Search Results (702)

Accurate prediction of landslide-induced displacement is essential for the structural integrity and operational safety of buildings and infrastructure situated in geologically unstable regions. This study introduces a novel hybrid predictive framework that synergistically integrates Gaussian Process Regression (GPR) with Temporal Convolutional Neural Networks (TCNs), herein referred to as the GTCN model, to forecast displacement at building monitoring points subject to landslide activity. The proposed methodology is validated using time-series monitoring data collected from the slope adjacent to the Zhongliang Reservoir in Wuxi County, Chongqing, an area where slope instability poses a significant threat to nearby structural assets. Experimental results demonstrate the GTCN model’s superior predictive performance, particularly under challenging conditions of incomplete or sparsely sampled data. The model proves highly effective in accurately characterizing both abrupt fluctuations within the displacement time series and capturing long-term deformation trends. Furthermore, the GTCN framework outperforms comparative hybrid models based on Gated Recurrent Units (GRUs) and GPR, with its advantage being especially pronounced in data-limited scenarios. It also exhibits enhanced capability for temporal feature extraction relative to conventional imputation-based forecasting strategies like forward-filling. By effectively modeling both nonlinear trends and uncertainty within displacement sequences, the GTCN framework offers a robust and scalable solution for landslide-related risk assessment and early warning applications. Its applicability to building safety monitoring underscores its potential contribution to geotechnical hazard mitigation and resilient infrastructure management. Full article

Reservoir-induced landslides threaten infrastructures and downstream communities, making continuous deformation monitoring vital. Time-series InSAR, notably the SBAS algorithm, provides high-precision surface-displacement mapping but suffers from voids due to layover/shadow effects and temporal decorrelation. Existing deep-learning approaches often operate on fixed-size patches or ignore irregular spatio-temporal dependencies, limiting their ability to recover missing pixels. With this objective, a hybrid spatio-temporal Graph Attention (ST-GAT) framework was developed and trained on SBAS-InSAR values using 24 influential features. A unified spatio-temporal graph is constructed, where each node represents a pixel at a specific acquisition time. The nodes are connected via inverse distance spatial edges to their K-nearest neighbors, and they have bidirectional temporal edges to themselves in adjacent acquisitions. The two spatial GAT layers capture terrain-driven influences, while the two temporal GAT layers model annual deformation trends. A compact MLP with per-map bias converts the fused node embeddings into normalized LOS estimates. The SBAS-InSAR results reveal LOS deformation, with 48% of missing pixels and 20% located near the Dasu dam. ST D-GAT reconstructed fully continuous spatio-temporal displacement fields, filling voids at critical sites. The model was validated and achieved an overall R² (0.907), ρ (0.947), per-map R² ≥ 0.807 with RMSE ≤ 9.99, and a ROC-AUC of 0.91. It also outperformed the six compared baseline models (IDW, KNN, RF, XGBoost, MLP, simple-NN) in both RMSE and R². By combining observed LOS values with 24 covariates in the proposed model, it delivers physically consistent gap-filling and enables continuous, high-resolution landslide monitoring in radar-challenged mountainous terrain. Full article

Early warning systems depend heavily on the accuracy of landslide displacement forecasts. This study focuses on the Bazimen landslide located in the Three Gorges Reservoir region and proposes a hybrid prediction approach combining support vector regression (SVR) and long short-term memory (LSTM) networks. These models are optimized via the K-Nearest Neighbor (KNN) algorithm. Initially, cumulative displacement data were separated into trend and cyclic elements using a smoothing approach. SVR and LSTM were then used to predict the components, and KNN was introduced to optimize input factors and classify the results, improving accuracy. The final KNN-optimized SVR-LSTM model effectively integrates static and dynamic features, addressing limitations of traditional models. The results show that LSTM performs better than SVR, with an RMSE and MAPE of 24.73 mm and 1.87% at monitoring point ZG111, compared to 30.71 mm and 2.15% for SVR. The sequential hybrid model based on KNN-optimized SVR and LSTM achieved the best performance, with an RMSE and MAPE of 23.11 mm and 1.68%, respectively. This integrated model, which combines multiple algorithms, offers improved prediction of landslide displacement and practical value for disaster forecasting in the Three Gorges area. Full article

