floor hosts pastures, the Toce River, major roads, railways, and water canals, all of which constrain where instruments could be placed and all of which generate anthropogenic noise that contaminates seismic recordings. Over 12 days in June 2019, the team deployed a 12,247-kilogram EnviroVibe vibrator truck, sweeping frequencies from 12.5 to 150 hertz over 12 seconds at each source point. Geophones with a resonant frequency of 15 hertz were planted along roads, disused highways, and open fields, connected to cabled acquisition systems totaling hundreds of channels.

To cope with the complex, steeply dipping geology, the team employed a crossed-array method, combining a central receiver line oriented across the strike of the target structures with shorter orthogonal crosslines. This arrangement provided sparse three-dimensional coverage and allowed the researchers to capture reflections dipping obliquely to the main profile. Where sources and receivers were closely co-located, the seismic fold, a measure of how many independent measurements contribute to each image point, reached values as high as 70, and up to 195 at the center of the Ornavasso primary profile. A supplementary ultra-high-resolution survey, dubbed nanO-SEIZE, used a 35-kilogram portable vibrator and geophones spaced just 1.5 meters apart to characterize the immediate vicinity of the Ornavasso drill site right up to an adjoining cliff face.

The processing chain was rigorous and iterative. After vibroseis correlation, trace editing, filtering, deconvolution, and velocity analysis, the team built site-specific velocity models for each profile. Refraction analysis of first-arrival times revealed a simple two-layer near-surface structure: a thin veneer of dry sediments, only about 5 to 10 meters thick, overlying water-saturated sediments with an average velocity of 1,520 meters per second. Constant-velocity stack tests refined the stacking velocities, and a velocity gradient of 0.00167 per meter proved capable of coherently imaging horizontal reflectors down to roughly 500 meters. For the Megolo profile, which runs nearly parallel to the valley walls and to the dipping rock fabric, the team went further and constructed a full three-dimensional velocity model, using a representative metagabbro velocity of 7,000 meters per second derived from field samples and published laboratory measurements.

The results delivered a striking picture of the valley itself. Along the transect running from Premosello–Chiovenda toward Megolo, the seismic sections revealed a wide, U-shaped glacial valley carved into crystalline bedrock, with the trough centered beneath the middle of the Ossola Valley. The base of the Quaternary glacial and glacioflacial sediments sits at approximately 550 meters depth, equivalent to about 300 meters below sea level. Within the sedimentary fill, the reflectors are far from simple: irregular, onlapping layering points to thick proglacial lake sediments preserved from older glacial cycles, along with evidence of paleochannels left behind as the Toce River meandered across the valley floor. At the two drill sites themselves, the sedimentary overburden was found to be up to 50 meters thick, and the surveys prompted a practical adjustment: the Ornavasso borehole location has been moved roughly 20 meters closer to an exposed bedrock cliff to minimize the amount of soft sediment the drill must pass through and to better target the axis of the tightly folded Massone Antiform.

Equally important was what the surveys revealed about the drilling targets themselves. At Megolo, where an inclined borehole is planned to cross the flank of the broad Proman Anticline, the seismic data confirmed the east-southeast dip of the metagabbroic rocks at roughly 20 degrees and guided the planned borehole inclination of 15 to 20 degrees from vertical, ensuring the hole will cross the rock layering as orthogonally as possible and reach the deepest structural levels achievable. At Ornavasso, the target is the hinge of the narrow Massone Antiform, and a near-vertical borehole is planned. Critically, the surveys found no evidence of major geological drilling hazards: no shallow-dipping reflectors indicative of large open-fracture systems, fault zones, or cataclastic zones were observed in the crystalline basement at either site, although the geometry of the surveys means that steeply inclined faults cannot be entirely excluded.

