Search Results (124)

The Eocene fourth member of the Shahejie formation (Es4x) in the Bonan Depression, Bohai Bay Basin, records syn-rift sedimentation under alternating arid and humid climates. It provides insight into how orbital-scale climatic fluctuations influenced tectonics, facies patterns, and reservoir distribution. This study integrates 406 m of core data, 92 thin sections, 450 km² of 3D seismic data, and multiple geochemical proxies, leading to the recognition of five facies associations (LFA): (1) alluvial fans, (2) braided rivers, (3) floodplain mudstones, (4) fan deltas, and (5) saline lacustrine evaporites. Three major depositional cycles are defined within the Es4x. Seismic reflections, well-log patterns, and thickness trends suggest that these cycles represent fourth-order lake-level fluctuations (0.8–1.1 Myr) rather than short 21-kyr precession rhythms. This implies long-term climate and tectonic modulation, likely linked to eccentricity-scale monsoon variability. Hyperarid phases are marked by Sr/Ba > 4, δ¹⁸O > +4‰, and thick evaporite accumulations. In contrast, Sr/Ba < 1 and δ¹⁸O < −8‰ reflect humid conditions with larger lakes and enhanced fluvial input. During wet periods, rivers produced sand bodies nearly 40 times thicker than in dry intervals. Reservoir quality is highest in braided-river sandstones (LFA 2) with 12%–19% porosity, preserved by chlorite coatings that limit quartz cement. Fan-delta sands (LFA 4) have <8% porosity due to calcite cementation, though fractures (10–50 mm) improve permeability. Floodplain mudstones (LFA 3) and evaporites (LFA 5) act as seals. This work presents a predictive depositional and reservoir model for arid–humid rift systems and highlights braided-river targets as promising exploration zones in climate-sensitive basins worldwide. Full article

Antarctic ice shelves regulate ice-sheet discharge and global sea-level rise, yet their rapid retreat underscores the need for new, low-cost monitoring tools. We analyze ambient seismic noise recorded by seismometers on the Pine Island Glacier ice shelf to characterize wind-induced signals and detect persistent structural resonances. Power spectral analysis shows that wind sensitivity is strongly damped compared with bedrock sites: noise increases only 5–7 dB from 0 to 25 m s⁻¹ winds, versus a 42 dB increase at an inland bedrock station, reflecting the contrasted coupling environments of floating and grounded substrates. The horizontal-to-vertical spectral ratio (HVSR) spectrograms reveal two temporally stable peaks at ~2.2 Hz and ~4.3 Hz that persist across stations and remain independent of environmental forcing. Forward modeling indicates that these peaks correspond to S-wave resonances within the ice shelf. The inferred ice-water interface depth (~440 m) agrees with the Bedmap2 thickness estimate (466 m). This work demonstrates that HVSR provides an effective passive, single-station method for measuring ice shelf thickness. Full article

Tunnel seismic advanced prediction is a widely used technique in geotechnical engineering due to its non-destructive characteristics and deep detection capability. However, limitations in acquisition space and complex on-site conditions often result in missing traces, damaged channels, and low-resolution data, thereby hindering accurate geological interpretation. Although deep learning models such as U-Net have shown promise in seismic data reconstruction, their emphasis on local features and fixed parameter configurations limits their capacity to capture global and long-range dependencies, thereby constraining reconstruction accuracy. To address these challenges, this study proposes a novel deep unrolling network, TSISTA-Net (Tunnel Seismic Iterative Shrinkage–Thresholding Algorithm Network), specifically designed to improve seismic data quality. Built upon the ISTA-Net architecture, TSISTA-Net incorporates three distinct innovations. First, reflection padding is utilized to minimize boundary artifacts and effectively recover edge information. Second, multi-scale dilated convolutions are employed to extend the receptive field, thereby facilitating the extraction of long-range and multi-scale features from seismic signals. Third, a lightweight and patch-based processing strategy is adopted, guaranteeing high computational efficiency while maintaining reconstruction quality. The effectiveness of the proposed method was validated on both synthetic and real tunnel seismic datasets. On synthetic data, TSISTA-Net achieved a PSNR of 37.28 dB, an SSIM of 0.9667, and an LCCC of 0.9357, outperforming U-Net (35.93 dB, 0.9480, 0.9087) and conventional ISTA-Net (34.04 dB, 0.9167, 0.8878). These results demonstrate superior signal fidelity, structural similarity, and local correlation relative to established baselines. Consistent improvements were also observed on real tunnel datasets, indicating that TSISTA-Net provides an efficient, data-driven solution for tunnel seismic data processing with strong potential for practical engineering applications. Full article