This paper presents a formulation for the dynamic analysis of dam–reservoir–foundation systems, employing a coupled finite element model that integrates displacements and reservoir pressures. An innovative coupled approach, without separating the solid and fluid equations, is proposed to directly solve the single non-symmetrical governing equation for the whole system with non-proportional damping. For the modal analysis, a state–space method is adopted to solve the coupled eigenproblem, and complex eigenvalues and eigenvectors are computed, corresponding to non-stationary vibration modes. For the seismic analysis, a time-stepping method is applied to the coupled dynamic equation, and the stress–transfer method is introduced to simulate the nonlinear behavior, innovatively combining a constitutive joint model and a concrete damage model with softening and two independent scalar damage variables (tension and compression). This formulation is implemented in the computer program DamDySSA5.0, developed by the authors. To validate the formulation, this paper provides the experimental and numerical results in the case of the Cahora Bassa dam, instrumented in 2010 with a continuous vibration monitoring system designed by the authors. The good comparison achieved between the monitoring data and the dam–reservoir–foundation model shows that the formulation is suitable for simulating the modal response (natural frequencies and mode shapes) for different reservoir water levels and the seismic response under low-intensity earthquakes, using accelerograms measured at the dam base as input. Additionally, the dam’s nonlinear seismic response is simulated under an artificial accelerogram of increasing intensity, showing the structural effects due to vertical joint movements (release of arch tensions near the crest) and the concrete damage evolution. Full article

Due to the complex mineral composition, low clay content, and strong heterogeneity of the mixed sedimentary shale in the Xinjiang Salt Lake Basin, the wettability characteristics of the reservoir and their influencing factors are not yet clear, which restricts the evaluation of oil-bearing properties and the identification of sweet spots. This paper analyzed mixed sedimentary shale samples from the Lucaogou Formation of the Jimsar Sag and the Fengcheng Formation of the Mahu Sag. Methods such as petrographic thin sections, X-ray diffraction, organic matter content analysis, and argon ion polishing scanning electron microscopy were used to examine the lithological and mineralogical characteristics, geochemical characteristics, and pore space characteristics of the mixed sedimentary shale reservoir. Alternating imbibition and nuclear magnetic resonance were employed to quantitatively characterize the wettability of the reservoir and to discuss the effects of compositional factors, lamina types, and pore structure on wettability. Research findings indicate that the total porosity, measured by the alternate imbibition method, reached 72% of the core porosity volume, confirming the effectiveness of alternate imbibition in filling open pores. The Lucaogou Formation exhibits moderate to strong oil-wet wettability, with oil-wet pores predominating and well-developed storage spaces; the Fengcheng Formation has a wide range of wettability, with a higher proportion of mixed-wet pores, strong heterogeneity, and weaker oil-wet properties compared to the Lucaogou Formation. TOC content has a two-segment relationship with wettability, where oil-wet properties increase with TOC content at low TOC levels, while at high TOC levels, the influence of minerals such as carbonates dominates; carbonate content shows an “L” type response to wettability, enhancing oil-wet properties at low levels (<20%), but reducing it due to the continuous weakening effect of minerals when excessive. Lamina types in the Fengcheng Formation significantly affect wettability differentiation, with carbonate-shale laminae dominating oil pores, siliceous laminae contributing to water pores, and carbonate–feldspathic laminae forming mixed pores; the Lucaogou Formation lacks significant laminae, and wettability is controlled by the synergistic effects of minerals, organic matter, and pore structure. Increased porosity strengthens oil-wet properties, with micropores promoting oil adsorption through their high specific surface area, while macropores dominate in terms of storage capacity. Wettability is the result of the synergistic effects of multiple factors, including TOC, minerals, lamina types, and pore structure. Based on the characteristic that oil-wet pores account for up to 74% in shale reservoirs (mixed-wet 12%, water-wet 14%), a wettability-targeted regulation strategy is implemented during actual shale development. Surfactants are used to modify oil-wet pores, while the natural state of water-wet and mixed-wet pores is maintained to avoid interference and preserve spontaneous imbibition advantages. The soaking period is thus compressed from 30 days to 3–5 days, thereby enhancing matrix displacement efficiency. Full article

