With the rapid development of marine engineering and the increasing frequency of extreme weather events, the risk of coastal landslides has increased significantly. However, existing studies on landslide susceptibility and zoning primarily focus on inland mountainous regions, and systematic research on coastal landslide susceptibility remains insufficient.

In this study, the coastal zone of Fujian Province was selected as the study area. Historical data on coastal landslides were collected, and a susceptibility assessment indicator system suitable for coastal landslides was established using the information gain ratio method and Pearson correlation coefficient method. Particle swarm optimization support vector machine (PSO-SVM) and random forest (RF) were used as base learners to construct a stacking heterogeneous ensemble learning model. This model was then used to conduct the susceptibility assessment and zoning of coastal landslides in Fujian Province, and the effects of different training-to-testing ratios on the prediction accuracy of the heterogeneous ensemble model were examined.

The comparison results demonstrated that the stacking model performed optimally when the training-to-testing ratio was 70:30, achieving an accuracy of 0.869, a precision of 0.842, a recall of 0.909, and an F1 score of 0.874. Compared with other models, the accuracy, precision, and F1 score improved by up to 0.198, 0.227, and 0.140, respectively. In addition, the area under the curve (AUC) value was 0.938, which was 0.019 to 0.216 higher than that of the other models.

The findings indicate that the stacking heterogeneous ensemble model exhibits strong applicability and superior performance in susceptibility assessment of coastal landslides.

The Qizhou Islands, located on the east side of Hainan Island, is an area with a high risk of geohazards due to the influence of tectonic processes (e.g., active fault zones and the Hainan mantle plume) and related earthquakes. The southern part of the Qizhou Islands is close to the edge of the continental shelf, with well-developed canyons and ancient channels, which weaken seabed stability and threaten the safety of engineering facilities in the area. Therefore, studying marine geohazards is of great significance for disaster prevention and mitigation in the Qizhou Islands area. However, research on geohazards in the sea area is limited, and the development characteristics of geohazard elements are unclear.

To clarify the potential risks of marine geohazards in the offshore Qizhou Islands,

based on 2D seismic data,

this study identified six geohazard elements (volcanoes, faults, shallow gas, mass-transport deposits (MTDs), canyons, and channels) offshore from the Qizhou Islands. According to their quantity, scale, and distribution characteristics, three risk levels (low risk, medium risk, and high risk) were assigned to 12 blocks.

Combined with the geomorphological and tectonic characteristics, suggestions for geohazard prevention and control were proposed for the offshore Qizhou Islands area.

Many large underground caverns in China will adopt a multi-stage construction method, and the expansion of underground caverns may have a certain impact on the seepage field of similar caverns near operation, potentially leading to a series of safety accidents such as oil and gas leakage. Therefore, ensuring the safety of the water seal after expansion is of critical importance.

In this paper, aimed at addressing this problem, the geological conditions and fracture distribution characteristics of the reservoir site area are analyzed based on a large underground cavern expansion project. Considering the joint dense zone connecting the two-stage caverns, and based on the field hydrological test results, the equivalent opening of the fracture is inverted. A simplified model of the two-stage underground caverns is then established using the random fracture network (DFN) approach. The water seal safety of the expanded underground caverns is studied, along with the influence of the expanded caverns on the water seal safety of the operating caverns.

The research shows that the expanded caverns have no effect on the water seal safety of the operating caverns, but the joint dense zone will seriously affect the water seal safety of the expanded caverns. Through the study of the influence factors of the expansion of the oil depot on the water seal safety of the adjacent operating oil depot, it is determined that the minimum safety distance between the caverns is 200 m, and the vertical and horizontal water curtain pressures are set to 0.4 MPa. These settings can guarantee the water seal safety of both the expanded and operating caverns.

Therefore, for large-scale underground cavern expansion projects, the joint dense zone is the key factor affecting water seal safety. Ensuring a minimum safety distance and appropriate water curtain pressure can effectively ensure the safety of both the expanded and operating caverns. The results provide a theoretical basis for studying water seal safety in the expansion of large underground caverns.