This paper presents the development of OpenCHIRP, an innovative sub-bottom profiler (SBP) designed for high-resolution seismic reflection surveys in shallow-water marine and lacustrine environments. The instrument employs chirped (frequency-modulated) impulses to penetrate the first few meters of unconsolidated sediments below the seafloor. Key characteristics include low cost, light weight, and low energy consumption, making it particularly suitable for deployment onboard Autonomous Surface Vehicles (ASVs). We discuss design, functionality, and potential applications of this innovative instrument, as well as results of the preliminary tests. Full article

Groundwater resources in Jordan are under severe stress due to rapidly increasing water demand and over-abstraction that far exceeds natural replenishment. In addition, water quality is threatened by pollution from the misuse of fertilizers and pesticides, leakage from septic tanks, and illegal waste disposal. This study focuses on the Aqeb, Corridor, and Special Economic Zone wellfields, where hydrological and hydrochemical investigations were carried out. A total of 36 groundwater samples were collected and analyzed for hydrochemical composition, stable isotopes of oxygen (δ¹⁸O) and hydrogen (δ²H), and trace elements. In addition, two exploration 2D seismic profiles crossing the study area were interpreted, providing critical insights into the activity of the subsurface Fuluk Fault zone and its relationship with the wellfields. The hydrochemical results reveal elevated total dissolved solids and nitrate concentrations, accompanied by more depleted δ¹⁸O and δ²H values in wells located in the central part of the study area. Three distinct hydrochemical groups were identified within the same aquifer, indicating heterogeneity in groundwater chemistry that reflects variations in recharge conditions, flow paths, and geochemical processes. The first group (high Na/Cl with low salinity) likely represents recently recharged waters with limited rock–water interaction. The second group (intermediate Na/Cl and moderate salinity) may be influenced by evaporation, irrigation return flow, or cation exchange. The third group (low Na/Cl with high salinity) suggests the dissolution of sulfate minerals or mixing with deeper mineralized groundwater, possibly facilitated by structural features such as the Fuluk Fault. Seismic interpretation indicates several active near-surface fault systems that are likely to serve as preferential pathways for salinity and nitrate enrichment, linked to intensive agricultural activities and wastewater leakage from nearby septic tanks. The findings emphasize the combined influence of geochemical processes, excessive groundwater abstraction, and structural features in controlling water quality in the region. Full article

While 3D seismic reflection is well established in hydrocarbon exploration at the kilometer scale in relatively simple offshore settings, its application to shallow faulting in continental basins is rare, owing to difficulties in adapting acquisition and processing to rugged terrains and complex near-surface conditions. We present the first high-resolution 3D seismic study of a seismogenic fault in a structurally complex intramontane basin at depths < 200 m. The survey focuses on the Pantano–Ripa Rossa Fault, ruptured during the 1980 Mw 6.9 Irpinia earthquake, the largest Italian event of the past century. This fault cuts across the Pantano di San Gregorio Magno, a small basin filled with Quaternary sediments and showing modest cumulative displacement. Our results demonstrate that in such environments, where morphotectonic analysis and 2D geophysics provide limited constraints, high-resolution 3D seismic imaging is crucial to resolve fault geometry and to assess surface-faulting hazard. The 3D volume reveals a ~35–40 m wide intra-basin deformation zone beneath the 1980 rupture, composed of synthetic and antithetic splays, and highlights lateral variations in fault geometry and stratigraphy. Deformation is distributed and complex, with fault-controlled depocenters, variable sedimentary architectures, and rapid basement-depth changes—features unresolved by 2D data. We infer that the Pantano–Ripa Rossa Fault is relatively young, active since the late Middle Pleistocene, and developed in the hanging wall of the NE-dipping southern basin-bounding fault, challenging previous models that located the master fault along the northern basin margin. Full article

