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Steep geological structures are critical for improved understanding of tectonic processes and fluid circulation, particularly in crystalline settings. However, accurately determining their geometry at depth remains a challenge for conventional 2D surveys. In this study, we present an automated three-dimensional (3D) reflection traveltime modelling approach to estimate 3D subsurface geometries of dipping reflectors. The method utilises the traveltime hyperboloid equation adapted for dipping reflected events. The required inputs include the acquisition geometry, the known location where the dipping layer intersects or projects to the surface, pre-stack gathers, first-break picks and reflection hyperbola picks. The traveltime equation is modified and adapted to incorporate common available information from seismic acquisitions, and the resulting function is analysed to optimise the input parameters. The study also highlights the sinusoidal behaviour of the objective function and demonstrates the importance of multi-azimuth acquisitions in constraining the possible reflector geometries. The output consists of a root mean square (RMS) error map for all modelled dip-strike pairs relative to the picked reflection traveltime, the best-fitting reflector geometry and its corresponding modelled reflection traveltime. If desired, the best-fitting reflector can also be modelled in the migrated stacked section for comparison purposes. Compared to traditional manual techniques, the proposed method improves accuracy, reduces the operator dependency and provides quantitative reliability metrics. Owing to its simplicity and application efficiency, this method can be largely applied in onshore reflection seismic data interpretations, where 2D crooked profiles commonly provide multi-azimuth coverage, enabling improved delineation of steep structures such as faults and dykes.

As the mining industry shifts toward more responsible and lower-impact practices, mine tailings are increasingly regarded as a secondary resource that can be sourced into the raw-material supply chain. However, limited knowledge of subsurface geometry at many historical tailings sites leads to uncertainties in volume and resource estimates. High-resolution seismic imaging can provide improved characterization of such sites. Here, we present the results of a seismic survey conducted in 2024 on tailings at Bl & ouml;tberget in central Sweden. The data were acquired using a combined, partly collocated setup consisting of a sparse 3D nodal array, a landstreamer and distributed acoustic sensing (DAS) systems. The objective was to characterize the tailings and to optimize the acquisition and processing strategies for our application. Through 2D reflection seismic imaging, layer-based refraction travel-time modelling and travel-time tomography, we obtain well-constrained P-wave velocities for the tailings on the order of 300-350 m/s. Additional 3D travel-time modelling yielded volumetric estimates, from which we estimate a total tailings tonnage of approximately 4 Mt. Finally, we demonstrate that surface DAS can serve as a complementary recording system, capable of delineating the tailings when fibre cable-ground coupling conditions are favourable. The survey serves as a pilot for future mine tailings investigations and related near-surface characterization efforts, and we highlight the benefits of using multi-element seismic recording arrays for such purposes.

Subtle faults and discontinuities are often poorly resolved in conventional reflection seismic imaging but can influence reservoir integrity and fluid pathways in geological carbon storage sites. At Thorning, a salt pillow is overlain by a deformed overburden including the Upper Triassic Gassum Formation, the primary CO2 storage target. Two orthogonal seismic profiles image a fault system along the southwestern margin of the reservoir structural closure. Seismic data were prepared for depth and diffraction imaging by projecting source-receiver coordinates onto locally defined migration lines to satisfy the 2D assumption. A detailed interval velocity model was iteratively constructed, followed by 2D prestack Kirchhoff depth migration. Diffraction imaging using specularity analysis suppressed reflections while retaining diffracted energy. Specularity taper settings assessed robustness, and sharp survey-line turns were carefully handled to avoid false responses. The resulting diffraction images reveal a set of small-scale structures some of which are generated by minor faults and discontinuities.