The surveys also exposed a fundamental challenge of imaging crystalline terrains. The Ivrea lower crustal rocks have very low acoustic impedance contrasts between conformable layers, with reflection coefficients below 0.05, so the basement rocks return almost no coherent specular reflections. Only the gently dipping fabric of the Proman Anticline, where the target rocks lie close to the surface, could be directly imaged. Elsewhere, the team relied on secondary indicators such as diffraction tails from steeply dipping irregular surfaces and sharp terminations. With the borehole geometries now determined and agreed upon, drilling can proceed, and the seismic database will serve as an essential reference for interpreting the forthcoming borehole logging results, complemented by two years of passive seismic monitoring from the DIVEnet network of 12 stations surrounding the sites. What began as a practical site-characterization exercise has thus produced a detailed portrait of a glacial valley and its hidden bedrock, setting the stage for humanity’s closest look yet at the deep roots of the continents.

Subject of Research: Active seismic characterization of drilling targets in the Ivrea–Verbano zone for the ICDP DIVE continental drilling project

Article Title: Active seismic surveys for drilling target characterization in Ossola Valley: International Continental Scientific Drilling Program (ICDP) project Drilling the Ivrea–Verbano zonE (DIVE) phase I

Article References: Greenwood, A., Hetényi, G., Baron, L., Zanetti, A., Müntener, O., & the MOS field team (2024). Active seismic surveys for drilling target characterization in Ossola Valley: International Continental Scientific Drilling Program (ICDP) project Drilling the Ivrea–Verbano zonE (DIVE) phase I. Scientific Drilling, 33(2), 219-236. https://doi.org/10.5194/sd-33-219-2024

Image Credits: AI Generated

DOI: 10.5194/sd-33-219-2024

Keywords: Ivrea–Verbano zone, scientific drilling, ICDP, seismic reflection, lower continental crust, Ossola Valley, DIVE project, glacial sediments, Moho, geophysics, borehole characterization, Western Alps

The central challenge the researchers tackled is one of access. Soil microorganisms and the organic matter they decompose are distributed unevenly through a labyrinthine pore network, and only a small fraction of soil microbes can move under their own power. Most bacterial decomposition therefore relies on diffusion: organic molecules must drift through water films to reach the microbes or their extracellular enzymes. Because diffusion only happens in water, the connectivity of the aqueous phase becomes the master variable. As a soil dries, water retreats into progressively thinner and more disconnected films, forcing substrates to travel ever more tortuous paths, and respiration declines sharply.

What makes the new work clever is the recognition that electricity faces exactly the same physical constraints. When a voltage is applied across a soil, charge carriers, mostly dissolved ions, must move through the same water-filled pore network that substrates use. If drying breaks the continuity of the water phase, both ionic conduction and substrate diffusion suffer. The team hypothesized that electrical conductivity, measured across a range of soil moisture conditions, could therefore act as a mechanistically informed proxy for respiration whenever microbial activity is limited by diffusion rather than by the sheer amount of carbon available.

To test this idea, the researchers collected soil from the long-term La Cage field experiment at the INRAE campus in Versailles, France, established in 1998 on a well-drained Luvisol. They compared two contrasting management systems: conventional tillage, with annual ploughing to 30 centimeters, and conservation agriculture, which leaves the soil untilled under persistent cover crops. From each system they took both sieved topsoil and subsoil samples, homogenized to two millimeters, and undisturbed cores collected in PVC rings that preserved the natural pore architecture. The samples were frozen, thawed gradually, saturated by capillary rise, and placed in airtight microcosms fitted with ceramic plates connected to a suction pump.

By applying matric potentials ranging from −70 to −630 hectopascals, and a final step near −996 hectopascals using an oversaturated lithium chloride solution, the team could dry the samples in controlled increments without physically disturbing them. At each moisture level they measured carbon dioxide accumulation in the microcosm headspace with a micro gas chromatograph, calculating respiration flux per gram of organic matter, while simultaneously recording the real part of the complex electrical conductivity at one hertz using a portable spectral induced polarization unit and custom brass-screw electrodes. Water retention curves fitted with the van Genuchten model converted each applied suction into an equivalent water saturation for every sample.

