Search Results (890)

In this study, we investigate the nonlinear dynamical behavior of a one-dimensional linear piecewise-smooth discontinuous (LPSD) map with a negative slope, motivated by its occurrence in systems exhibiting discontinuities, such as power electronic converters. The objective of the proposed research is to develop an analytical approach. Analytical conditions are derived for the existence of stable period-1 and period-2 orbits within the third quadrant of the parameter space defined by slope coefficients $a<0$ and $b<0$. The coexistence of multiple attractors is demonstrated. We also show that a novel class of orbits exists in which both points lie entirely in either the left or right domain. These orbits are shown to eventually exhibit periodic behavior, and a closed-form expression is derived to compute the number of iterations required for a trajectory to converge to such orbits. This method also enhances the ease of analyzing system stability by mapping the state–variable dynamics using a non-smooth discontinuous map. The analytical findings are validated using bifurcation diagrams, cobweb plots, and basin of attraction visualizations. Full article

The use of the Soil and Water Assessment Tool (SWAT) model driven by China Meteorological Assimilation Driving Datasets (CMADS) for runoff simulation research is of great significance for regional flood prevention and control. Therefore, from the perspective of production-living-ecological space, this article combined multi-source data such as DEM, soil texture and land use type, in order to construct scenarios of territorial spatial change (TSC) across distinct periods. Based on the CMADS-L40 data and the SWAT model, it simulated the runoff dynamics in the Xitiaoxi River Basin, and analyzed the hydrological response characteristics under different TSCs. The results showed that The SWAT model, driven by CMADS-L40 data, demonstrated robust performance in monthly runoff simulation. The coefficient of determination (R²), Nash–Sutcliffe efficiency coefficient (NSE), and the absolute value of percentage bias (|PBIAS|) during the calibration and validation period all met the accuracy requirements of the model, which validated the applicability of CMADS-L40 data and the SWAT model for runoff simulation at the watershed scale. Changes in territorial spatial patterns are closely correlated with runoff variation. Changes in agricultural production space and forest ecological space show statistically significant negative correlation with runoff change, while industrial production space change exhibits a significant positive correlation with runoff change. The expansion of production space, particularly industrial production space, leads to increased runoff, whereas the enlargement of agricultural production space and forest ecological space can reduce runoff. This article contributes to highlighting the role of land use policy in hydrological regulation, providing a scientific basis for optimizing territorial spatial planning to mitigate flood risks and protect water resources. Full article

The Silurian marine shale in the Sichuan Basin is currently the main reservoir for shale gas reserves and production in China. This study investigates the reservoir evolution of the Silurian marine shale based on fractal dimension, quantifying the complexity and heterogeneity of the shale’s pore structure. Physical simulation experiments were conducted on field-collected shale samples, revealing the evolution of total organic carbon, mineral composition, porosity, and micro-fractures. The fractal dimension of shale pore was characterized using the Frenkel–Halsey–Hill and capillary bundle models. The relationships among shale components, porosity, and fractal dimensions were investigated through a correlation analysis and a principal component analysis. A comprehensive evolution model for porosity and micro-fractures was established. The evolution of mineral composition indicates a gradual increase in quartz content, accompanied by a decline in clay, feldspar, and carbonate minerals. The thermal evolution of organic matter is characterized by the formation of organic pores and shrinkage fractures on the surface of kerogen. Retained hydrocarbons undergo cracking in the late stages of thermal evolution, resulting in the formation of numerous nanometer-scale organic pores. The evolution of inorganic minerals is represented by compaction, dissolution, and the transformation of clay minerals. Throughout the simulation, porosity evolution exhibited distinct stages of rapid decline, notable increase, and relative stabilization. Both pore volume and specific surface area exhibit a trend of decreasing initially and then increasing during thermal evolution. However, pore volume slowly decreases after reaching its peak in the late overmature stage. Fractal dimensions derived from the Frenkel–Halsey–Hill model indicate that the surface roughness of pores (D1) in organic-rich shale is generally lower than the complexity of their internal structures (D2) across different maturity levels. Additionally, the average fractal dimension calculated based on the capillary bundle model is higher, suggesting that larger pores exhibit more complex structures. The correlation matrix indicates a co-evolution relationship between shale components and pore structure. Principal component analysis results show a close relationship between the porosity of inorganic pores, microfractures, and fractal dimension D2. The porosity of organic pores, the pore volume and specific surface area of the main pore size are closely related to fractal dimension D1. D1 serves as an indicator of pore development extent and characterizes the changes in components that are “consumed” or “generated” during the evolution process. Based on mineral composition, fractal dimensions, and pore structure evolution, a comprehensive model describing the evolution of pores and fractal dimensions in organic-rich shale was established. Full article