CO₂ flooding is an important method to improve the recovery efficiency of tight oil reservoirs. However, the diagenesis of tight sandstones is complex, and it is necessary to clarify the mechanisms behind the microstructural changes in tight sandstones with different cement characteristics during the CO₂ flooding process.

In this study, CO₂ flooding, casting thin sections, scanning electron microscopy, nuclear magnetic resonance, and X-ray diffraction were used to investigate the changes in pore structure and mineral composition of tight sandstone before and after CO₂ flooding.

The results show that the cementation of tight sandstone is complex and diverse. Clay minerals and carbonates are the main filling materials, with significant distribution differences. Cements can affect the mineralogical structure of tight sandstone and its structural impact on pore morphology. After CO₂ flooding, the increase in porosity of the tight sandstone is 0.55%, the increase in permeability is 21.5%, and the relative selectivity coefficient decreases by only 0.01, indicating that CO₂ flooding can increase the porosity and permeability of the reservoir, but has a weak impact on the heterogeneity of the pore structure. During CO₂ flooding, feldspar and carbonates are dissolved, resulting in the precipitation of quartz and clay minerals. In tight sandstone with high clay content, CO₂ dissolution is dispersed, and the newly precipitated minerals and exfoliation of skeleton particles during CO₂ flooding can block pores, leading to a slight improvement in properties. In tight sandstone with high calcite content, extensive dissolution of calcite can create new storage spaces and flow paths, significantly improving the properties of tight sandstone after CO₂ flooding.

Therefore, CO₂ flooding has different effects on the pore structure of tight sandstones with varying types of cement. CO₂ flooding leads to a more significant improvement in the physical properties of tight sandstones with high carbonate content compared to those with high clay content. These results provide new insights for the development and evaluation of tight sandstone reservoirs.

CO₂-enhanced oil recovery (CO₂-EOR) is currently one of the most widely used techniques for oilfield production enhancement and carbon sequestration worldwide. Under the "dual carbon" goals, numerical simulation of CO₂-EOR needs to consider the impact of interphase mass transfer of the non-independent water phase to accurately depict the multiphase dissolution distribution of CO₂.

Based on the actual reservoir conditions of the 3^rd member of the Funing Formation in the Zhangjiaduo Oilfield, Subei Basin, this study uses the multiphase flow numerical simulation software TOGA to establish a core displacement model, achieving three-phase full-component mutual solubility simulation. By simulating the interaction between CO₂ and reservoir fluids under different pressures and gas injection rates, the differences in CO₂ solubility in water, gas, and oil phases under the reservoir conditions of the study area are characterized, revealing the miscible flooding mechanism.

The simulation results indicate that the minimum miscible pressure for miscible flooding in the study area is 30 MPa, at which the oil-gas interfacial tension approaches zero. Miscible displacement significantly improves oil recovery, with recovery rates of 80% and 52% under confining pressures of 38 MPa and 10 MPa, respectively. CO₂ solubility in the oil phase is much greater than in the water phase, and with increasing confining pressure, the mole fraction of CO₂ in both oil and water phases increases. At confining pressures of 22 MPa and 38 MPa, the mole fractions of CO₂ migrating in the water phase are 1.8% and 2.1%, respectively, while those in the oil phase are 65% and 80%, respectively.

The reservoir conditions in the study area can achieve miscible flooding, which is also conducive to carbon sequestration. Accelerating the gas injection rate can improve production efficiency, but it has little effect on total oil recovery and carbon dioxide storage, and may increase the risk of gas breakthrough. This study provides technical references for field simulations and leakage risk assessments of the 3rd member of the Funing Formation, Zhangjiaduo Oilfield.

As an important source of drinking water, abnormal calcium (Ca) concentrations in groundwater could endanger human growth and lead to health risks. Previous research has primarily focused on how inorganic carbonate equilibrium processes involving atmospheric CO₂ regulate groundwater Ca cycling. However, the important role of the organic carbon pool has been overlooked, and the microscopic mechanisms underlying the interactions between different components of organic matter (OM) and Ca remain elusive.