The results revealed a striking and mechanistically coherent picture. Relative respiration rates, normalized to the wettest condition, rose by roughly three orders of magnitude as the soils dried from −996 to −70 hectopascals, but the response was not monotonic. Undisturbed samples showed a distinct respiration peak at −250 hectopascals, beyond which further wetting brought no additional increase. The researchers attribute this plateau to oxygen limitation: near saturation, oxygen, which diffuses far more slowly through water than through air, becomes the bottleneck, even as substrate diffusion is at its easiest. There is, in effect, an optimal moisture window where oxygen supply and substrate connectivity are balanced.

Electrical conductivity, by contrast, declined systematically as the soils desaturated, exactly as expected from the progressive loss of connectivity in the conductive water phase. Fitting the bulk conductivity data with the Waxman-Smits pedophysical relationship allowed the team to derive a tortuosity factor for the water phase in each sample, a quantitative measure of how winding and constrained the diffusive pathways had become. Tortuosity increased steadily with drying in every soil, and when the researchers plotted log-transformed respiration flux against log-transformed tortuosity within the diffusion-limited range, they found significant negative relationships in both the conventionally tilled and conservation agriculture samples. The drier and more tortuous the water phase, the slower the microbes respired.

The influence of soil structure emerged in a subtle but important way. In the conventionally tilled samples, the slope of the respiration-tortuosity relationship was significantly steeper for sieved soils than for undisturbed ones, suggesting that homogenized pore networks make respiration more sensitive to diffusive constraints. Sieving also raised respiration rates near saturation, likely because breaking aggregates exposes physically protected organic carbon to microbial attack. In the conservation agriculture samples, whose long-term aggregate stability is known to be greater, no such structural modulation appeared, hinting that stable aggregation may buffer biological responses to changes in tortuosity. Notably, the tortuosity values themselves did not differ significantly between structural treatments, revealing a decoupling between bulk transport metrics and biological response that the authors argue deserves further attention.

The broader implications are considerable. Carbon models routinely represent the moisture dependence of soil respiration with empirical curves, but this study points toward a physically grounded alternative: if electrical conductivity tracks the connectivity of the aqueous phase, then geophysical sensors already used to map soil moisture in the field could, in principle, deliver quantitative information about diffusion-limited microbial activity without disturbing the soil at all. The authors are careful to note that the approach applies in the absence of substantial water flow, that near-saturated conditions fall outside its scope because of oxygen limitation, and that one anomalous conductivity increase in a tilled subsoil sample, possibly linked to fungal growth on the core surface, remains unexplained. Field validation is the clear next step. Still, the prospect is tantalizing: a routine electrical measurement, of the kind that can be made with electrodes and a modest instrument, may one day tell us how fast the largest terrestrial carbon reservoir is breathing, pore by tortuous pore, as the planet warms and dries.

Subject of Research: Using electrical conductivity as a proxy for diffusion-limited microbial respiration in soils

Article Title: Electrical conductivity measurements as proxies for diffusion-limited microbial activity in soils under controlled laboratory conditions

Article References: Fülöp, O., Nunan, N., Gueye, M., & Jougnot, D. (2026). Electrical conductivity measurements as proxies for diffusion-limited microbial activity in soils under controlled laboratory conditions. SOIL, 12(1), 703-714. https://doi.org/10.5194/soil-12-703-2026

Image Credits: AI Generated

DOI: 10.5194/soil-12-703-2026

Keywords: soil respiration, electrical conductivity, geophysics, microbial activity, carbon cycle, diffusion limitation, tortuosity, soil moisture, soil structure, conservation agriculture, Luvisol, pedophysics