Based on the new high-resolution multibeam bathymetry data collected by the “Dongfanghong 3” vessel in 2023 in the Parece Vela Basin (PVB) and previous magnetic anomaly data, we systematically analyze the seafloor topographical changes of abyssal hills and oceanic core complexes (OCCs) in the “Chaotic Terrain” region, and the revised seafloor spreading model is constructed in the PVB. Using detailed analysis of the seafloor topography, we identify typical geomorphological features associated with seafloor spreading, such as regularly aligned abyssal hills and OCCs in the PVB. The direction variations of seafloor spreading in the PVB are closely related to mid-ocean ridge rotation and propagation. The formation of OCCs in the “Chaotic Terrain” can be explained by links to the continuous and persistent activity of detachment faults and dynamic adjustments controlled by variations of deep magma supply in the different segments in the PVB. We use 2D discrete Fourier image analysis of the seafloor topography to calculate the aspect ratio (AR) values of abyssal hills in the western part of the PVB. The AR value variations reveal a distinct imbalance in magma supply across various regions during the basin spreading process. Compared to the “Chaotic Terrain” area, the region with abyssal hills indicates a higher magma supply and greater linearity on seafloor topography. AR values fluctuated between 2.1 and 1.7 of abyssal hills in the western segment, while in the “Chaotic Terrain”, they dropped to 1.3 due to the lower magma supply. After the formation of the OCC-1, AR values increased to 1.9 in the eastern segment, and this shows the increase in magma supply. Based on changes in seafloor topography and variations in magma supply across different segments of the PVB, we propose that the seafloor spreading process in the magnetic anomaly linear strip 9-6A of the PVB mainly underwent four formation stages: ridge rotation, rift propagation, magma-poor supply, and the maturation period of OCCs. Full article

This study investigates the spatio-temporal dynamics of Climate Potential Productivity (CPP) in Central Africa during 1901–2019 using the Thornthwaite Memorial model coupled with Mann–Kendall tests based on high spatial and temporal resolution data. The results demonstrate the climate–vegetation interactions under global warming: (1) Central Africa exhibited a statistically significant warming trend (r² = 0.33, p < 0.01) coupled with non-significant rainfall reduction, suggesting an emerging warm–dry climate regime that parallels meteorological trends observed in North Africa. (2) Central Africa exhibited an overall increasing trend in CPP, with temporal fluctuations closely aligned with precipitation variability. Specifically, the CPP in Central Africa has undergone three distinct phases: an increasing phase (1901–1960), a decreasing phase (1960–1980), and a slow recovery phase (1980–2019). The multiple intersection points between the UF and UB curves indicate that Central Africa’s CPP has been significantly affected by climate change under global warming. (3) The correlation of CPP–Temperature was mainly positive, mainly distributed in the Lower Guinea Plateau and the northern part of the Congo Basin (r² = 0.26, p < 0.1). The relationship of CPP–Precipitation showed predominantly a very strong positive correlation (r² = 0.91, p < 0.01). 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

Lithology identification is one of the most important research areas in petroleum engineering, including reservoir characterization, formation evaluation, and reservoir modeling. Due to the complex structural environment, diverse lithofacies types, and differences in logging data and core data recording standards, there is significant overlap in the logging responses between different lithologies in the second member of the Lucaogou Formation in the Santanghu Basin. Machine learning methods have demonstrated powerful nonlinear capabilities that have a strong advantage in addressing complex nonlinear relationships between data. In this paper, based on felsic content, the lithologies in the study area are classified into four categories from high to low: tuff, dolomitic tuff, tuffaceous dolomite, and dolomite. We also study select logging attributes that are sensitive to lithology, such as natural gamma, acoustic travel time, neutron, and compensated density. Using machine learning methods, XGBoost, random forest, and support vector regression were selected to conduct lithology identification and favorable reservoir prediction in the study. The prediction results show that when trained with 80% of the predictors, the prediction performance of all three models has improved to varying degrees. Among them, Random Forest performed best in predicting felsic content, with an MAE of 0.11, an MSE of 0.020, an RMSE of 0.14, and a R² of 0.43. XGBoost ranked second, with an MAE of 0.12, an MSE of 0.022, an RMSE of 0.15, and an R² of 0.42. SVR performed the poorest. By comparing the actual core data with the predicted data, it was found that the results are relatively close to the XRD results, indicating that the prediction accuracy is high. Full article

