Abandoned floodplains are complex landscapes in boreal permafrost regions due to diverse biogeomorphic effects that are highly modified by permafrost aggradation and degradation. We compiled biophysical properties for 150 cores at 135 sites with depths up to ~4 m on the Tanana Flats in central Alaska and developed depth profiles for bulk density, moisture, organic carbon, pH, stable isotopes, radiocarbon age, and thaw strain. We found strong associations among biophysical components but also highly variable soil properties and ecological histories. We developed a conceptual model of the transition pathways and biophysical drivers among ecosystem types. Across sites, fluvial deposition was active from 9820 to 4290 14C YBP, eolian silt and sand deposition prevalent from 3780 to 1890 YBP, and peat accumulation from 5330 YBP to present. Due to flat topography, water impoundment in depressions, groundwater, and ecological feedbacks, ecosystem-driven permafrost has a complex history of repeated aggradation and degradation resulting in highly fragmented landscapes. Recent thermokarst features had ages ranging from 20 to 920 YBP in collapse-scar bogs and from 50 to 250 YBP in collapse-scar fens. Abandoned floodplains with rapid thermokarst provide saturated environments for robust organic accumulation, with mean soil carbon stocks in the top 3 m being similar among thermokarst bogs (133 kg/m2), fens (108 kg/m2) and permafrost plateaus (115 kg/m2). This study contributes needed information on how permafrost dynamics and ground-ice characteristics influence landscape evolution and on the vulnerability of villages built on abandoned floodplains, infrastructure, and military use of training lands in boreal lowlands. Landscape fragmentation, complex palaeoecological histories, high spatial variability, and limited deep sampling of thermokarst features, however, restrict interpretation of how permafrost loss is affecting the soil carbon balance in an area where most permafrost will disappear in this century.
The Lampang Basin is a Cenozoic rift basin in northern Thailand whose geometry remains poorly constrained because of limited subsurface data. This study applies integrated gravity analysis and 3D gravity inversion to characterize basin geometry, structural segmentation, and subsurface density distributions. Complete Bouguer anomaly data from 1488 gravity stations were analyzed using regional–residual separation, edge-detection filtering, spectral depth estimation, and 2D forward gravity modeling, constrained by geological mapping and available borehole and seismic data. The resulting geological and geophysical constraints were incorporated into 3D geometry and density inversions to construct the first basin-scale 3D gravity inversion model of the Lampang Basin. The results identify four structurally distinct, fault-controlled sub-basins, refining previous gravity-based interpretations of three principal sub-basins. The Western and Central Sub-basins trend predominantly NE–SW, whereas the Eastern Sub-basin is predominantly N–S oriented; the Northeastern Sub-basin has a less well-defined geometry but is bounded by structures supporting a broadly N–S alignment. The 3D inversion indicates a maximum preserved sediment thickness of ~2050 m, with the deepest depocenter within the Central Sub-basin, whereas the broadest depocenter occurs within the Eastern Sub-basin. Gravity anomalies and inversion-derived density distributions further indicate an association between contrasting pre-Cenozoic basement domains on basin segmentation and geometry, including accretionary complexes, volcanic arcs, and forearc basin successions of the Paleo-Tethys subduction margin. Integrated gravity modeling therefore provides regional constraints on the preserved geometry and structural segmentation of Cenozoic intermontane basins where direct subsurface information is spatially limited.