Based on a detailed investigation of the geological setting of coalbed methane by previous work in the Xiangzhong Depression, Hunan Province, numerical simulation methods were used to simulate the geological storage of carbon dioxide and displacement gas production in this area. In this simulation, a 400 m × 400 m square well group was constructed for coalbed methane production, and a carbon dioxide injection well was arranged in the center of the well group. Injection storage and displacement gas production simulations were carried out under the conditions of original permeability and 1 mD permeability. At the initial permeability (0.01 mD), carbon dioxide is difficult to inject, and the production of displaced and non-displaced coalbed methane is low. During the 25-year injection process, the reservoir pressure only increased by 7 MPa, and it is difficult to reach the formation fracture pressure. When the permeability reaches 1 mD, the carbon dioxide injection displacement rate can reach 4000 m³/d; the cumulative production of displaced and non-displaced coalbed methane is 7.83 × 10⁶ m³ and 9.56 × 10⁵ m³, respectively, and the average daily production is 1430 m³/d and 175 m³/d. The displacement effect is significantly improved compared to the original permeability. In the later storage stage, the carbon dioxide injection rate can reach 8000 m³/d, reaching the formation rupture pressure after 3 years, and the cumulative carbon dioxide injection volume is 1.17 × 10⁷ m³. This research indicates that permeability has a great impact on carbon dioxide geological storage. During the carbon dioxide injection process, selecting areas with high permeability and choosing appropriate reservoir transformation measures to enhance permeability are key factors in increasing the amount of carbon dioxide injected into the area. Full article

China has abundant shale oil and gas resources, which have become a critical pillar for future energy substitution. However, due to the highly heterogeneous nature and complex pore structures of shale reservoirs, traditional plugging agents face significant limitations in enhancing plugging efficiency and adapting to extreme wellbore environments. In response to the technical demands of nanoparticle-based plugging in shale reservoirs, this study systematically investigated the microscopic interaction mechanisms of nano-plugging agent shell polymers (Ployk) with various reservoir minerals under different temperature and salinity conditions using molecular simulation methods. Key parameters, including interfacial interaction energy, mean square displacement, and system density distribution, were calculated to thoroughly analyze the effects of temperature and salinity variations on adsorption stability and structural evolution. The results indicate that nano-plugging agent shell polymers exhibit pronounced mineral selectivity in their adsorption behavior, with particularly strong adsorption performance on SiO₂ surfaces. Both elevated temperature and increased salinity were found to reduce the interaction strength between the shell polymers and mineral surfaces and significantly alter the spatial distribution and structural ordering of water molecules near the interface. These findings not only elucidate the fundamental interfacial mechanisms of nano-plugging agents in shale reservoirs but also provide theoretical guidance for the precise design of advanced nano-plugging agent materials, laying a scientific foundation for improving the engineering application performance of shale oil and gas wellbore-plugging technologies. Full article