In recent years, the exploration and utilization of geothermal energy have received growing attention as a sustainable alternative to conventional energy sources. Reliable, data-driven identification of geothermal reservoirs, particularly in crystalline basement terrains, is crucial for reducing exploration uncertainties and costs. In such geological settings, magnetic susceptibility, radioactive heat production, and seismic wave characteristics play a vital role in evaluating geothermal energy potential. Building on this foundation, our study integrates in situ and laboratory measurements, collected using advanced sensors from spatially diverse locations, with statistical and unsupervised artificial intelligence (AI) clustering models. This integrated framework improves the effectiveness and reliability of identifying clusters of potential geothermal sites. We applied this methodology to the migmatitic gneisses within the Simav Basin in western Türkiye. Among the statistical and AI-based models evaluated, Density-Based Spatial Clustering of Applications with Noise and Autoencoder-Based Deep Clustering identified the most promising and spatially confined subregions with high geothermal production potential. The potential geothermal sites identified by the AI models align closely with those identified by statistical models and show strong agreement with independent datasets, including existing drilling locations, thermal springs, and the distribution of major earthquake epicenters in the region. Full article

With the continuous improvement of reservoir projects and the advancement of digital twin basin initiatives in China, rapidly and accurately generating long-term practical reservoir operation schedules has become a key priority for stakeholders. This study proposes a Theory-guided Long Short-Term Memory (TgLSTM) model to extract optimal reservoir operation rules accurately and reliably. Concretely, TgLSTM integrates data-fitting accuracy with the physical constraints of an operation, e.g., water level constraints and minimal discharge constraints, to address the low credibility often observed in conventional LSTM networks. Using the Three Gorges Reservoir during the dry season as a case study, a multi-year hydrological series optimized by particle swarm optimization (PSO) was used to train the TgLSTM network and derive optimized operation rules. Results show that TgLSTM efficiently generates operation schemes close to the theoretical optimum, achieving power generations of 4.27 × 10¹⁰ kW·h and 4.19 × 10¹⁰ kW·h in two test years, with deviations of only 4.20% and 2.33%, respectively. Compared to traditional LSTM models, TgLSTM is more reliable as it captures key operational characteristics such as terminal water levels and water level fluctuations, maintaining an average ten-day drawdown depth below 1.5 m—significantly lower than the 7 m fluctuations observed with conventional LSTM. Furthermore, comparative analyses against SwR, BP–ANN, and SVM confirm that TgLSTM offers a moderate performance in absolute metrics but is the best to simulate the constrained reservoir operation. Full article

The Ghris watershed in southern Morocco is a significant ecological and agricultural area. However, due to the current impacts of climate change, farming activities, and pollution, data on its quality and biological importance need to be updated. Therefore, this study aimed to evaluate the physico-chemical and biological quality of surface water in the Ghris River. The Water Quality Index (WQI) and the Iberian Biological Monitoring Working Group (IBMWP) index were used to assess water quality along four sampling sites in 2024. The collected data were analyzed with descriptive and multivariate statistics. In total, 424 benthic macroinvertebrates belonging to seven orders were identified in the surface waters of the Ghris basin. These microfauna were significantly variable among the studied sites (p < 0.05). Station S4 is significantly rich in species, including seven orders and nine families of macroinvertebrates, followed by Station S2, with seven orders and eight families. Stations S3 and S1 showed less species diversity, with three orders and one family, respectively. The Insecta comprised 95.9% of the abundance, while the Crustacea constituted just 4.1%. The physico-chemical parameters significantly surpassed (p < 0.05) the specified norms of surface water in Morocco. This indicates a decline in the water quality of the studied sites. The findings of the principal component analysis (PCA) demonstrate that the top two axes explain 87% of the cumulative variation in the data. Stations 2 and 3 are closely associated with high concentrations of pollutants, notably Cl⁻, SO₄²⁻, NO₃⁻, and K⁺ ions. Dissolved oxygen (DO) showed a slight correlation with S2 and S3, while S4 was characterized by high COD and PO₄ concentrations, low levels of mineral components (except Cl⁻), and average temperature conditions. Bioindication scores for macroinvertebrate groups ranging from 1 to 10 enabled the assessment of pollution’s influence on aquatic biodiversity. The IBMWP biotic index indicated discrepancies in water quality across the sites. This study gives the first insight and updated data on the biological and chemical quality of surface water in the Ghris River and the entire aquatic ecosystem in southeast Morocco. These data are proposed as a reference for North African and Southern European rivers. However, more investigations are needed to evaluate the impacts of farming, mining, and urbanization on the surface and ground waters in the study zone. Similarly, it is vital to carry out additional research in arid and semi-arid zones since there is a paucity of understanding regarding taxonomic and functional diversity, as well as the physico-chemical factors impacting water quality. Full article