Rock slope landslide potential, tunnel design, and the engineering of underground spaces critically require an analysis of rock joint orientation and spacing. Joint set measurements are typically determined by hand in the field using a compass–clinometer to measure the orientation of the geologic planes with respect to north and the dip of the plane with respect to the horizontal. Unmanned aerial vehicles (UAVs) can be utilized to capture hundreds of photos to create high-resolution 3D models of a rock outcrop, capturing visible joint set discontinuities on a faceted surface of a triangular irregular network (TIN). Computing methods of facets and facet normals from a point cloud allow for the characterization of discontinuity orientations without the need for manual measurements in the field. However, these methods used to calculate facets and facet normals result in the addition of noise in the dataset, which increases the difficulty of analysis. A two-stage filtering process employing density-based spatial clustering of applications with noise (DBSCAN), and the second derivative of the remaining clusters, removes data that are not representative of a discontinuity within the intact rock mass. Finally, an unsupervised clustering algorithm, K-Means Clustering, is applied to the dataset to extract the dip and dip direction of discontinuities. The methodology used to identify the orthogonal joint sets on a dam spillway demonstrated good performance across all identified joint sets, with the estimated variability in dip and dip direction broadly comparable to that observed in the manual field dataset. This indicates that this newly developed proof-of-concept approach can reliably capture the orientation and variability of orthogonal joint sets from large datasets.
Reliable stability assessment of structurally complex rock masses increasingly relies on advanced remote sensing techniques integrated with detailed geotechnical analysis. This study presents a combined remote geotechnical workflow applied to rock masses surrounding natural cavities, with the study area located in Greece, aiming to evaluate the stability of coupled cavity–slope systems under varying conditions. The methodology combines Unmanned Aerial Vehicle (UAV) photogrammetry and SLAM-based LiDAR surveying to acquire centimetre-scale surface and underground opening data. These datasets are fused into a geometrically consistent three-dimensional representation of the slope–portal–cavity system, enabling improved documentation of slope morphology, internal cave geometry and externally exposed discontinuity patterns. The fused spatial dataset was then used to extract a representative two-dimensional cavity–slope section for plane-strain finite element analysis. The numerical model was formulated as an equivalent-continuum model using the Hoek–Brown failure criterion, with stability assessed through the Shear Strength Reduction technique across multiple scenarios. Overall, the study demonstrates that integrated geotechnical and remote-sensing approaches improve geometric completeness and consistency, enhance reproducibility, and reduce geometry-related uncertainty in scenario-based stability assessments of complex rock masses with natural cavities and underground openings.
Shallow landslides triggered by extreme rainfall often occur abruptly and show pronounced spatial clustering. Accurate representation of rainfall conditions is therefore important for event-based landslide hazard assessment. This study investigated shallow landslides triggered by the April 2024 extreme rainfall event in Jiangwan Town, Guangdong Province, China. An event-based landslide inventory, half-hourly GPM IMERG precipitation data, and multiple environmental factors were used for hazard modelling. Three rainfall descriptors were considered: event cumulative rainfall, 21-day cumulative rainfall, and maximum 1 h rainfall. Controlled incremental experiments using Random Forest (RF) were conducted to evaluate the additional predictive information provided by these rainfall descriptors. RF, XGBoost, and an Artificial Neural Network (ANN) were then compared in terms of predictive performance. Incorporating all three rainfall descriptors increased the RF test-set AUC from 0.907 to 0.945. Among the three predefined rainfall descriptors, 21-day cumulative rainfall produced the largest incremental improvement. XGBoost achieved the highest overall predictive performance, with a test-set AUC of 0.971, and was selected for final hazard mapping. The high- and very-high-hazard zones predicted by XGBoost covered 33.2% of the study area and contained 89.7% of the observed landslide samples. These zones were concentrated mainly in the central and northeastern parts of Jiangwan Town. SHAP analysis identified elevation as the most influential predictor, while all three rainfall descriptors ranked among the important predictors. Overall, the results indicate that rainfall information at multiple temporal scales provides complementary predictive information and can improve event-conditioned shallow-landslide hazard assessment.
As a key tectonic zone formed by the India–Eurasia collision, the eastern Tibetan Plateau has complex crustal structures and intense tectonic activity. Its crustal stability is closely linked to regional geohazards and the safety of major engineering projects. This study assessed crustal stability using nine multi-source datasets, including terrestrial gravity, Bouguer gravity anomalies, seismic data, active faults, terrain indicators, and annual precipitation. A hybrid weighting framework coupling the Analytic Hierarchy Process (AHP) and CRITIC method was established, and factor analysis was further adopted to cross-verify the rationality of index weights. Moderately unstable and unstable zones appear as alternating bands with distinct linear extensions. These unstable areas are mainly distributed around Jiuquan–Zhangye–Wuwei, Xining–Haidong, Yushu–Garzê, Mianyang, and Chengdu. Statistically, stable, moderately stable, moderately unstable, and unstable zones account for 20.74%, 35.47%, 28.78%, and 15.01%, respectively. The results provide a scientific reference for regional planning and infrastructure site selection in tectonically active regions.
