Search Results (1,726)

The integration of petrological and geochemical analyses serves as an effective methodology for reconstructing depositional environments and constraining sediment provenance within distinct tectonic frameworks. This study investigates the provenance characteristics of the Silurian Kepingtag Formation in the northwestern Tarim Basin through an integrated approach combining field outcrop observations and laboratory analyses. Fieldwork covers the Sishichang, Dawangou, and Tongguzibulong sections, while laboratory analyses include clastic component identification, whole-rock major and trace element geochemical analysis, and rare earth element (REE) profiling. These efforts enable a systematic evaluation of sediment sources and their tectonic linkages. The research provides a theoretical basis for understanding the tectono-sedimentary framework of the northwestern Tarim Basin during the Early Silurian and offers significant guidance for reconstructing the lithofacies paleogeographic pattern of the basin during this period. Petrographic analyses reveal a lithological assemblage dominated by lithic quartz sandstones and lithic sandstones, with subordinate feldspathic lithic sandstones. Quartz exhibits secondary overgrowths. In a relatively stable tectonic environment, sediments undergo a gentle burial rate, which favors the formation of this phenomenon. Lithic fragments are dominated by magmatic lithics, indicating that the source contains magmatic rocks. Detrital component analysis reveals that the provenance of Kepingtag Formation sandstones in the study area is predominantly characterized by stable craton and recycled orogenic belt tectonic settings. Integrated geochemical datasets from major element compositions and trace element signatures constrain the provenance characteristics of the Kepingtag Formation sandstones. Major element ratios demonstrate predominant contributions from felsic igneous source rocks, while trace element ratios are diagnostic of sediment derivation from passive continental margin settings, consistent with prolonged tectonic quiescence along the northern Tarim cratonic margin during Silurian deposition The CIA index indicates that the Silurian Kepingtag Formation in the study area exhibits weak to moderate weathering. Integrating the above analyses, the Tabei Uplift—ancient craton setting—is interpreted as the likely provenance source for the sandstones of the Kepingtag Formation in the northwestern Tarim Basin. Full article

Landslide susceptibility mapping (LSM) faces persistent challenges in defining representative stable samples as conventional random selection often includes unstable areas, introducing spatial bias and compromising model accuracy. To address this, we redefine the certainty factor (CF) method—traditionally for factor weighting—as a spatial screening tool for stable zone delineation and apply it to the tectonically active upper Jinsha River (937 km², southeastern Tibetan Plateau). Our approach first generates a preliminary susceptibility map via CF, using the natural breaks method to define low- and very low-susceptibility zones (CF < 0.1) as statistically stable regions. Non-landslide samples are exclusively selected from these zones for support vector machine (SVM) modeling with five-fold cross-validation. Key results: CF-guided sampling achieves training/testing AUC of 0.924/0.920, surpassing random sampling (0.882/0.878) by 4.8% and reducing ROC standard deviation by 32%. The final map shows 88.49% of known landslides concentrated in 25.70% of high/very high-susceptibility areas, aligning with geological controls (e.g., 92% of high-susceptibility units in soft lithologies within 500 m of faults). Despite using a simpler SVM, our framework outperforms advanced models (ANN: AUC, 0.890; RF: AUC, 0.870) in the same region, proving physical heuristic sample curation supersedes algorithmic complexity. This transferable framework embeds geological prior knowledge into machine learning, offering high-precision risk zoning for disaster mitigation in data-scarce mountainous regions. Full article

Ferromanganese nodules exhibit strong capacity for heavy metal immobilization and are thus a crucial contributor to the high geological background in karst areas. Heavy metals sequestered within ferromanganese nodules display low bioavailability, which leads to an overestimation of ecological risk in areas with high geological backgrounds. However, limited attention is given to the enrichment process of heavy metals and the overestimated ecological risk of ferromanganese nodules in karst areas. Here, the surface soils and ferromanganese nodules are collected from a region dominated by carbonate and clastic rocks to investigate the enrichment of heavy metals (Cr, Ni, Cu, Zn, As, Cd, Pb, and Hg), the influence of parent rock, and their ecological implications in Northeastern Guangxi. Results show the following findings: (1) Heavy metals are enriched in ferromanganese nodules, with Cr and As correlating with Fe, and Cd and Pb correlating with Mn. (2) The spatial distribution of each element closely matches parent rock lithology, and high heavy-metal concentrations of both soils and ferromanganese nodules occur in carbonate areas. (3) The proportion of contaminated samples generally decreases after excluding the contribution of ferromanganese nodules, leading to a decline in risk level in carbonate areas, while clastic areas exhibit minimal change. Full article