The team’s answer matters because the stakes of seismic inversion extend far beyond academic curiosity. The three elastic parameters at issue — P-wave velocity, S-wave velocity, and density — are the raw ingredients from which geophysicists derive indicators of fluid content, porosity, and hydrocarbon saturation. Traditional deterministic inversion methods, such as least-squares approaches, deliver a single best-fitting model but say little about how confident one should be in it. Bayesian inference offers a different philosophy: instead of one answer, it produces an entire probability distribution over plausible underground models, blending prior geological knowledge with the information contained in the seismic data itself. The catch is that this posterior distribution cannot be written down analytically for realistic problems, so researchers must sample from it using Markov Chain Monte Carlo methods — and the choice of sampler shapes both the quality of the answer and the size of the computing bill.

The four contenders in this statistical showdown represent distinct generations of sampling technology. The oldest and simplest is the Metropolis-Hastings algorithm, developed in the 1950s and 1970s, which explores the model space by random walks: it proposes a random perturbation of the current model and accepts or rejects it according to a probability ratio. It requires no gradient calculations, making it cheap per step, but in high-dimensional spaces its drunken-wander behavior means samples are highly correlated and convergence is slow. At the other extreme sits Hamiltonian Monte Carlo, borrowed from molecular dynamics, which endows each model with an auxiliary momentum variable and simulates frictionless motion across an energy landscape defined by the negative logarithm of the posterior. By following the gradient of that landscape, HMC proposes bold, physically informed moves that traverse the parameter space far more efficiently — provided the gradients are computed correctly and the step sizes are tuned with care.

Between these poles lie two Langevin-based methods rooted in the mathematics of Brownian motion, the theory Paul Langevin formulated in 1908 as a simplification of Einstein’s treatment of jittering particles. The Metropolis-Adjusted Langevin Algorithm, or MALA, discretizes a stochastic differential equation whose drift term pulls each proposal toward regions of higher posterior probability, then applies a Metropolis acceptance step to remove discretization bias. Its newer variant, Lip-MALA, goes further: it adapts the step length at every iteration according to a Lipschitz condition, automatically shrinking steps where the posterior landscape changes abruptly and enlarging them where it is smooth. This dynamic tuning, the authors note, improves stability and mixing in the high-dimensional posteriors that seismic inversion generates, where the number of unknowns scales with the number of layers in the model.

The forward physics connecting models to data is the Aki-Richards approximation, the workhorse equation of amplitude-versus-offset analysis that emerged in the early 1980s. It expresses the reflection coefficient at each rock interface as a linearized function of the contrasts in P-wave velocity, S-wave velocity, and density, weighted by angle-dependent coefficients. The researchers worked in a logarithmic parameterization — inverting for the logarithms of the three elastic parameters — which guarantees physically sensible positive values and dovetails naturally with the structure of the Aki-Richards equations. Working at three incidence angles, they assembled a matrix operator that converts any candidate model into synthetic seismic traces, then measured how well those traces match the observed data through a Gaussian likelihood combined with a Gaussian prior built from well logs and low-frequency velocity models.

The first arena was a synthetic test: noise-free seismic traces generated from real well-log values at angles of 9, 18.5, and 27.5 degrees, with the true answer known in advance. Each algorithm ran a Markov chain of 10,000 accepted realizations after a burn-in period, and the team judged performance through posterior means, standard deviations, correlation coefficients, root-mean-square errors, acceptance rates, execution times, and a multivariate effective sample size diagnostic to confirm convergence. The results drew a clear dividing line. For velocity estimation, the three gradient-based methods all outperformed Metropolis-Hastings, with HMC achieving the highest correlation and the lowest error. For density, the picture inverted in an unexpected way: MH and HMC both struggled, with correlations below 0.29, while MALA and Lip-MALA delivered correlations above 0.60 and errors roughly a third smaller.