Bulk compressibility of reservoir rocks can be characterized dynamically or statically, and both vary with burial depth due to increasing temperature and pressure. To quantify these effects, cyclic hydrostatic compression tests are conducted on two reservoir sandstones under confining pressure up to 50 MPa at three temperatures (30 °C, 70 °C, and 110 °C). Experimental results show that static bulk compressibility is consistently larger than dynamic values across all tested conditions. As confining pressure increases, static compressibility decreases more sharply than dynamic compressibility, leading to a gradual reduction in their discrepancy. In contrast, temperature exerts a weaker yet more complex influence. Elevated temperature increases dynamic bulk compressibility, but has opposite effects on static compressibility upon loading versus unloading: it reduces static compressibility upon hydrostatic loading but enhances it upon unloading. This complex temperature dependence is attributed to thermally induced stress, which resists hydrostatic compression during loading but assists decompression during unloading. The influence of thermal stress is more pronounced at low confining pressures. These findings highlight that temperature not only alters the magnitude of static compressibility but also introduces path-dependent asymmetry between loading and unloading, which has important implications for reservoir geomechanics, subsidence prediction, and production-induced compaction in high-temperature environments.
The first electrical conductivity model determined beneath the InSight landing site is revisited in this study by performing a careful selection of magnetic records from the IFG dataset. This conductivity model is recalculated for the crust and the uppermost mantle (0–182 km depth), considering the data provided by this careful selection. In general, the present model shows a good agreement with synthetic models and other models calculated from magnetic data. In the present model, the conductivity of the crust is 0.0007 S/m, and the conductivity for the uppermost mantle coincides with that determined in the former paper. The crustal conductivity has been calculated for the first time beneath the InSight landing site. Better knowledge can be achieved when more accurate magnetic data are available.
The “Los Escudos” mural at the Late Postclassic site known as Tehuacán–Ndachjian in Puebla, Mexico, is relatively unknown within Mexico due to there being limited access to the site, which is situated underground on a mountain. This study describes the first unique opportunity to analyse mural painting samples on mud plaster from this archaeological site. Small, pigmented samples were analysed using optical microscopy, scanning electron microscopy, energy-dispersive X-ray spectroscopy, and X-ray diffraction. The compositional and structural characterisation of the samples revealed a stratigraphic composition without a lime plaster layer in addition to the presence of minerals, such as hematite, goethite, palygorskite, gypsum, and feldspars. These findings support the conclusion that the “tempera on earth” pictorial technique with mineral pigments was used to create the mural. The overall results provide valuable data concerning the types of materials and techniques that were used and serve as a reference for conservators in addressing preservation, conservation, and restoration issues for mural paintings on mud plaster. Furthermore, the study enhances understanding of ancient painting techniques on mud plaster and the technological advances that were developed by pre-Hispanic cultures in Mexico.