Long and continuous lacustrine sediments in Southwest China provide exceptional records of the Indian summer monsoon (ISM) evolution. Rock magnetic and environmental magnetic methods have significant roles in these lacustrine studies. However, lacustrine sedimentary environments are complex and magnetic mineral signatures can be altered by post-depositional processes. This study applies isothermal remanent magnetization (IRM) component unmixing methods to lacustrine sediments from the Heqing core, to identify and quantify magnetic mineral components. We analyzed 104 samples based on lithological variations and magnetic susceptibility (χ) to examine the composition of magnetic minerals and their relative contributions. Three distinct magnetic components were identified in IRM component unmixing results: a low-coercivity detrital component, a medium-coercivity authigenic component, and a hard magnetic component. Based on rock magnetic results, the medium-coercivity component was attributed to greigite. These components exhibit stratigraphic trends that reflect changes in paleoenvironmental conditions. The medium-coercivity component shows an upwards decrease, indicating a significant change in ISM science at about 1.8 Ma. The study highlights the importance of considering post-depositional processes when interpreting magnetic mineral signatures in lacustrine sediments. The CLG model, combined with conventional rock magnetic analyses, provides a rapid approach for characterizing magnetic assemblages in weakly magnetic sediments. Full article

The profound Phanerozoic destruction of the eastern North China Craton (NCC) is well documented, yet its mechanism remains debated due to limited constraints on thermal state and lithospheric thickness during the Early Cretaceous—the peak period of cratonic destruction. We address this gap through integrated geochemical analysis (major/trace elements, Sr-Nd-Pb isotopes, olivine chemistry) of Early Cretaceous (~125 Ma) Fangcheng basalts from Shandong. These basalts possess high MgO (8.14–11.31 wt%), Mg# (67.23–73.69), Ni (126–244 ppm), and Cr (342–526 ppm). Their trace elements show island arc basalt (IAB) affinities: enrichment in large-ion lithophile elements and depletion in high-field-strength elements, with negative Sr and Pb anomalies. Enriched Sr-Nd isotopic compositions [⁸⁷Sr/⁸⁶Sr(t) = 0.709426–0.709512; ε_Nd(t) = −12.60 to −13.10], unradiogenic ²⁰⁶Pb/²⁰⁴Pb(t) and ²⁰⁸Pb/²⁰⁴Pb(t) ratios (17.55–17.62 and 37.77–37.83, respectively), and slightly radiogenic ²⁰⁷Pb/²⁰⁴Pb(t) ratios (15.55–15.57) reflect an upper continental crustal signature. Covariations of major elements, Cr, Ni, and trace element ratios (Sr/Nd, Sc/La) with MgO indicate dominant olivine + pyroxene fractionation. High Ce/Pb ratios and lack of correlation between Ce/Pb or ε_Nd(t) and SiO₂ preclude significant crustal contamination. The combined isotopic signature and IAB-like trace element patterns support a lithospheric mantle source that was metasomatized by upper crustal material. Olivine phenocrysts exhibit variable Ni (1564–4786 ppm), Mn (903–2406 ppm), Fe/Mn (56.63–85.49), 10,000 × Zn/Fe (9.55–19.55), and Mn/Zn (7.07–14.79), defining fields indicative of melts from both peridotite and pyroxenite sources. High-MgO samples (>10 wt%) in the Grossular/Pyrope/Diopside/Enstatite diagram show a clinopyroxene, garnet, and olivine residue. Reconstructed primary melts yield formation pressures of 3.5–3.9 GPa (110–130 km depth) and temperatures of 1474–1526 °C, corresponding to ~60 mW/m² surface heat flow. This demonstrates retention of a ≥110–130 km thick lithosphere during peak destruction, arguing against delamination and supporting a thermo-mechanic erosion mechanism dominated by progressive convective thinning of the lithospheric base via asthenospheric flow. Our findings therefore provide crucial thermal and structural constraints essential for resolving the dynamics of cratonic lithosphere modification. Full article