This study took the paleo-channel area along the middle reaches of the Yangtze River as the study area. Groundwater samples were analyzed using hydrochemical analysis, principal component analysis, parallel factor analysis (PARAFAC) of fluorescence excitation-emission matrix (EEM) spectroscopy, and fluorescence excitation-emission matrix regional integration.

The results demonstrated that groundwater Ca concentrations exhibited significant spatial heterogeneity, ranging from 111 to 213 mg/L, mainly concentrated in the meanders and oxbow lakes of the paleo-channel region. Greater OM content was observed in the groundwater with elevated Ca concentration, and the two exhibited similar spatial distribution patterns. In the study area, the EEM-PARAFAC model identified three major components in groundwater, including protein-like components (C1), microbial and terrestrial humic components (C2 and C3).

With the increase of Ca concentration in groundwater, the content of protein-like components decreased while that of the humic-like components increased. Notably, the abundant organic matter buried in the paleo-channel area provides a strong reducing environment that favors the degradation of protein-like organic matter. This process promotes the dissolution of Ca-bearing minerals, which contributes to the groundwater Ca enrichment. This research investigated the heterogeneous spatial distribution and occurrence environments of Ca in groundwater, characterized differences in organic matter composition among groundwater with different Ca concentrations, and revealed the mechanisms by which organic matter influenced the migration and enrichment of Ca in groundwater.

Characterizing the spatial distribution of the regional groundwater table is critical for effective groundwater management and pollution control. However, the limited number and uneven distribution of observation wells in many regions, including Jiangsu Province, China, make it difficult for traditional interpolation or physically based numerical models to provide reliable predictions. Interpolation methods such as Kriging depend heavily on well coverage, which restricts their applicability in data-scarce areas, while numerical models require large amounts of hydrogeological parameters and boundary conditions that are often unavailable in practice.

To address these limitations, this study develops a machine learning–based framework that integrates multi-source data, including elevation, vegetation coverage, rainfall, distance from surface water, land surface temperature, and soil moisture. A dataset of 953 groundwater observations collected during the dry season, complemented by surface water levels and published measurements, was compiled and standardized. A deep neural network (DNN) was trained using 80% of the data, validated on 10%, and tested on the remaining 10%.

The model achieved a determination coefficient (R²) of 0.91 on the test dataset, substantially outperforming ordinary Kriging (R² = 0.63). The predicted groundwater table maps revealed clear large-scale patterns consistent with hydrogeological understanding, including a west-to-east flow gradient and discharge into the Yangtze River, Taihu Lake, and the East China Sea. Compared with nationwide groundwater models, the proposed approach provided finer spatial resolution and captured more local flow features. Validation in three representative demonstration areas-a coastal industrial park, a riverside development zone, and a cross-hydrogeological unit—confirmed that predicted groundwater flow directions matched observed values, even where monitoring wells were sparse. To enhance interpretability, Shapley additive explanations (SHAP) analysis was applied, which revealed that land surface temperature, vegetation cover, and distance to surface water exerted dominant influences at the provincial scale, while site-specific analyses emphasized the importance of local hydrological connectivity.

Overall, the machine learning framework developed in this study provides an efficient and scalable tool for estimating groundwater table distributions in data-limited regions. By integrating diverse environmental factors, the approach improves predictive accuracy, enhances spatial resolution of groundwater flow mapping, and offers insights into governing controls. The results highlight the potential of combining big data and artificial intelligence methods to support groundwater monitoring optimization, regional environmental impact assessments, and sustainable water resource management.

Electron transfer is fundamental to biogeochemical reactions in subsurface environments. Sediments act as key electron reservoirs capable of cyclic electron storage and release under groundwater level fluctuations, thereby significantly influencing material transformation and elemental cycling. However, the patterns and mechanisms governing sediment charging and discharging driven by groundwater level fluctuations remain poorly understood.

In this study, a one-dimensional soil column system was developed to simulate the groundwater fluctuation zone. The patterns and mechanisms of sediment charging and discharging driven by groundwater level fluctuations were investigated using a combination of chemical analyses, iron mineral speciation, and molecular biological techniques.