The computational ledger told an equally important story. Metropolis-Hastings was the fastest of the four, despite its statistical clumsiness, because each of its steps is so cheap. HMC was the slowest, its long Hamiltonian trajectories and repeated gradient evaluations exacting a heavy price in wall-clock time — and it also recorded the lowest acceptance rate. Lip-MALA, by contrast, posted the highest acceptance rate of all four algorithms, a sign that its adaptive step control consistently proposes moves the posterior is willing to accept. MALA ran quickly as well. The trade-off, in short, was stark: gradient information buys accuracy, but the bill arrives in computing hours.

Synthetic benchmarks, however, can flatter an algorithm. The decisive test came from real data: an oil field in eastern Venezuela’s Eastern Basin, where alternating sandstones and shales host brine and oil, and where partial-stack seismic traces at angles of 19, 24, and 29 degrees had to be tied to upscaled well logs — a correlation of 0.55 that reflects the messiness of field data. Here the same hierarchy largely held. Metropolis-Hastings again showed the weakest velocity correlations, while Lip-MALA achieved the highest and the lowest errors, and the Langevin pair again dominated density estimation, with correlations above 0.48 where MH and HMC fell below 0.28. The team then scaled the problem to two dimensions, inverting a grid of 351 time samples by 136 horizontal cells over a 340-meter span, using a prior model built from interpreted horizons and faults. In this more realistic setting, HMC redeemed itself: its long trajectories navigated the rougher, more heterogeneous posterior landscape better than local Langevin steps, producing the lowest posterior standard deviations for all three parameters — though at the highest computational cost, with Lip-MALA offering the best compromise between precision and efficiency.

The practical guidance that emerges is refreshingly concrete. When speed matters most — rapid screening of frontier areas with poor well control, or near-real-time decisions during drilling — Metropolis-Hastings or MALA remain defensible choices despite their statistical limitations. When fidelity is paramount, as in mature fields where drilling and production decisions hinge on accurate elastic properties, HMC earns its runtime, particularly in two-dimensional and higher-dimensional problems where its ability to traverse multi-basin posterior landscapes reduces global uncertainty. Lip-MALA stands out as the algorithm for practitioners who want gradient-informed accuracy without HMC’s price tag, and as the most reliable option for the stubborn problem of density estimation. The authors also offer a methodological caution: researchers should report both pointwise fit and uncertainty measures, because an algorithm that wins on one metric can lose on another, and choosing the wrong yardstick can make the best tool look like the worst.

Beyond the rankings, the study demonstrates something conceptually larger: that the full Bayesian machinery — priors, likelihoods, posterior sampling, and rigorous convergence diagnostics — can be carried from idealized synthetic exercises all the way to geologically complex field data, delivering not just pictures of the subsurface but honest probability distributions over what lies there. The framework is not locked to its simplifying assumptions of one-dimensional layered models and linearized reflectivity; the authors point out that more sophisticated forward modeling and petrophysical relationships can be slotted into the same statistical skeleton. As exploration moves into ever more challenging terrain, and as computing resources grow, the quiet contest between random walks, Hamiltonian trajectories, and Langevin diffusion may well determine how clearly the industry can see what it is drilling toward.

Subject of Research: Comparison of Markov Chain Monte Carlo algorithms for Bayesian prestack seismic inversion of elastic properties

Article Title: Bayesian inference based on algorithms: MH, HMC, MALA and Lip-MALA for prestack seismic inversion

Article References: Perez-Roa, R., Infante, S., Barragan, G., & Manzanilla, R. (2026). Bayesian inference based on algorithms: MH, HMC, MALA and Lip-MALA for prestack seismic inversion. Nonlinear Processes in Geophysics, 33(2), 173-195. https://doi.org/10.5194/npg-33-173-2026

Image Credits: AI Generated

DOI: 10.5194/npg-33-173-2026

Keywords: seismic inversion, Bayesian inference, Markov Chain Monte Carlo, Metropolis-Hastings, Hamiltonian Monte Carlo, MALA, Lip-MALA, AVO, elastic properties, reservoir characterization, Venezuela, geophysics