The Baraul Banda Formation preserves an important Paleocene–Eocene sedimentary record within the western Kohistan–Ladakh Arc (KLA) and provides new constraints on sediment provenance and tectonic evolution during the final stages of Neo-Tethyan closure. This study integrates stratigraphic observations, detrital zircon U-Pb geochronology, and quantitative provenance analyses to investigate sediment sources and basin development within the western India–Eurasia collision zone. The formation comprises a thick marine siliciclastic succession of conglomerate, sandstone, siltstone, mudstone, and slate deposited in a tectonically active forearc basin. Detrital zircon age spectra are dominated by Mesozoic–Cenozoic populations (48%) with major peaks at ~57–61 Ma, ~70 Ma, ~85–90 Ma, and ~114–115 Ma, accompanied by subordinate Neoproterozoic, Mesoproterozoic, Paleoproterozoic, and minor Archean populations. These age components closely resemble those of the KLA, Karakoram Block, and Lhasa Block. Statistical provenance analyses indicate the strongest affinity with Eurasian arc-related terranes and contemporaneous forearc basin deposits of the Tar and Indus groups, whereas affinity with Indian Plate sources is minor. The provenance record indicates that sediment supply was dominated by erosion of the KLA and the adjacent Karakoram–Lhasa continental margin, with only minor recycled contributions from Indian-derived sources. The youngest zircon populations constrain deposition to the Paleocene–Early Eocene and record rapid erosion of active arc terranes immediately prior to the India–KLA collision. Placed within the regional magmatic chronology, these results support initiation of the KLA by ca. 155 Ma, Late Cretaceous amalgamation with the Karakoram–Lhasa margin at ca. 80–70 Ma, and subsequent collision with India at ca. 60–55 Ma. The KLA therefore remained an active pre-India-collision arc system for approximately 95–100 Myr, whereas collision-related magmatism continued until ca. 40 Ma, extending its complete magmatic history to approximately 115 Myr.
Tsunami hazards in the Bay of Naples are primarily driven by submarine landslides, intense seismic activity, and volcanic phenomena from nearby systems like Vesuvius and the Campi Flegrei caldera. While localized historical tsunamis have occurred, they are generally rare events. Key tsunami sources include submarine landslides, volcanic eruptions, and seismicity. In this paper we provide a review of the tsunamis in Naples Bay within a general framework of Mediterranean tsunamis based on a literature review. Underwater avalanches, particularly around the steep slopes of the Dohrn Canyon and Ischia, are considered a primary localized threat. Scientific models indicate that a major collapse (like past events like the Ischia debris avalanche) could generate significant waves that could cross the bay in minutes. Explosive eruptions where magma meets seawater (such as PDCs—pyroclastic density currents) can displace water violently. This was famously documented during the AD 79 eruption of Mount Vesuvius, which created submarine ash fans and tsunami waves in the gulf. Earthquakes related to bradyseism in the Campi Flegrei or regional faults can also trigger sea level oscillations or localized tidal waves. Among the historical modeled events, we focus on the A.D. 79 eruption and on the 1343 Naples tsunami. The numerical simulations are revised. Depending on the source, the modeled waves vary from minor oscillations to heights of up to 6 m in canyon areas or over 20 m in nearby islands like Ischia.
The deep to ultra-deep sandstone reservoirs of the Cretaceous Bashijiqike Formation in the Kelasu structural belt of the Kuqa Depression exhibit strong heterogeneity. This study integrates single-well stress calculation, image log fracture interpretation, thin-section petrographic analysis, and porosity–permeability testing to compare stress, fracture, and reservoir characteristics across the Dabei–Bozi cross-section. The results show that the northern stress release zone is characterized by low SH (98 to 148 MPa) and E (9220 to 23,420 MPa), indicating weak cumulative stress, low effective fracture density (0.09 fractures/m), and primary-pore dominated reservoirs. The central stress transition zone has progressively increasing SH (136 to 187 MPa) and E (27,450 to 33,210 MPa) from north to south, indicating strong cumulative stress, high effective fracture density (0.31 fractures/m), and mixed primary–secondary pore-fracture reservoirs. The southern stress accumulation zone shows increasing SH but decreasing E to the south, indicating that the late-stage high stress results in low effective fracture density (0.08 fractures/m) and preserving primary pores. These results demonstrate that reservoir quality is governed by the cumulative effect of the stress field, rather than by present-day stress or peak paleo-stress alone. This reservoir distribution model could provide a theoretical basis for reservoir prediction in the foreland basin.