The results showed that under short-cycle fluctuation conditions, sediments completed two charging-discharging cycles, with maximum charge/discharge capacities of 2.3, 8 μmol e⁻·g⁻¹, and peak rates of 0.577, 2.012 μmol e⁻·g⁻¹·d⁻¹, respectively. The electron donating capacity (EDC) of the sediments was mainly contributed by adsorbed, ion-exchangeable, and highly reactive weakly crystalline Fe(Ⅱ). Water level fluctuations drove microbial Fe(Ⅲ) reduction followed by chemical Fe(Ⅱ) oxidation, thereby enabling sediment charging and discharging cycles. However, repeated redox cycles reduced the bioavailability of iron oxides, ultimately hindering sustained electron storage and release. The introduction of the electron shuttle anthraquinone-2,6-disulfonate (AQDS) significantly increased the initial charging and discharging rate but also accelerated the decline in Fe(Ⅲ) bioavailability, resulting in a gradual decrease in the charging and discharging rate and the cessation of cycling after the third cycle. In contrast, the addition of sodium lactate, as an electron donor, significantly enriched the iron-reducing bacterium Anaeromyxobacter, maintained high Fe(Ⅲ) bioavailability, and markedly enhanced the charging and discharging rate, supporting sustained cycling under water level fluctuations.

This study reveals the variation patterns and regulatory mechanisms of sediment charging and discharging behaviors under different groundwater level fluctuation regimes, providing new strategies for groundwater pollution prevention and control.

The Lingshui X gas field in the Qiongdongnan Basin has proven natural gas geological reserves of 12.809 billion cubic meters. However, exploration and development efforts have been hindered by challenges such as the large water depths of the offshore basin, limited well data, low resolution of seismic data, and unclear identification of interbedded layers, which are critical for optimizing oil and gas exploration strategies. This study aims to address these challenges by establishing a methodology for identifying interbedded layers and optimizing the oil and gas development plan for the Lingshui X gas field.

This research utilizes core samples, well logging, and seismic data, which are used to create a set of criteria for identifying interbedded layers in the Huangliu Formation’s gravity flow channels. Additionally, frequency extension and inversion techniques are employed to enhance the resolution of seismic data and to reveal the distribution patterns of interbedded layers with different origins. These results contribute to the optimization of exploration and development strategies.

The results indicate that: (1) The overall sedimentary system in the study area is a canyon-channel system, characterized by the development of five distinct microfacies: gravity flow channels, channel-levee complexes, sheet sands, slump deposits, and deep-sea mud. (2) The Huangliu Formation contains mudstone interlayers, mudstone interbeds, and calcareous interbeds. The mudstone interlayers exhibit high natural gamma ray, high density, high velocity, and high impedance characteristics, whereas the calcareous interbeds are distinguished by moderate natural gamma values, low density, and high resistivity. (3) Mudstone interlayers predominantly occur in the central and marginal areas of the canyon, forming large-scale stable distributions, while mudstone interbeds are confined to smaller, localized areas on the flanks of the canyon channels. Calcareous interbeds have limited distribution areas and are less stable in nature. (4) The development of these interbedded layers is influenced by the sedimentary microfacies. When the gravity flow energy is strong, interbedded layers are more commonly found in the levee mud deposits along the channel sides. Conversely, when the energy is weaker, interbeds are more likely to occur in deep-water in-situ deposits. (5) Based on these observations, an optimized deployment plan for a newly developed well, A-1, was proposed, along with its well trajectory. This plan incorporates a semi-quantitative prediction method for identifying interbedded layers, which will improve the precision of future exploration and development.

In conclusion, the results of this study provide significant theoretical and technical support for the identification, prediction, and subsequent oil and gas development in the Lingshui X gas field and similar deep-water gas fields. The methodology established in this research is expected to contribute to enhancing the exploration efficiency and optimizing development strategies for deep-water hydrocarbon reservoirs.

Under complex geological conditions, the mechanical properties of the surrounding rock in underground water-sealed storage caverns are weakened due to construction disturbances, accompanied by stress redistribution and deformation accumulation, leading to the higher risk of localized instability. The creep effect further exacerbates the deformation and plastic failure of the surrounding rock, posing a threat to the long-term stability of the cavern. Therefore, the study of surrounding rock stability should fully utilize monitoring data to assess the state of the surrounding rock and guide construction and operation.