The study presents a scenario analysis of the long-term dynamics of the water level of Lake Balkhash, one of the largest closed lakes in Central Asia, taking into account climate change according to CMIP6 scenarios (SSP2-4.5 and SSP5-8.5) and socio-economic factors of water use. Based on historical data (1947–2021) and a water balance model, the contribution of surface runoff, precipitation and evaporation to the formation of the lake’s hydrological regime was assessed. It was established that the main source of water resources for the lake is the flow of the Ile River, which feeds the western part of the reservoir. The eastern part is characterized by extremely limited water inflow, while evaporation remains the main element of water consumption, having increased significantly in recent decades due to rising air temperatures. Increasing intra-seasonal and interannual fluctuations in water levels have been recorded: The amplitude of short-term fluctuations reached 0.7–0.8 m, which exceeds previously characteristic values. The results of water balance modeling up to 2050 show a trend towards a 30% reduction in surface inflow and an increase in evaporation by 25% compared to the 1981–2010 climate norm, which highlights the high sensitivity of the lake’s hydrological regime to climatic and anthropogenic influences. The results obtained justify the need for the comprehensive and adaptive management of water resources in the Balkhash Lake basin, taking into account the transboundary nature of water use and changing climatic conditions. Full article

There is a consensus that climate change has affected society. The increase in temperature and reduction in precipitation for some regions of the world have had implications for the intensity and frequency of extreme events. This scenario is worrying for various sectors of water use, such as hydroelectric power generation and agriculture. Reduced flows in river basins, coupled with increased water consumption, can significantly affect energy generation and food production. Within this context, this paper presents an analysis of climate change impacts in a large basin of Brazil between the Amazon and Cerrado biomes, considering the effects of water demands. Inflow projections were generated for seven power plant reservoirs in the Tocantins–Araguaia river basin, using projections from five climate models. The results indicate significant reductions in flows, with decreases of more than 50% in the average flow. For minimum flows, there are indications of reductions of close to 85%. The demand for water, although growing, represents a smaller part of the effects, but should not be disregarded, since it impacts the dry periods of the rivers and can generate conflicts with energy production. Full article

The mechanism of low- to middle-rank coal seam gas accumulation in the Baode block on the eastern edge of the Ordos Basin is well understood. However, exploration efforts in the Shizuishan area on the western edge started later, and the current understanding of enrichment and accumulation rules is unclear. It is important to systematically study enrichment and accumulation, which guide the precise exploration and development of coal seam gas resources in the western wing of the basin. The coal seam collected from the Shizuishan area of Ningxia was taken as the target. Based on drilling, logging, seismic, and CBM (coalbed methane) test data, geological conditions were studied, and factors and reservoir formation modes of CBM enrichment were summarized. The results are as follows. The principal coal-bearing seams in the study area are coal seams No. 2 and No. 3 of the Shanxi Formation and No. 5 and No. 6 of the Taiyuan Formation, with thicknesses exceeding 10 m in the southwest and generally stable thickness across the region, providing favorable conditions for CBM enrichment. Spatial variations in burial depth show stability in the east and south, but notable fluctuations are observed near fault F1 in the west and north. These burial depth patterns are closely linked to coal rank, which increases with depth. Although the southeastern region exhibits a lower coal rank than the northwest, its variation is minimal, reflecting a more uniform thermal evolution. Lithologically, the roof of coal seam No. 6 is mainly composed of dense sandstone in the central and southern areas, indicating a strong sealing capacity conducive to gas preservation. This study employs a system that fuses multi-source geological data for analysis, integrating multi-dimensional data such as drilling, logging, seismic, and CBM testing data. It systematically reveals the gas control mechanism of “tectonic–sedimentary–fluid” trinity coupling in low-gentle slope structural belts, providing a new research paradigm for coalbed methane exploration in complex structural areas. It creatively proposes a three-type CBM accumulation model that includes the following: ① a steep flank tectonic fault escape type (tectonics-dominated); ② an axial tectonic hydrodynamic sealing type (water–tectonics composite); and ③ a gentle flank lithology–hydrodynamic sealing type (lithology–water synergy). This classification system breaks through the traditional binary framework, systematically explaining the spatiotemporal matching relationships of the accumulated elements in different structural positions and establishing quantitative criteria for target area selection. It systematically reveals the key controlling roles of low-gentle slope structural belts and slope belts in coalbed methane enrichment, innovatively proposing a new gentle slope accumulation model defined as “slope control storage, low-structure gas reservoir”. These integrated results highlight the mutual control of structural, thermal, and lithological factors on CBM enrichment and provide critical guidance for future exploration in the Ningxia Autonomous Region. Full article