Landslide susceptibility mapping in alpine regions with limited data has two persistent obstacles: too few recorded landslide cases and the questionable reliability of non-landslide samples. We address these issues with a hybrid generative framework—a Variational Autoencoder (VAE) performs latent-space interpolation to produce additional positive samples, while a Conditional Diffusion Model (CDM) generates counterfactual negative samples. To validate generation quality, we used Principal Component Analysis (PCA) scatterplots, convex hull containment analysis, and covariance structure checks. The generated samples were then evaluated across five classifiers (Logistic Regression (LR), Random Forest (RF), Support Vector Machine (SVM), eXtreme Gradient Boosting (XGBoost), and The Convolutional Neural Network-Transformer-Long Short-Term Memory-Graph Convolutional Network (CTLGNet)). VAE-CDM consistently outperformed the original dataset, Synthetic Minority Over-sampling Technique (SMOTE), and Conditional Tabular Generative Adversarial Network (CTGAN), with XGBoost achieving the best results—Area Under the Curve (AUC) of 0.9337, recall of 0.91, and F1 of 0.87. DeLong’s test confirmed the AUC gain was statistically significant (p = 0.043). After augmentation, the very-high-susceptibility capture rate rose from 68.5% to 89.4%, while cumulative capture curves reflected a 4.9% improvement in spatial targeting efficiency. Shapley Additive Explanations (SHAP) analysis highlighted distance to roads, elevation, and the Freeze-Thaw Index (FTI) as the dominant controlling factors. Application to Southeastern Xizang shows the framework offers a viable pathway for susceptibility mapping in data-limited environments, although the generated samples show moderate diversity reduction (0.53) due to the interpolation-based generation strategy.
The Lacul fără nume landslide dam in the Vrancea Mountains (Romania) represents a unique example of a dynamic landslide dam system characterized by recurrent damming–breaching cycles. Through the combined use of remote sensing, field investigations, and historical reconstruction, eight such cycles were documented over a period of 49 years. To the best of current knowledge, this is one of the few documented landslide dams reported in the scientific literature that exhibits frequent damming–breaching episodes involving repeated dam failure, renewed slope instability, and subsequent re-damming with renewed lake impoundment over comparatively short timescales. The observed persistence and spatial extent of the associated lake are highly variable, ranging from 12 days to almost 10 years and from 23,920 m2 to 82,610 m2, respectively. Antecedent precipitation was frequently elevated prior to lake state transitions, but a seasonally constrained Monte Carlo analysis showed no significant departure from the climatic background, while numerous intense rainfall periods occurred without documented transitions. Similarly, no systematic temporal association was identified between recurrent lake state transitions and regional seismicity, although the initial dam formation coincided with the 1977 Mw 7.4 Vrancea earthquake. These findings suggest that precipitation conditions and seismicity alone cannot explain the recurrent damming and drainage, which likely result from interactions between hydrometeorological forcing, geomorphic processes, and human influences. Taken together, the results and the proposed conceptual model demonstrate that debris-flow-generated landslide dams can evolve into persistent and dynamic geomorphic systems capable of posing recurring hazards over multiple decades.
Geomechanical properties of rock are essential components in designing hydraulic fracturing procedures. Although ultrasonic measurement methods are usually utilized to obtain static geomechanical properties of rocks in the laboratory, they are limited to borehole locations. To obtain spatial distribution of these properties, a 3D prestack seismic inversion process is employed to derive them dynamically. However, 3D prestack seismic datasets are less readily available compared to 3D poststack seismic. We present a methodology that integrates 3D poststack seismic and wireline log data using a machine learning workflow to compute the dynamic geomechanical properties, namely Young’s modulus (E), Mu-Rho (MR), and brittleness (BRI) volumes, and generate crossplots to characterize the Salt Creek carbonate reservoir in the Midland Basin, Kent County, Texas. Our results show that: (1) Based on the comparison of seismically (dynamically) derived E and BRI maps with litho-facies maps, the zones with the highest porosity (oolites) are characterized by low E and low BRI. (2) Each of these properties is linearly related to the photoelectric factor (PEF) log, which can indicate porosity and calcite richness within a mixed carbonate–siliciclastic system. (3) In a mixed carbonate and siliciclastic system, geomechanical properties, especially E, can be used to identify rigid rock layers within the reservoir and deduce possible lithologies. Finally, when prestack seismic data are unavailable, our workflow offers a quick and inexpensive method to generate dynamic geomechanical property maps to characterize hydrocarbon reservoirs using poststack seismic data and well logs.