To increase the reliability of three-dimensional (3D) geological models in areas characterized by sparse well data and poor seismic quality, a sedimentary dynamics simulation was conducted on the J7 tidal delta sedimentary reservoir in the Y gas field, which is located in the West Siberian Basin. A 3D sedimentary model of the study area was developed by defining parameters such as bottom topography, water level, tidal range, river discharge, and wave amplitude. By integrating the reservoir characteristics, the sedimentary dynamics simulation results were transformed into a three-dimensional training template for multipoint geostatistical modeling. Simultaneously, the channel and bar parameters derived from the sedimentary dynamics simulation served as variable inputs for attribute modeling. Combined with well data, a 3D geological model of the reservoir was constructed and subsequently validated using verification wells. The results demonstrate that the reliability of reservoir lithology modeling—when constrained by three-dimensional training templates generated through sedimentary dynamics simulation—is significantly higher than that achieved using sequential Indicator simulation. Three-dimensional modeling of tidal delta reservoirs, employing coupled sedimentary dynamics simulations and multipoint geostatistical methods, can effectively enhance the reliability of reservoir geological models in areas with sparse well data, thereby providing a robust foundation for subsequent well deployment and development. Full article

This study presents an integrated geomechanical modeling framework for predicting multi-scale fracture networks and their activity in the Longmaxi Formation shale reservoir, northern Luzhou region, southeastern Sichuan Basin—an area shaped by complex, multi-phase tectonic deformation that poses significant challenges for resource prospecting. The workflow begins with quantitative characterization of key mechanical parameters, including uniaxial compressive strength, Young’s modulus, Poisson’s ratio, and tensile strength, obtained from core experiments and log-based inversion. These parameters form the foundation for multi-phase finite element simulations that reconstruct paleo- and present-day stress fields associated with the Indosinian (NW–SE compression), Yanshanian (NWW–SEE compression), and Himalayan (near W–E compression) deformation phases. Optimized Mohr–Coulomb and tensile failure criteria, coupled with a multi-phase stress superposition algorithm, enable quantitative prediction of fracture density, aperture, and orientation through successive tectonic cycles. The results reveal that the Longmaxi Formation’s high brittleness and lithological heterogeneity interact with evolving stress regimes to produce fracture systems that are strongly anisotropic and phase-dependent: initial NE–SW-oriented domains established during the Indosinian phase were intensified during Yanshanian reactivation, while Himalayan uplift induced regional stress attenuation with limited new fracture formation. The cumulative stress effects yield fracture networks concentrated along NE–SW fold axes, fault zones, and intersection zones. By integrating geomechanical predictions with seismic attributes and borehole observations, the study constructs a discrete fracture network that captures both large-scale tectonic fractures and small-scale features beyond seismic resolution. Fracture activity is further assessed using friction coefficient analysis, delineating zones of high activity along fold–fault intersections and stress concentration areas. This principle-driven approach demonstrates how mechanical characterization, stress field evolution, and fracture mechanics can be combined into a unified predictive tool, offering a transferable methodology for structurally complex, multi-deformation reservoirs. Beyond its relevance to shale gas development, the framework exemplifies how advanced geomechanical modeling can enhance resource prospecting efficiency and accuracy in diverse geological settings. Full article

To unravel the link between agate geochemistry, host volcanic rocks, and ore-forming processes, this study integrated elemental correlation analysis, interaction interpretation, and interpretable machine learning (LightGBM-SHAP framework with SMOTE and 5-fold cross-validation) using 203 in-situ element datasets from 16 global deposits. The framework achieved 99.01% test accuracy and 97.4% independent prediction accuracy in discriminating host volcanic rock types. Key findings reveal divergence between statistical elemental correlations and geological interactions. Synergies reflect co-migration/co-precipitation, while antagonisms stem from source competition or precipitation inhibition, unraveling processes like stepwise crystallization. Rhyolite-hosted agates form via a “crust-derived magmatic hydrothermal fluid—medium-low salinity complexation—multi-stage precipitation” model, driven by high-silica fluids enriching Sb/Zn. Andesite-hosted agates follow a “contaminated fluid—hydrothermal alteration—precipitation window differentiation” model, controlled by crustal contamination. Basalt-hosted agates form through a “low-temperature hydrothermal fluid—basic alteration—progressive mineral decomposition” model, with meteoric water regulating Na-Zn relationships. Zn acts as a cross-lithology indicator, tracing crust-derived fluid processes in rhyolites, feldspar alteration intensity in andesites, and alteration timing in basalts. This work advances volcanic-agate genetic studies via “correlation—interaction—mineralization model” coupling, with future directions focusing on large-scale micro-area elemental analysis. Full article