This study addresses the water basin effect in the underwater sand layer of steel pipe pile cofferdams by integrating the concept from building foundation pits to cofferdam foundation pit analysis. A theoretical derivation is presented for the deformation evolution of steel pipe piles and bottom seals within the cofferdam pit. The cofferdam construction dewatering process is divided into four stages: riverbed excavation for bottom sealing, dewatering to the second support, dewatering to the third support, and dewatering to final bottom sealing. The steel pipe piles are modeled as single-span or multi-span cantilever continuous beam structures. Using the superposition principle, deformation evolution equations for these statically indeterminate structures across the four stages are derived. The bottom seal is simplified to a single-span end-fixed beam, and its deflection curve equation under uniform load and end-fixed additional load is obtained via the same principle. A case study based on the 6# pier steel pipe pile cofferdam of Xi’an Metro Line 10 Jingwei Bridge rail-road project employs FLAC3D for hydrological–mechanical coupling analysis of the entire dewatering process to validate the water basin effect. Results reveal a unique water basin effect in cofferdam foundation pits. Consistent horizontal deformation patterns of steel pipe piles occur across all working conditions, with maximum horizontal displacement (20.72 mm) observed at 14 m below the pile top during main pier construction completion. Close agreements are found among theoretical, numerical, and monitored deformation results for both steel pipe piles and bottom seals. Proper utilization of the formed water basin effect can effectively enhance cofferdam stability. These findings offer insights for similar engineering applications. Full article

Pore pressure prediction gives drillers an early warning of potential oil and gas kicks, enabling them to adjust mud weight pre-emptively. A kick causes a delay in drilling practices, blowouts, and jeopardization of the wells. Changes in pore pressure affect the type of fluid contact in the reservoir. This study predicted the pore pressure and determined fluid contacts within the Lower Cretaceous and early Upper Cretaceous (Barremian to early Cenomanian) sandstone reservoirs of the Bredasdorp Basin using well logs and repeat formation test (RFT) data from three wells: E-BK1, E-AJ1, and E-CB1. Eaton’s method of developing a depth-dependent Normal Compact Trend (NCT), using resistivity and sonic wireline logs, as well as other methods including the Mathews and Kelly, Baker and Wood, and Modified Eaton and Bowers methods, were employed for pore pressure prediction. Eaton’s method provided reliable pore pressure results in all the wells when compared to alternative methods in this study. Overburden gradient and predicted pore pressures ranged from 1.84 gm/cc to 2.07 gm/cc and from 3563.74 psi to 4310.06 psi, respectively. Eaton’s resistivity and density/neutron log method results indicated normal pressure in E-BK1 and E-AJ1, as well as overpressured zones in E-AJ1. However, in E-CB1, the results showed only overpressured zones. The E-AJ1 significant overpressures were from 2685 m to 2716 m and from 2716 m to 2735 m in the pores exceeding 7991.54 psi. Gas–water contact (GOC) was encountered at 2967.5 m in E-BK1, while oil–gas contact (OGC) was at 2523 m in E-CB1, and gas–oil and oil–water contacts (GOC and OWC) were at 2699 m and 2723 m, respectively, in E-AJ1. In E-CB1, oil–water contact (OWC) was at 2528.5 m. Fluid contacts observed from the well logs and RFT data were in close agreement in E-AJ1, whereas there was no agreement in E-CB1 because the well log observations showed a shallower depth compared to RFT data with a difference of 5.5 m. This study illustrated the significance of an integrated approach to predicting fluid contacts and pore pressure within the reservoirs by showing that fluid contacts associated with overpressures were gas–water and oil–water contacts. In contrast, gas–oil contact was associated with normal pressure and under pressure. Full article