Rare metal exploration increasingly relies on the integration of heterogeneous geological datasets and advanced analytical methods to improve the efficiency and reliability of mineral prospecting. This study presents the development of a web-based Geographic Information System, Geospatial Information System for Optimized Rare Metal Exploration in Eastern Kazakhstan (GISORMEK), using the central part of the Kalba–Narym rare-metal belt (Eastern Kazakhstan) as a case study. A comprehensive geospatial database was developed through the digitization of archival geological maps and the integration of geological, geochemical, tectonic, geophysical, geomorphological, and mineral occurrence datasets. To complement historical mapping data, Landsat-8 multispectral imagery was incorporated to improve lithological discrimination and identify hydrothermal alteration zones. Two remote sensing techniques were applied: Principal Component Analysis (PCA) for lithological mapping and enhancement of geological features, and band ratio (BR) analysis for the calculation of geological spectral indices, including the iron oxide index and the hydroxyl-bearing (Al–OH) mineral index. The resulting spectral indices were subsequently integrated to generate a predictive hydrothermal alteration map. GISORMEK integrates historical and contemporary datasets within a unified web-GIS framework, ensuring spatial consistency, reproducibility, and accessibility. The proposed framework enhances the interpretation of the mineralization potential of the Kalba–Narym region and provides geospatial platform for supporting rare metal exploration and future mineral prospectivity assessments.
Open-water mapping of flooded areas using multispectral remote sensing still presents significant challenges, particularly in urban environments, where high spectral mixing leads to substantial commission and omission errors in water classifications. This study proposes FLOODISI (Flood Detection Integrating Spectral Water Indices), a framework that integrates multiple spectral water indices through adaptive thresholding to generate an Integrated Water Map (IWM). The method was applied to Landsat-8/OLI imagery to map an extreme flood event in southern Brazil. The approach evaluates 12 spectral indices and iteratively adjusts threshold values to minimize false positives while preserving true positives. The results indicate that the Normalized Difference Flood Index (NDFI2), using adaptive thresholding, achieved the best individual performance, with an overall accuracy of 91.8%, whereas the IWM increased this value to 93.5%, substantially reducing omission errors and improving open-water detection in urban areas. In comparison, the Random Forest classification achieved an overall accuracy of 95.0%, but exhibited similar precision and specificity, with a slight increase in commission errors and a modest reduction in omission errors relative to the IWM. In general, the integration of multiple spectral indices with adaptive thresholds through FLOODISI improved the robustness of open-water detection by reducing the dependence on individual spectral indices and providing a scalable, reproducible, and computationally efficient solution for rapid open-water mapping of flooded areas.