Subsurface characterization for lithological and fluid properties is important for all aspects of geophysical exploration where estimating a high-resolution elastic property through seismic inversion is vital. Starting with an initial subsurface model, computing synthetic or predicted seismic data, and matching these data with observed seismic data, seismic inversion uses an optimization process to iteratively modify the initial model until the prediction reasonably matches the observation. Routine applications of seismic inversion for subsurface reservoir characterization are currently restricted to amplitude-variation-with-angle inversion, which uses convolution as the basis for forward modeling to compute synthetic seismic data. Although computationally efficient, the inherent convolutional assumption ignores complex wave propagation effects and often fails to estimate subsurface models with sufficient accuracy. Here, we review the current state of the art for seismic inversion, and we discuss a method that uses an analytical wave equation solver for forward modeling and a global method for optimization that can overcome the current limitations of amplitude-variation-with-angle inversion. Using real seismic data, we demonstrate the accuracy of this method. Because this waveform-based method is computationally demanding, we also discuss the current advances of computational technology, including artificial intelligence that can improve its computational efficiency. Full article

The Lower Cretaceous Baxigai Formation is characterized by fan-delta front deposits and serves as a crucial target for ultradeep tight gas exploration in western China. Consequently, investigating its reservoir characteristics and controlling factors is critical. To characterize these reservoirs, we integrated well logs, core observation and analyses, thin-section petrography, high-pressure mercury injection, and scanning electron microscopy. This approach enabled comprehensive analysis of tight reservoir attributes and their genetic controls. Results show that the Baxigai Formation developed a fan-delta system, with premium reservoirs primarily concentrated in subaqueous distributary channels of fan-delta fronts. Reservoir lithology consists of medium- to fine-grained arkose and lithic arkose, exhibiting well-developed intergranular and intragranular dissolution pores alongside low mineralogical maturity. With average porosity of 2.76% and permeability of 0.24 × 10⁻³ μm², these reservoirs are classified as low-porosity and medium–low-permeability systems. Depositional, diagenetic, and structural factors are the main controls on reservoir quality. Subaqueous distributary channels and mouth bars within the fan-delta system provide favorable conditions for reservoir development. Intergranular dissolution pores formed by feldspar dissolution and organic acid reactions play a key role in enhancing reservoir quality and supporting hydrocarbon generation. Structural fractures play a pivotal role in elevating permeability and establishing effective fracture–pore configurations. 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

Water reservoirs play a crucial role in the environment in many aspects: hydrology, geochemistry, sediment lithology, geo- and biodiversity, landscape, etc. First of all, it is necessary to have accurate information about the spatial distribution of these objects in a given area to assess their size and functioning. Maps and contemporary spatial databases are often incomplete or outdated, especially in regard to small objects, of variable surface area and condition. This article uses the following approach: high-resolution terrain models derived from airborne laser scanning (ALS) were used for visual interpretation of extensive, flat depressions representing water body basins, thus determining the total number of objects, and classifying them as kettle holes, lakes, ponds, and other types of reservoirs (e.g., overbank basins, oxbow lakes). Using an aerial orthophotomap, the objects were subsequently verified as to how many basins are currently occupied by water bodies. The next step was to determine a number of topographic and morphometric parameters for each object in order to assess their functioning conditions. For selected objects, the assessment was expanded to include a geochemical and lithological analysis of the sediments. The study was conducted in the catchment of the Słubia River (136 km²), located in Central Europe, in northwestern Poland. In the Słubia catchment, a total of 931 water body basins were mapped. The dominant forms are kettle holes (<1 ha), representing nearly 80% of all objects. At present, kettle holes are largely devoid of water bodies and subject to a strong human impact. In addition to those, 118 lake basins were identified (>1 ha, the largest being Lake Morzycko, 360 ha), half of which are occupied by water reservoirs. Ponds and other reservoirs were represented by 37 and 47 objects, respectively. From the perspective of contemporary sediment-forming processes in the documented sedimentary basins, the most favorable conditions for biogenous sediment accumulation exist in the catchments of the upper and medium courses of the Słubia River valley. Although the lithological diversity and thickness of individual sediment types in the Słubia catchment represent local features, they corroborate the results of previous telmatologic research conducted in Myślibórz Lakeland. Full article