Surface fibre-optic distributed acoustic sensing (S-DAS) typically requires trenching to achieve adequate coupling, which can be challenging and costly in hardrock environments. As an alternative, untrenched S-DAS offers significant time and cost savings, though at the expense of data quality. In this study, we systematically evaluated the impact of untrenched deployment on DAS data quality through a multimethod comparison with conventional sensors, including three-component geophones and vertical-component accelerometers. All recorded data were converted to particle velocity to enable direct amplitude comparisons across arrays. Phase fidelity was assessed using the surface-wave method, cross-power spectral analysis and ambient noise interferometry. Untrenched S-DAS recorded amplitude levels that differed from those of conventional sensors, particularly above 50 Hz. However, within the surface-wave band (up to 35 Hz), the data quality was sufficient to derive reliable shear-wave velocity profiles, especially when the data were resorted to common-receiver gathers. Sensitivity and coherence decreased significantly at higher frequencies and larger offsets, and a systematic time delay was observed for DAS in the surface-wave band. Ambient noise interferometry was ineffective for the untrenched DAS array, largely due to variable channel coupling and system-specific noise. This study provides a systematic field comparison of untrenched S-DAS and conventional sensors in hardrock settings, outlining both the limitations and the practical potential of this cost-effective deployment method.

A 2D-pseudo-3D reflection seismic survey is planned for imaging a mafic-ultramafic magmatic system, which hosts Ni-Cu mineralisation, southwest of Sala in the Bergslagen region, central Sweden. The study focuses on the greenfield Granmuren mineralisation, a steeply plunging sulphide-rich body, which remains poorly constrained due to limited high-resolution subsurface data. New geological observations, petrophysical measurements, and gravity data demonstrate that the mafic intrusions hosting the mineralisation provide ample contrast from the surrounding lithologies to have a strong seismic response. Building on these data and experience from similar hard-rock seismic studies, a survey layout combining long-offset 2D profiles with a sparse 3D configuration has been developed to image large-scale structures and the geometry of the mafic-ultramafic intrusions. Analyses of offset, azimuthal coverage, and fold indicate that the planned acquisition provides suitable conditions for imaging steeply-dipping intrusions and deformation zones. The study further highlights the benefits of leveraging sparse 3D seismic data approaches, as opposed to only 2D surveys, to improve subsurface imaging in hard-rock settings and support future exploration and resource evaluation.

The Petra morphological depression on Lesvos Island hosts one of Greece's most promising low- to intermediateenthalpy geothermal prospects, yet its internal structure and fluid pathways remain poorly constrained. To improve the characterization of the geothermal system, an integrated geophysical survey combining seismic, gravity, and magnetic methods was conducted in 2024 to delineate basin geometry and identify fault and fracture zones with enhanced permeability. Reflection seismic data were processed to image subsurface structure, while point-diffraction modelling was applied to constrain migration velocities and distinguish structural discontinuities from faults and small-scale intrusive bodies. First-break traveltime tomography provided complementary constraints on fault geometry and on the thickness of fresh volcanic units (Upper Lava), and residual gravity data were used to resolve lateral density variations. The integrated interpretation reveals a fault-bounded depression filled with low-density, low-velocity Upper Lava overlying higher-velocity, higher-density Lower Lava. Two major sets of steeply dipping faults define the Petra depression; minor and intersected faults are considered as conduits that enhance permeability and promote hydrothermal circulation. The Petra depression is interpreted as a small transtensional pull-apart basin that localizes geothermal fluid flow along its major fault zones. From a geothermal perspective, these results reduce structural uncertainty and highlight two domains along the northern and southern bounding faults as the most promising targets for future geothermal drilling.

The success of seismic depth imaging in sedimentary basins affected by salt tectonics depends as much on the illumination of complex geological targets as on our ability to transform mere data into images that we consider to be an accurate structural description of the Earth. Achieving this level of precision on land is by no means simple. This study presents a tailored depth imaging workflow that combines novel landstreamer and nodal 2D seismic data sets acquired for geological carbon storage site investigations above the Thorning salt pillow in Denmark. The dual-element configuration provides dense near-offset coverage alongside long-offset recordings, thereby enhancing the resolution of the shallow velocity field and improving illumination of both near-surface and deeper reflectors. The combined processing workflow addresses differences in geometry, amplitude, phase, and statics between the two data sets. Early-stage merging of these data sets transforms the two partial views into a single, unified image, thereby providing the basis for PSDM (prestack depth migration) of the combined data. The resulting depth image delineates a fault system along the southwestern margin of the Gassum Formation reservoir and deformed suprasalt strata with high resolution. Subtle structural discontinuities are identified in the overburden, and Quaternary paleovalleys are observed in the shallow subsurface, with implications for seal integrity and groundwater systems. The combined data enable improved velocity model building and enhanced imaging of key geological boundaries and structures from the shallow subsurface to depths exceeding 5 km. These findings demonstrate the potential of combining dual-element land data and tailored processing workflows for high-resolution imaging in structurally complex onshore environments.