The Muji Fault Zone (MJF) in the northeastern Pamir Plateau hosts a well-developed non-volcanic geothermal system, characterized by widespread hot springs and mud volcanoes—where core processes of geothermal fluids, including atmospheric precipitation recharge, shallow crustal circulation, carbonate-driven water–rock interactions, and CO₂-rich fluid discharge, are tightly coupled with regional intense crustal deformation and frequent seismic activity. We collected and analyzed 22 geothermal water samples and 8 bubbling gas samples from the MJF periphery, finding that the geothermal waters are predominantly of the HCO₃-Ca·Mg hydrochemical type, with hydrogen (δD: −103.82‰ to −70.21‰) and oxygen (δ¹⁸O: −14.89‰ to −10.10‰) isotopes indicating atmospheric precipitation as the main recharge source. The Na-K-Mg ternary diagram classified the waters as immature, reflecting low-temperature water–rock interactions in the shallow crust (<3 km), while noble gas isotopes (³He/⁴He: 0.03–0.09 Ra, Ra = 1.43 × 10⁻⁶) and carbon isotopes (δ¹³C-CO₂) confirmed fluid origin from crustal carbonate dissolution; SiO₂ geothermometry estimated thermal reservoir temperatures at 67–155 °C. Long-term monitoring (May 2019–April 2024) of Tahman (THM) and Bulake (BLK) springs revealed significant pre-seismic anomalies: before the 2023 Tajikistan Ms7.2 and 2024 Wushi Ms7.1 earthquakes, Na⁺, Cl⁻, and SO₄²⁻ concentrations showed notable negative anomalies (exceeding 2σ of background values) with synchronous trends between the two springs. Integrating these findings, a “Fault-Spring-Mud Volcano-Earthquake” fluid response model was established, providing direct evidence of deep-shallow fluid coupling in mud volcano–geothermal fluid interactions. This study enhances understanding of the dynamic evolution of non-volcanic geothermal systems under tectonic stress and clarifies the mechanisms of hydrogeochemical variations in fault-controlled geothermal systems, offering a robust scientific basis for advancing research on tectonic–fluid interactions in active fault zones of the northeastern Pamir Plateau. Full article

In the context of reservoir monitoring, time-lapse (4D) full-waveform inversion (FWI) of seismic data can potentially estimate reservoir changes with high resolution. However, most existing field-data applications are carried out with isotropic, and often acoustic, FWI algorithms. Here, we apply a time-lapse FWI methodology for transversely isotropic (TI) media with a vertical symmetry axis (VTI) to offshore streamer data acquired at Pyrenees field in Australia. We explore different objective functions, including those based on global correlation (GC) and designed to mitigate errors in the source signature (SI, or source-independent). The GC objective function, which utilizes mostly phase information, produces the most accurate inversion results by mitigating the difficulties associated with amplitude matching of the synthetic and field data. The SI FWI algorithm is generally more robust in the presence of distortions in the source wavelet than the other two methods, but its application to field data is hampered by reliance on amplitude matching. Taking anisotropy into account provides a better fit to the recorded data, especially at far offsets. In addition, the application of the anisotropic FWI improves the flatness of the major reflection events in the common-image gathers (CIGs). The 4D response obtained by FWI reveals time-lapse parameter variations likely caused by the reservoir gas coming out of solution and by the replacement of gas with oil. Full article

The structure and geomorphology of channel systems play a critical role in interpreting sedimentary processes and characterizing subsurface reservoir capacity. This study presents an innovative 3D DS-TransUnet model for seismic channel interpretation. The model incorporates a multi-scale Swin Transformer architecture capable of processing 3D data in both the encoder and decoder, and integrates a feature fusion module into the skip connections to effectively combine shallow detail features with deep semantic features, thereby enhancing the detectability of weak reflection signals. This design not only enables the network to capture global dependencies but also preserves fine-grained local details, allowing for more robust feature learning under complex geological conditions. In addition, a complete synthetic data generation workflow is proposed, through which 300 pairs of high-quality synthetic data were constructed for model training. During training, the proposed model achieved a significantly faster convergence speed compared with other selected models. Experimental results on both synthetic and field seismic datasets demonstrate that the proposed method yields substantial improvements in channel boundary delineation accuracy and interference suppression, providing an efficient and reliable approach for intelligent channel recognition. Full article