Based on the comprehensive analysis of multi-source monitoring data, such as surrounding rock displacement, anchor stress, and borehole wave velocity, numerical experiments using orthogonal design were employed to invert the mechanical parameters of the rock mass. Additionally, pore water pressure, surrounding rock deformation laws, stress variation, and plastic zone distribution characteristics under layered excavation of the cavern during construction were analyzed. Finally, the stability characteristics of the underground water-sealed storage cavern under long-term water-sealing conditions were evaluated using a creep model of the underground cavern group.

The results show that the deformation of the surrounding rock sharply increases when passing through the monitored section during excavation, with a maximum increment of approximately 3 mm, and then tends to converge. The area affected by the J₁ jointed zone exhibits higher displacement. The overall stress of the anchor rod system is relatively low, and the stress of the anchor rod is synchronized with the deformation of the surrounding rock. The depth of the loosening zone of the surrounding rock is approximately 1.0 m. During construction period, the pore pressure in the excavation area approaches 0 MPa, and the seepage flow of cavern and deformation of surrounding rock are densely distributed along the J₁ jointed zone. The excavation of the middle and lower layers causes the displacement at the intersection of J₁ and the arch line to increase by 90.4% and 28.7%, respectively. The plastic zone in the sidewalls deepens layer by layer, with a maximum depth of 9.2 m. The long-term deformation characteristics of the surrounding rock are manifested as sidewall convergence > floor uplift > crown settlement. The cumulative deformation at the intersection of the J₁ and the arch line during the first year accounts for 92% of the total deformation over 30 years, with a maximum deformation of 27.1 mm. Under the creep effect, stress is gradually released, and the stress distribution tends to become more uniform. The plastic zone near the J₁ expands significantly, while the plastic range in the intact granite area is relatively small, indicating higher long-term stability, indicating that the geological structure-affected zone is the main instability risk zone.

This study provides engineering significance and reference value for stability evaluation during both the construction and operational phases of underground water-sealed storage caverns.

Deep Earth exploration is a multidisciplinary scientific endeavor aimed at uncovering the structure, dynamics, and evolution of continents and their margins. Understanding of the Earth’s interior is crucial for advancing scientific knowledge and comprehending the fundamental processes that shape our planet. Over the past half-century, many countries worldwide have implemented various deep Earth exploration programs, accumulating valuable experience and achieving significant breakthroughs in technology and methods. These advancements provide important references for deep Earth exploration in China.

This paper analyzes the technical approaches and achievements of representative deep Earth exploration programs in the United States, Europe, and Australia since the 21st century, summarizing the latest progress of these programs.

Six frontiers and key potential directions of deep Earth exploration are summarized, including seismic tomography for deep Earth structure detection, magnetotellurics for mineral resource exploration, GNSS monitoring for Earth's motion and state changes, coupled surface-to-deep Earth processes, advanced data processing, analysis and modeling capabilities, and open data sharing. These are expected to provide informational support and references for the “SinoProbe-II” deep exploration program, the “Earth CT” international cooperative research program, and the National Science and Technology Major Projects focused on deep Earth and mineral resources exploration in China.

The Naneng gold deposit is an important medium-sized Carlin type gold deposit in southeastern Yunnan, and studying its genesis is of great significance for searching for such gold deposits in southeastern Yunnan.

Two generations of pyrite (PyI and PyII) were found to develop in the Naneng gold deposit during detailed field survey and indoor observation, and trace elements and sulfur isotopes of gold-bearing minerals are analyzed by LA-ICP-MS to constrain the source of ore-forming materials and ore genesis.