Deep saline aquifers in the eastern part of Drava Basin were screened for potential storage sites. The input dataset included three seismic volumes, a rather extensive set of old seismic sections and 71 wells. Out of all identified potential storage objects, only two sites were found to be situated in the favorable geological settings, meaning that the inspected wells drilled through structural traps had a seal at least 20 m thick which was intersected by only a few faults with rather limited displacement. Many more closed structures in the area were tested by exploration wells, but in all other wells, various problems were encountered, including inadequate reservoir properties, inadequate seal or inadequate depth of the identified trap. Analysis was highly affected by the insufficient quality and spatial distribution of the seismic input data, as well as in places with insufficient quality of input well datasets. An initial characterization of identified storage sites was performed, and their attributes were compared, with potential storage object B recognized as the one that should be further developed. However, given the depth and increased geothermal gradient of the potential storage object B, it is possible that it will be developed as a geothermal reservoir, and this brings forward the problem of concurrent subsurface use. Full article

In tight sandstone gas reservoirs, proppant flowback severely limits stable gas production. This study uses laboratory flowback experiments and field analyses of the ShaXimiao tight sandstone in the Wenxing gas area to investigate the mechanisms controlling sand production. The experiments show that displacing fluid viscosity significantly affects the critical sand-flow velocity: with high-viscous slickwater (5 mPa·s), the critical velocity is 66% lower than with low-viscous formation water (1.15 mPa·s). The critical velocity for coated proppant is three times that of the mixed quartz sand and coated proppant. If the confining pressure is maintained, but the flow rate is further increased after the proppant flowback, a second instance of sand production can be observed. X-ray diffraction (XRD) tests were conducted for sand produced from practical wells to help find the sand production reasons. Based on experimental and field data analysis, sand production in Well X-1 primarily results from proppant detachment during rapid shut-in/open cycling operations, while in Well X-2, it originates from proppant crushing. The risk of formation sand production is low for both wells (the volumetric fraction of calcite tested from the produced sands is smaller than 0.5%). These findings highlight the importance of fluid viscosity, proppant consolidation, and pressure management in controlling sand production. Full article

Due to factors such as low porosity and permeability, thin sand body thickness, and strong interlayer heterogeneity, the fluid flow in the tight reservoir (beach-bar sandstone reservoir) exhibits obvious nonlinear seepage characteristics. Considering the time-varying physical parameters of different types of sand bodies, a nonlinear seepage coefficient is derived based on permeability and capillary force, and a low-velocity nonlinear seepage model for beach bar sand reservoirs is established. Based on core displacement experiments of different types of sand bodies, the low-velocity nonlinear seepage coefficient was fitted and numerical simulation of low-velocity nonlinear seepage in beach-bar sandstone reservoirs was carried out. The research results show that the displacement pressure and flow rate of low-permeability tight reservoirs exhibit a significant nonlinear relationship. The lower the permeability and the smaller the displacement pressure, the more significant the nonlinear seepage characteristics. Compared to the bar sand reservoir, the water injection pressure in the tight reservoir of the beach sand is higher. In the nonlinear seepage model, the bottom hole pressure of the water injection well increases by 10.56% compared to the linear model, indicating that water injection is more difficult in the beach sand reservoir. Compared to matrix type beach sand reservoirs, natural fractures can effectively reduce the impact of fluid nonlinear seepage characteristics on the injection and production process of beach sand reservoirs. Based on the nonlinear seepage characteristics, the beach-bar sandstone reservoir can be divided into four flow zones during the injection production process, including linear seepage zone, nonlinear seepage zone, non-flow zone affected by pressure, and non-flow zone not affected by pressure. The research results can effectively guide the development of beach-bar sandstone reservoirs, reduce the impact of low-speed nonlinear seepage, and enhance oil recovery. Full article