This study presents a novel approach to the parametrization of 3D PETRO FACIES and SEISMO FACIES using supervised and unsupervised learning, supported by a coherent structural and stratigraphic framework, to enhance understanding of the presence of hydrocarbons in the Dzików–Uszkowce region. The prediction relies on selected seismic attributes and well logging data, which are essential in hydrocarbon exploration. Three-dimensional seismic data, a crucial source of information, reflect the propagation velocity of elastic waves influenced by lithological formations and reservoir fluids. However, seismic response similarities complicate accurate seismic image interpretation. Three-dimensional seismic data were also used to build a structural–stratigraphic model that partitions the study area into coeval strata, enabling spatial analysis of the machine learning results. In the 3D seismic model, PETRO FACIES classification achieved an overall accuracy of 80% (SD = 0.01), effectively distinguishing sandstone- and mudstone-dominated facies (RT1–RT4) with F1 scores between 0.65 and 0.85. RESERVOIR FACIES prediction, covering seven hydrocarbon system classes, reached an accuracy of 70% (SD = 0.01). However, class-level performance varied substantially. Non-productive zones such as HNF (No Flow) were identified with high precision (0.82) and recall (0.84, F1 = 0.83), while mixed-saturation facies (HWGS, BSWGS) showed moderate performance (F1 = 0.74–0.81). In contrast, gas-saturated classes (BSGS and HGS) suffered from extremely low F1 scores (0.08 and 0.12, respectively), with recalls as low as 5–7%, highlighting the model’s difficulty in discriminating these units from water-saturated or mixed facies due to overlapping seismic responses and limited training data for gas-rich intervals. To enhance reservoir characterization, SEISMO FACIES analysis identified 12 distinct seismic facies using key attributes. An additional facies (facies 13) was defined to characterize gas-saturated sandstones with high reservoir quality and accumulation potential. Refinements were performed using borehole data on hydrocarbon-bearing zones and clay volume (VCL), applying a 0.3 VCL cutoff and filtering specific facies to isolate zones with confirmed gas presence. The same approach was applied to PETRO FACIES and a new RT facie was extracted. This integrated approach improved mapping of lithological variability and hydrocarbon saturation in complex geological settings. The results were validated against two blind wells that were excluded from the machine learning process. Knowledge of the presence of gas in well N-1 and its absence in well D-24 guided verification of the models within the structural–stratigraphic framework. Full article

The Huangliu Formation, Section I, Gas Group II, at the eastern X gas field of the Yinggehai Basin, hosts thick, irregularly deposited sandstone bodies. The genesis of these sedimentary sand bodies has remained unclear. Utilizing drilling logs, core samples, and 3D seismic data from this field, this study integrates seismic geomorphology analysis, paleo-hydrodynamic reconstruction, and sedimentary numerical simulation to investigate the spatiotemporal evolution of the depositional system under micro-paleotopographic conditions during Gas Zone II sedimentation. Key conclusions include the development of seven morphologically diverse isolated sand bodies in the Lower II Gas Zone, covering areas of 1.4–13.4 km² with thicknesses ranging from 8.0 to 42.0 m. These sand bodies consist predominantly of massive fine-grained sandstone, characterized by box-shaped gamma-ray (GR) log responses and U- or V-shaped seismic reflection configurations. Reconstruction of paleo-turbidity current hydrodynamics for the Lower II depositional period was achieved through analysis of topographic slope gradients and the dimensional constraints (width/depth) of confined channels. Critically, slope gradients within the intraslope basin prompted a transition from supercritical to subcritical flow states within turbidity currents. This hydraulic transformation drove alternating erosion and deposition along the seafloor topography, ultimately generating the observed irregular, isolated turbidite sand bodies. Full article

The Qiangtang Basin (Tibetan Plateau) poses significant geophysical challenges for seismic exploration due to near-surface widespread permafrost and steeply dipping Mesozoic strata induced by the Cenozoic Indo-Eurasian collision. These seismic geological conditions considerably contribute to lower signal-to-noise ratios (SNRs) with complex wavefields, to some extent reducing the reliability of conventional seismic imaging and structural interpretation. To address this, the common-reflection-surface (CRS) stack method, derived from optical paraxial ray theory, is implemented to transcend horizontal layer model constraints, offering substantial improvements in high-SNR prestack gather generation and prestack depth migration (PSDM) imaging, notably for permafrost zones. Using 2D seismic data from the basin, we detailedly compare the CRS stack with conventional SNR enhancement techniques—common midpoint (CMP) FlexBinning, prestack random noise attenuation (PreRNA), and dip moveout (DMO)—evaluating both theoretical foundations and practical performance. The result reveals that CRS-processed prestack gathers yield superior SNR optimization and signal preservation, enabling more robust PSDM velocity model building, while comparative imaging demonstrates enhanced diffraction energy—particularly at medium (20–40%) and long (40–60%) offsets—critical for resolving faults and stratigraphic discontinuities in PSDM. This integrated validation establishes CRS stacking as an effective preprocessing foundation for the depth-domain imaging of complex permafrost geology, providing critical improvements in seismic structural resolution and reduced interpretation uncertainty for hydrocarbon exploration in permafrost-bearing basins. Full article