In carbon capture and storage (CCS) projects, it is important to investigate the seal properties, which often include the shallower part of the investigated area. Reflection seismic data in most of the Danish Basin appear less strong and coherent in the top 500 m, and hence reflectivity alone cannot be used to study the integrity of these potential CCS reservoirs. This study seeks to bolster and connect near-surface with deeper reflection seismic data by leveraging the capabilities of seismic traveltime tomography and other elements of seismic data. By exploiting the advantages of high-resolution, large offset data acquisition, the traveltime tomography method was adopted for detailed structural characterization of the Quaternary sediments and the Chalk Group in the Central Jutland region, Denmark. Specifically, a focus on the potential for CO2 capture and storage in this area is pursued by constructing accurate velocity models and integrating them into reflection data processing. Our study aims to enhance reflection images and correlate them with the traveltime tomographic results for an updated geological interpretation of the area. The subsequent findings demonstrate the effectiveness of the tomography method with major improvements in the reflection seismic sections that provide additional features for improved large-scale geological mapping. The combined integration of the tomography and reflection seismic sections reveals that salt tectonics influence the region's topography. Adaptation of different velocity models shows significant alterations in the seismic imaging of the area that should be taken into consideration regarding the site's capture and storage potential.

High-resolution seismic data are essential for interpreting thin-layered stratigraphy and subtle structures within hardrock media, as this information can lead to better exploration decisions in the mining sector. Conventional resolution enhancement techniques, such as spectral broadening and supervised deep-learning techniques, often rely on oversimplified assumptions or require high-resolution training labels. These limitations restrict their applicability in real seismic data processing, especially for hardrock seismic data, which are typically characterized by high velocities, strong heterogeneity and short reflector continuity due to complex emplacement contacts and geological settings. We propose an unsupervised seismic resolution enhancement framework that integrates physics-guided and attention-based mechanisms. The framework is designed to address the progressive loss of high-frequency information in seismic exploration and the limitations of conventional resolution enhancement methods, which struggle to balance imaging fidelity with geological interpretability. The proposed network incorporates coordinate attention blocks and the lightweight Vision Transformer, enabling more effective capture of spatial dependencies and long-range significant features in complex geological settings. Specifically, our approach utilizes a physics-constrained deconvolutional loss function, where the predicted reflectivity is regularized by an adaptive sparsity prior and convolved with a wavelet to synthesize seismic traces that are consistent with the observed data. In addition, a robust Charbonnier penalty ensures stable physical fitting, while anisotropic total variation regularization improves lateral continuity. Following this design, the model achieves end-to-end recovery of high-resolution seismic information without requiring high-resolution labels, thereby explicitly embedding physical constraints into the learning process. Testing results on synthetic and field datasets from two different regions demonstrate that the proposed method significantly enhances vertical resolution, reflector sharpness and lateral continuity, enabling more precise delineation of subtle stratigraphic features within the target intervals. Compared with spectral enhancement and conventional deep-learning methods, our approach achieves higher seismic reconstruction fidelity and more interpretable reflectivity, providing an option that combines robustness with interpretability for high-resolution imaging in complex geological conditions.

Characterizing near-surface fault architecture and structural framework is critical for geological carbon storage (GCS) sites, as it directly influences storage maturation, integrity, and associated risks. Building on earlier interpretations, this study revisits the Gassum domal structure, a potential GCS site in eastern Jutland, Denmark, using seismic data acquired in 2023. The main aim is to address primary risk zones and delineate structural features that were previously not delineated. We applied spectral decomposition and red-green-blue (RGB) co-rendering to migrated reflection seismic sections to improve the imaging of faults and weakness zones. Spectrally decomposed attributes were further combined with first-break traveltime tomography to derive tuning thickness, providing a first-order approximation of layer thicknesses. This approach revealed detailed and complex fault architecture, including internal faulting within the near-surface secondary seal, the Chalk Group. The highest fault densities occur at the dome crest and within the spill-point zone; two areas critical for CO₂ leakage. Our results indicate that the Gassum structure poses structural risk and must be carefully studied for its fault network integrity to ensure long-term CO₂ storage without significant de-risking.