Enhanced oil recovery (EOR) via CO₂ flooding is a promising strategy for improving hydrocarbon recovery and carbon sequestration, yet the influence of pH on solid–liquid interfacial interactions in quartz-dominated reservoirs remains poorly understood. This study employs molecular dynamics (MD) simulations to investigate the pH-dependent adsorption behavior of crude oil components on quartz surfaces and its impact on CO₂ displacement mechanisms. Three quartz surface models with varying ionization degrees (0%, 9%, 18%, corresponding to pH 2–4, 5–7, and 7–9) were constructed to simulate different pH environments. The MD results reveal that aromatic hydrocarbons exhibit significantly stronger adsorption on quartz surfaces at high pH, with their maximum adsorption peak increasing from 398 kg/m³ (pH 2–4) to 778 kg/m³ (pH 7–9), while their alkane adsorption peaks decrease from 764 kg/m³ to 460 kg/m³. This pH-dependent behavior is attributed to enhanced cation–π interactions that are facilitated by Na⁺ ion aggregation on negatively charged quartz surfaces at high pH, which form stable tetrahedral configurations with aromatic molecules and surface oxygen ions. During CO₂ displacement, an adsorption–stripping–displacement mechanism was observed: CO₂ first forms an adsorption layer on the quartz surface, then penetrates the oil phase to induce the detachment of crude oil components, which are subsequently displaced by pressure. Although high pH enhances the Na⁺-mediated weakening of oil-surface interactions, which leads to a 37% higher diffusion coefficient (8.5 × 10⁻⁵ cm²/s vs. 6.2 × 10⁻⁵ cm²/s at low pH), the tighter packing of aromatic molecules at high pH slows down the displacement rate. This study provides molecular-level insights into pH-regulated adsorption and CO₂ displacement processes, highlighting the critical role of the surface charge and cation–π interactions in optimizing CO₂-EOR strategies for quartz-rich reservoirs. Full article

Narrative review synthesizes the most current literature on the SARS-CoV-2 XEC variant, focusing on its genomic evolution, immune evasion characteristics, epidemiological dynamics, and public health implications. To achieve this, we conducted a structured search of the literature of peer-reviewed articles, preprints, and official surveillance data from 2023 to early 2025, prioritizing virological, clinical, and immunological reports related to XEC and its parent lineages. Defined by the distinctive spike protein mutations, T22N and Q493E, XEC exhibits modest reductions in neutralization in vitro, although current evidence suggests that mRNA booster vaccines, including those targeting JN.1 and KP.2, retain cross-protective efficacy against symptomatic and severe disease. The XEC strain of SARS-CoV-2 has drawn particular attention due to its increasing prevalence in multiple regions and its potential to displace other Omicron subvariants, although direct evidence of enhanced replicative fitness is currently lacking. Preliminary analyses also indicated that glycosylation changes at the N-terminal domain enhance infectivity and immunological evasion, which is expected to underpin the increasing prevalence of XEC. The XEC variant, while still emerging, is marked by a unique recombination pattern and a set of spike protein mutations (T22N and Q493E) that collectively demonstrate increased immune evasion potential and epidemiological expansion across Europe and North America. Current evidence does not conclusively associate XEC with greater disease severity, although additional research is required to determine its clinical relevance. Key knowledge gaps include the precise role of recombination events in XEC evolution and the duration of cross-protective T-cell responses. New research priorities include genomic surveillance in undersampled regions, updated vaccine formulations against novel spike epitopes, and long-term longitudinal studies to monitor post-acute sequelae. These efforts can be augmented by computational modeling and the One Health approach, which combines human and veterinary sciences. Recent computational findings (GISAID, 2024) point to the potential of XEC for further mutations in under-surveilled reservoirs, enhancing containment challenges and risks. Addressing the potential risks associated with the XEC variant is expected to benefit from interdisciplinary coordination, particularly in regions where genomic surveillance indicates a measurable increase in prevalence. Full article

To investigate the energy conduction behavior of polymer gel profile control and flooding in low-permeability reservoirs, a parallel dual-tube displacement experiment was conducted to simulate reservoirs with different permeability ratios. Injection schemes included constant rates from 0.40 to 1.20 mL/min and dynamic injection from 1.20 to 0.40 mL/min. Pressure monitoring and shunt analysis were used to evaluate profile control and recovery performance. The results show that polymer gel preferentially enters high-permeability layers, transmitting pressure more rapidly than in low-permeability zones. At 1.20 mL/min, pressure onset at 90 cm in the high-permeability layer occurs earlier than in the low-permeability layer. Higher injection rates accelerate pressure buildup. At 0.80 mL/min, permeability contrast is minimized, achieving a 22.96% recovery rate in low-permeability layers. The combination effect of 1.2–0.4 mL/min is the best in dynamic injection, with the difference in shunt ratio of 9.6% and the recovery rate of low permeability layer increased to 31.23%. Polymer gel improves oil recovery by blocking high-permeability channels, expanding the swept volume, and utilizing viscoelastic properties. Full article