The widespread application of granite manufactured sand (GS) concrete in pavement engineering is limited by issues such as suboptimal particle size distribution and an unclear optimal rock powder content. Furthermore, research on the long-term evolution of the skid resistance characteristics of GS concrete remains relatively scarce. This knowledge gap makes it difficult to accurately assess the skid resistance performance of GS concrete in practical engineering applications, thereby compromising traffic safety. To address this research gap, this study utilized a self-developed indoor abrasion tester for pavement concrete to assess the skid resistance of GS concrete. Three-dimensional laser scanning was employed to acquire the concrete’s surface texture parameters. Using the friction coefficient and texture parameters as skid resistance evaluation indicators, and combining these with changes in the concrete’s surface morphology, the study explores how effective sand content, stone powder content, and fine aggregate lithology affect the long-term skid resistance of GS concrete pavements and reveals the evolution trends of their long-term skid resistance. Research results show that as the number of wear cycles increases, low and high effective sand content affect the surface friction coefficient of specimens in opposite ways. Specimens with 95% effective sand content exhibit superior skid resistance. Stone powder content influences the friction coefficient in three distinct variation patterns, showing no clear overall trend. Nevertheless, specimens with 5% stone powder content demonstrate better skid resistance. Among different fine aggregate lithologies, GS yields a higher friction coefficient than river sand (RS), while limestone manufactured sand (LS) shows significant friction coefficient fluctuations across different wear cycles. Adding stone powder substantially enhances mortar strength and delays groove collapse edge formation. Moreover, higher effective sand content and proper stone powder content mitigate bleeding, thereby improving mortar performance. Full article

The present study applied a GIS-based methodology for assessing soil diversity in a protected mountain area of Italy. Using QGIS, morphological (i.e., altitude and slope), lithological, climatic, and land use layers were intersected to delineate 16 land units (LUs), each representing relatively homogeneous conditions for soil formation, according to Jenny’s equation. To obtain the soil map units, a total of 112 soil profiles were analyzed, including 79 from previous studies and 33 that were newly excavated during 2023–2024 to fill gaps in underrepresented LU types. Most soils were classified as Inceptisols/Cambisols, occurring in both Dystric and Eutric variants, mainly in relation to lithology (i.e., arenaceous or pelitic facies). Alfisols, Umbrisols, and hydromorphic soils were also identified. The physicochemical properties showed marked variability among LUs, with sand content ranging from 39 to 798 g kg⁻¹, pH from 4.4 to 7.9, and organic carbon content from 1.6 to 6.1%. This LU-based framework allowed efficient field sampling, if compared to grid-based surveys, while retaining information on fine-scale pedodiversity. No quantitative accuracy assessment (e.g., boundary precision, internal homogeneity metrics) was conducted, even if the spatial coherence of the delineated LUs was supported by the distribution of soil profiles, which provided empirical validation of the LU framework. Full article

The borehole log image contains valuable text information, encompassing key geological data such as structural composition, orebody distribution, and lithological characteristics. These data are important for mineral prediction, GeoBigData, and GeoModeling. However, text recognition in borehole log images is challenging due to complex structures, image noise, and diverse fonts, leading to low accuracy with traditional OCR methods. As a result, substantial manual intervention is often required for verification and correction, hindering efficient application. This study proposes an optimization method based on the multi-layout adjustment voting mechanism to improve text recognition accuracy in borehole log images. During the recognition process, multiple OCR results are generated by adjusting text layouts, and a voting mechanism integrates these results to produce the most accurate output. Experimental results on the Dayingezhuang and Dingjiashan datasets demonstrate the effectiveness of the proposed method, achieving F1 scores of 97.96% and 94.36%, respectively. This optimization method improves text recognition accuracy and recall without modifying the OCR algorithm or applying post-processing, providing a new technical approach to enhancing text recognition precision in borehole log images. This improvement in text extraction accuracy from geological borehole data not only facilitates large-scale integration and analysis of subsurface geological information but also provides essential foundational data for GeoBigData and GeoModeling applications. Full article