The spring floods that occurred in 2024 in western and northern Kazakhstan caused extensive damage. Our understanding of runoff formation processes under frozen-soil conditions remains limited. In this study, we apply a coupled hydrothermal model as a case study to explicitly simulate vertical heat and water transport, phase transitions, snow dynamics, and reduced infiltration capacity due to cryogenic pore blockage (ice-filled pores). The model is based on regular meteorological data from 65 stations in five regions covering the full hydrological cycle (August–May) of 2021 and 2024. A multilevel diagnostic check showed that soil temperature is reproduced with a median R2 of 0.962 and NSE of 0.888, the frozen/thawed surface condition corresponds to WMO (World Meteorological Organization) standards on approximately 91% of days, and water balance agreement reaches 86.2% (56 out of 65 stations). The model reflects the regional variability of the 2024 flood. In the northern regions (Kostanay, North Kazakhstan), snowfall was above average, and modeled runoff increased compared to 2021 (for example, at the Sergeevka station, it increased by a factor of four). In the western regions, the trends were mixed: the strongest relative increase in runoff was recorded in the Atyrau region (+119%), whilst in the West Kazakhstan region, the increase was more modest (+19%), and in the Aktobe region, runoff increased by 60%. The key mechanism—the time lag between rapid snowmelt and delayed soil thaw—is clearly evident: peaks in snowmelt occur when the soil remains frozen, infiltration capacity decreases, and the runoff potential index (RPI) exceeds 1 for extended periods. Although the model does not simulate the river channel, its ability to diagnose runoff generation conditions at the slope scale offers a diagnostic framework for identifying runoff-conducive conditions in regions with limited data, rather than a physically validated tool for flood-prone area identification. The results show that the 2024 flood period was characterized by abnormally high water inflow and hydrothermal conditions consistent with a temporal mismatch between water supply and the recovery of soil infiltration capacity. Because the RPI is a diagnostic indicator constructed from water input and infiltration capacity, these results should be interpreted as evidence of conditions conducive to runoff generation rather than as an independent causal verification of the flood mechanism.
The genesis of authigenic clay minerals in tight sandstones fundamentally controls reservoir quality and micro-pore evolution. This study investigates the differential formation mechanisms of authigenic chlorite and kaolinite and their modulating effects on pore systems in the Chang-8 Member tight sandstones, Ordos Basin. Thin-section petrography, X-ray diffraction, scanning electron microscopy, and high-pressure mercury injection were utilized to quantify mineralogical and petrophysical characteristics. Results show chlorite (averaging 4.8%) and kaolinite (averaging 1.6%) are the dominant authigenic clay minerals with distinct spatiotemporal distributions. Chlorite nucleated as pore linings during early diagenesis under alkaline, oligohaline to mesohaline conditions driven by volcanic material hydration. Conversely, kaolinite precipitated as pore-filling during mid-to-late diagenesis (80–120 °C), driven by organic acid pulses from underlying source rocks causing feldspar dissolution. We conclude that early chlorite linings constructively preserve primary porosity by mechanically resisting compaction and chemically inhibiting quartz cementation, despite narrowing pore throats. Meanwhile, kaolinite acts as a pore-type modulator, restructuring macro-pores into micro-intercrystalline pores, which significantly impairs permeability only when its proportion crosses a critical threshold. The diagenetic fluid transition from alkaline to acidic ultimately dictates this mineralogical succession and subsequent reservoir heterogeneity.
Ultra-deep Ordovician carbonates in the Tarim Basin are a major target for oil and gas exploration in China. Localized overpressure, however, creates substantial well-control risks and impairs drilling safety and exploration performance. This study investigates the Fudong Block of the Fuman Oilfield using drilling, seismic, and well-test data. We develop a high-resolution, layer-specific formation-pressure prediction workflow that integrates well and seismic data through a stress–fracture-pressure framework. The workflow combines geomechanical modeling, prediction of the in situ stress field and fracture distribution, stress-fracture matching, Biot-theory-based pressure prediction, and iterative calibration against drilling observations. The results show that: (1) overpressure is concentrated near secondary faults, branch faults, and NW-trending faults. It is jointly controlled by tectonic compression, pressure retention within fracture–vug bodies, and fluid charging. Multiple vertically separated pressure systems are common, and their marked heterogeneity is closely related to secondary-fault development and fracture–vug connectivity; (2) drilling disturbance can generate apparent overpressure and lead to erroneous pressure interpretation. Overpressured wells commonly exhibit a kick followed by lost circulation or simultaneous kick and loss. Drilling-fluid invasion into confined fracture–vug bodies causes pressure buildup; and (3) formation pressure is a key parameter in integrated geological and engineering sweet-spot evaluation and is closely linked to wellbore stability. Field applications confirm the accuracy of the proposed workflow. The method strengthens integrated geology-engineering evaluation and provides a practical basis for the safe and efficient development of ultra-deep carbonate reservoirs.