In the development of high-temperature and high-salinity oil fields, biopolymer scleroglucan flooding technology faces significant challenges. Traditional scleroglucan products exhibit poor injectability and high extraction costs. This study investigated the application potential of the original fermentation broth of exopolysaccharides (EPS) produced by microorganisms in a simulated high-temperature and high-salinity oil reservoir environment. The polysaccharide was identified as scleroglucan through IR and NMR analysis. Its stability and rheological properties were comprehensively evaluated under extreme conditions, including temperatures up to 150 °C, pH levels ranging from 1 to 13, and salinities up to 22 × 10⁴ mg/L. The results demonstrated that EPS maintained excellent viscosity and stability, particularly at 76.6 °C and 22 × 10⁴ mg/L salinity, where its viscosity remained above 80% for 35 days. This highlights its significant viscoelasticity and stability in high-temperature and high-salinity oil reservoirs. Additionally, this study, for the first time, examined the rheological properties of the original fermentation broth of scleroglucan, specifically assessing its injectability and enhanced oil recovery (EOR) performance in a simulated Middle Eastern high-temperature, high-salinity, medium-low permeability reservoir environment. The findings revealed an effective EOR exceeding 15%, confirming the feasibility of using the original fermentation broth as a biopolymer for enhancing oil recovery in extreme reservoir conditions. Based on these experimental results, it is concluded that the original fermentation broth of Athelia rolfsii exhibits superior performance under high-temperature and high-salinity conditions in medium–low permeability reservoirs, offering a promising strategy for future biopolymer flooding in oil field development. Full article

In order to improve oil recovery efficiency in low-permeability reservoirs, this study developed amphiphilic Janus-SiO₂ nanoparticles to prepare polymer gel microspheres for enhanced oil recovery (EOR). Firstly, Janus-SiO₂ nanoparticles were synthesized via surface modification using (3-aminopropyl)triethoxysilane and α-bromoisobutyryl bromide. Fourier-transform infrared spectroscopy (FTIR) and scanning electron microscopy (SEM) characterization confirmed the successful grafting of amino and styrene chains, with the particle size increasing from 23.8 nm to 32.9 nm while maintaining good dispersion stability. The Janus nanoparticles exhibited high interfacial activity, reducing the oil–water interfacial tension to 0.095 mN/m and converting the rock surface wettability from oil-wet (15.4°) to strongly water-wet (120.6°), thereby significantly enhancing the oil stripping efficiency. Then, polymer gel microspheres were prepared by reversed-phase emulsion polymerization using Janus-SiO₂ nanoparticles as emulsifiers. When the concentration range of nanoparticles was 0.1–0.5 wt%, the particle size range of polymer gel microspheres was 316.4–562.7 nm. Polymer gel microspheres prepared with a high concentration of Janus-SiO₂ nanoparticles can ensure the moderate swelling capacity of the particles under high-temperature and high-salinity conditions. At the same time, it can also improve the mechanical strength and shear resistance of the microspheres. Core displacement experiments confirmed the dual synergistic effect of this system. Polymer gel microspheres can effectively plug high-permeability zones and improve sweep volume, while Janus-SiO₂ nanoparticles enhance oil displacement efficiency. Ultimately, this system achieved an incremental oil recovery of 19.72%, exceeding that of conventional polymer microsphere systems by more than 5.96%. The proposed method provides a promising strategy for improving oil recovery in low-permeability heterogeneous reservoir development. Full article