Amid increasing interest in enhanced oil recovery and carbon geological sequestration programs, improved static reservoir lithofacies models are emerging as a requirement for well-guided project management. Building reservoir models can leverage seismic attribute clustering for seismic facies mapping. One challenge is that machine learning (ML) seismic facies mapping is prone to a wide range of equally possible outcomes when traditional unsupervised ML classification is used. There is a need to constrain ML seismic facies outcomes to limit the predicted seismic facies to those that meet the requirements of geological plausibility for a given depositional setting. To this end, this study utilizes an unsupervised comparative hierarchical and K-means ML classification of the whole 3D seismic data spectrum and a suite of spectral bands to overcome the cluster “facies” number uncertainty in ML data partition algorithms. This comparative ML, which was leveraged with seismic resolution data preconditioning, predicted geologically plausible seismic facies, i.e., seismic facies with spatial continuity, consistent morphology across seismic bands, and two ML algorithms. Furthermore, the variation of seismic facies classes was validated against observed lithofacies at well locations for the Mississippian carbonates of Kansas. The study provides a benchmark for both unsupervised ML seismic facies clustering and an understanding of seismic facies implications for reservoir/saline-aquifer aspects in building reliable static reservoir models. Three-dimensional seismic reflection P-wave data and a suite of well logs and drilling reports constitute the data for predicting seismic facies based on seismic attribute input to hierarchical analysis and K-means clustering models. The results of seismic facies, six facies clusters, are analyzed in integration with the target-interval mineralogy and reservoir porosity. The study unravels the nature of the seismic (litho) facies interplay with porosity and sheds light on interpreting unsupervised machine learning facies in tandem with both reservoir porosity and estimated (Umaa-RHOmaa) mineralogy. Full article

This study investigates the influence of bedrock material conditions on the seismic behavior of the Niedzica earth dam in southern Poland. It examines the dam’s dynamic response to a real seismic event—the 2004 Podhale earthquake—and evaluates how different foundation conditions affect structural performance under spatially varying ground motions. A spatially varying ground motion excitation model was developed, incorporating both wave coherence loss and wave passage effects. Seismic data was collected from three monitoring stations: two located in fractured bedrock beneath the dam and one installed in the surrounding intact Carpathian flysch. From these recordings, two key spatiotemporal parameters were experimentally determined: the seismic wave velocity and the spatial scale parameter (α), which reflects the degree of signal incoherence. For the fractured bedrock beneath the dam, the wave velocity was 2800 m/s and α = 0.43; for the undisturbed flysch, it was 3540 m/s and α = 0.82. A detailed 3D finite element model of the dam was developed in ABAQUS and subjected to time history analyses under three excitation scenarios: (1) uniform input, (2) non-uniform input with coherence loss, and (3) non-uniform input including both coherence loss and wave passage effects. The results show that the dam’s seismic response is highly sensitive to the choice of spatiotemporal parameters. Using generalized values from the flysch reduced predicted shear stresses by up to 16% compared to uniform excitation. However, when the precise parameters for the fractured bedrock were applied, the reductions increased to as much as 24%. This change in response is attributed to the higher incoherence of seismic waves in fractured material, which causes greater desynchronization of ground motion across the dam’s foundation. Even small-scale geological differences—when properly reflected in the spatiotemporal model—can significantly influence seismic safety evaluations of large-scale structures. Ultimately, shifting from regional to site-specific parameters enables a more realistic assessment of dynamic stress distribution. Full article

The South China block (SCB) is characterized by complex tectonics, large-scale lithospheric deformation, and extensive mineralization in its southeastern region. However, the geodynamic processes and mechanisms driving mineralization remain controversial, partly due to the lack of information on its fine crustal structure. The resolution of crustal seismic tomography is relatively low due to the uneven distribution of local earthquakes in South China. In this study, we conduct a joint inversion of Bouguer gravity and seismic travel-time data to investigate the detailed 3-D P-wave velocity (Vp) structure of the crust beneath the SCB. Our results show the following: (1) strong lateral heterogeneities exist in the crust, which reflect the surface geology and tectonics well; (2) the Vp patterns at different depths beneath the Yangtze block are almost consistent, but those beneath the Cathaysia block vary significantly, which might be related to the lithosphere thinning in the Mesozoic; (3) decoupling between the upper crust and the lower crust occurs at ~20 km depth beneath the eastern SCB; (4) the Vp patterns vary beneath different metallogenic belts; and (5) distinct low-Vp anomalies exist in the lower crust beneath mineral deposits. These results suggest that the deep mineralization is closely associated with the lithospheric thinning and upwelling thermal flow in the Mesozoic beneath the eastern SCB. Our Vp tomographic result also strongly supports the viewpoint that the mineralization mechanism varies for different metallogenic belts. Full article