LA-ICP-MS analyses show that PyI contains a small amount of Au (mean 6.37×10⁻⁶), which is relatively enriched in elements such as Co, Ni, Se, W; The distribution characteristics of trace elements in PyII and PyI are similar, but the content of Au (mean 68.02×10⁻⁶) is relatively high, and As, Sb, Cu elements are enriched in PyII; The average Au content of arsenopyrite is 36.02×10⁻⁶, and arsenopyrite is mainly enriched in elements such as As、Ni、Sb、Se、Au, while Zn, Ag, Hg and Tl elements are low. In addition, gold-bearing minerals in the Naneng gold deposit have consistent in situ δ³⁴S values, ranging from 13.7‰ to 16.5‰, indicating that the S of gold-bearing minerals mainly come from the surrounding rocks.

It is preliminarily concluded that PyI was formed in a relatively stable environment by medium to low temperature hydrothermal fluid from the same source rich in trace elements such as Au、As、Sb, and a small amount of Au precipitated simultaneously with PyI in the form of solid solution (Au⁺). In the PyII stage, the intense tectonic activity in the area caused ore-forming fluid to upswell, and after sulfidation reaction with surrounding rock strata, the concentration of H₂S in the fluid decreased, Au-HS complex became unstable, and Au supersaturated precipitation was enriched in PyII in the form of nanoscale inclusions (Au⁰).

Block Fan 151 is a low-permeability beach-bar sandstone reservoir with poor overall physical properties and high heterogeneity, resulting in low oil recovery and significant amounts of residual oil during development. It is essential to analyze the influence of reservoir heterogeneity on the distribution of residual oil and identify enrichment areas. Furthermore, calculating the reservoir heterogeneity comprehensive index plays a crucial role in quantitatively characterizing heterogeneity. Therefore, improving the accuracy of calculating the comprehensive index can provide a basis for predicting favorable areas for oilfield development and finding residual oil.

To improve the accuracy of the comprehensive reservoir heterogeneity index calculation, this study proposes the AHP-CRITIC combined weighting method. This method determines the composite weight of evaluation indicators using both subjective and objective data, overcoming the limitations of a single weighting approach.

Quantitative analysis of the heterogeneity of the 2⁴ layers in the Upper Es4 Member of Block Fan 151 shows that the heterogeneous comprehensive index I ranges from 0.27 to 0.73, with about 63% of the values falling between 0.4 and 0.65.

The target formation in the study area exhibits moderate to strong heterogeneity, and the distribution of high values of the comprehensive heterogeneity index I aligns closely with the high-value areas on the residual oil saturation contour map. This indicates that the AHP-CRITIC combined weighting method effectively assigns weights to the evaluation parameters and establishes a quantitative evaluation criterion for the heterogeneity of this reservoir. This approach offers a new method for the quantitative characterization of reservoir heterogeneity.

The interpretation results of SBAS-InSAR exhibit multiple solutions, making it uncertain to directly use the interpreted deformation points for identifying potential landslide-prone areas. Therefore, taking the north bank of the Qingjiang River (Changyang Section) as the study area, this study proposed a method to comprehensively optimize SBAS-InSAR interpretation results by incorporating landslide susceptibility evaluation.

First, the deformation points interpreted by SBAS-InSAR were analyzed using clustering and outlier detection (Anselin Local Moran's I), and low-value cluster deformation points were retained. Subsequently, eight factors, including elevation, slope, and slope aspect, were selected to evaluate and generate a landslide susceptibility zoning map using the information value method. The reliability of the landslide susceptibility evaluation was confirmed by an ROC curve, with an AUC value of 0.844.

The optimized SBAS-InSAR results were obtained by filtering low-value cluster deformation points based on a threshold value (v ≤ -10 mm/a) and incorporating the landslide susceptibility zoning map. Field verification in selected areas shows that the number of deformation points was reduced after optimization, and their distribution characteristics were more consistent with the historical landslide development in the study area. Additionally, taking the Yupingcun landslide group and the Pianshan landslide as typical cases, the surface deformation values monitored by SBAS-InSAR and GNSS at the same time were compared. In the case of the Yupingcun landslide, the difference between surface displacement values monitored by SBAS-InSAR and GNSS ranged from 0 to 7.87 mm, with an average difference of approximately 2.23 mm and an RMSE of 3.67.

The proposed optimization method for SBAS-InSAR interpretation was demonstrated to be both practical and reliable, providing valuable insights into the application of InSAR technology in the field of geological disasters.