Geological Information Research Articles

Discharge Experiment and Structure Optimisation Simulation of Impulse Sound Source

The wave frequency and energy of traditional piezoelectric emission sources used in acoustic logging are limited, which results in an inadequate detection resolution for measuring small-scale geological formations. Additionally, the propagation of these waves in formations is prone to loss and noise interference, restricting detection to only a few tens of meters around the well. This paper investigates an impulse sound source, a new emission source that can effectively enhance the frequency range and wave energy of traditional sources by generating excitation waves through high-voltage discharges in a fluid-penetrated electrode structure. Firstly, a high-voltage circuit experimental system for the impulse sound source was constructed, and the discharge and response characteristics were experimentally analyzed. Then, four types of needle series electrode structure models were developed to investigate and compare the effects of different electrode structures on the impulse sound source, with the needle-ring electrode demonstrating superior performance. Finally, the needle-ring electrode structure was optimized to develop a ball-tipped needle-ring electrode, which is more suitable for acoustic logging. The results show that the electrode structure directly influences the discharge characteristics of the impulse sound source. After comparison and optimization, the final ball-tipped needle-ring electrode exhibited a broader frequency range—from zero to several hundred thousand Hz—while maintaining a high acoustic amplitude. It has the capability to detect geological areas beyond 100 m and is effective for evaluating micro-fractures and small fracture blocks near wells that require high detection accuracy. This is of significant importance in oil, gas, new energy, and other drilling fields.

Ghost age components in detrital thermochronology

Thermochronological dating of detrital samples is an important tool for understanding the thermal history of basins and their source regions. Detrital thermochronology data are often complex with apparent ages ranging over hundreds of million years due to variations in source-rock cooling age and rate, and the influence of post-depositional burial. A common strategy to interpret such data is to split a dataset into several age components by finite-mixture modeling. Herein, we describe for the first time a remarkable pattern of age components in some thermochronological datasets: two or more components showing ages that are approximately multiples of each other. We apply finite-mixture modeling to a log-normal age distribution (a random effects model) and show that these “ghost age components” are artifacts of inappropriately fitting discrete components to continuous age ranges. The striking pattern of the age components is a direct consequence of the underlying age distribution. For a continuous log-normal age distribution, the ghost components have approximately similar age ratios that depend on the overdispersion and the number of components. Due to their artifactual nature, ghost components appear in a range of dating methods, including fission-track, UPb and (UTh)/He dating, and in equivalent doses of luminescence dating. As they are not geologically meaningful, their occurrence hampers the geological interpretation of thermochronological data. We thus propose to carefully decide for the number of fitted components based on grain properties and additional geological information and to screen modeling results for the constant age ratios that are characteristic of ghost components.

Data-driven prediction of drilling strength ahead of the bit

This paper compares the performance of two data-driven methods, Signal-Matching Predictor (SMP) and Long Short-Term Memory (LSTM), for predicting drilling strength (Es) ahead of the bit based on drilling data from nearby offset wells. The comparison is based on the accuracy, applicability, complexity, and computational cost of the methods with the objective of suggesting the most appropriate tool for look-ahead drilling strength prediction. The methods were tested using data from offshore wells in Newfoundland. The SMP used a fixed-size sliding-window of real-time Es data from the target well to find a match in the offset well within similar geological formations and chose the scaled value from the offset well as the prediction. In the second approach, twelve LSTM models were trained using the drilling data of twelve offset wells, and the drilling data of the thirteenth well was used for blind testing. Results showed that the SMP achieved a coefficient of determination (R2) of 0.92, 0.92, and 0.79 for predicting 1.5, 3, and 5 feet ahead of the bit, respectively, while the LSTM reached an R2 of 0.95, 0.92, and 0.80 for the respective prediction intervals. The R2 of the LSTM models was further increased to 0.96, 0.94, and 0.83 after retraining it with weighted samples in formation transition zones. Also, a post-processing technique was proposed that further enhanced the R2 of the LSTM-based approach to 0.98, 0.97, and 0.93, respectively. The strength of the LSTM-based approach was to use measurable drilling parameters as the only inputs and not the Es itself. According to the results, the LSTM-based method can be reliably used to predict the Es ahead of the bit allowing drillers to identify upcoming drilling dysfunctions.

Assessment of thermal and physicochemical properties of mechanic village soils derived from two different geological formations in Ogun State, Nigeria

This study assessed and compared selected soil properties, oil and grease content, and thermophysical parameters of sandy loam soils from two representative automobile mechanic village (MV) on two different geological formations in Ogun State, Nigeria. The two locations: Abeokuta and Sagamu are situated on a basement complex and Cretaceous-sedimentary formations, respectively. Ten sample points were established on each MV. Physico-chemical and in-situ thermal properties were measured using standard methods and KD2 Pro thermal analyzer, respectively. Three different regression models (linear, semi-log and double-log) were generated for the prediction of thermal conductivity ( λ s ) and specific heat capacity ( C s ). Topsoils in both MVs are slightly acidic to neutral, with an average oil and grease content > 100 mg/kg. Results of thermophysical parameters revealed that the average λ s values in MV soils of basement complex and sedimentary backgrounds were 1.656 and 1.988 W/mK, respectively. The average C s values in Abeokuta and Sagamu MV soils are 2.295 and 3.043 MJ/m3K, respectively. The regression analysis showed that the double log model performed better than both linear and semi log models for predicting λ s at both locations. All the tested regression models have good prediction effects on C s at location within cretaceous sedimentary, whereas linear and double-log models proved feasible for predicting C s at location underlain by basement complex.

Construction and experimental verification of wave velocity model for source location in goaf overlying rock strata

The geological structure of the goaf overlying rock is complex, a consequence of coal mining that has modified the original stratified structure of the sedimentary strata. To enhance the accuracy of microseismic source location in such intricate geological formations, a wave velocity model for the “three zones” goaf was constructed based on natural divisions within the strata using Snell's law and assuming a homogeneous medium. The model took into account the effects of rock deformation and fracture development, enabling the derivation of formulas for microseismic wave propagation path and travel time calculation. Additionally, the concept of equivalent wave velocity was defined. An indoor simulation test using similar materials was conducted to establish a geological model of the goaf. By comparing the errors between the theoretical and measured values of equivalent wave velocity, assessing the locating effects before and after implementing the wave velocity model of the goaf, and verifying the feasibility of the model, it was demonstrated that establishing a wave velocity model based on the characteristics of the strata structure was crucial for improving the accuracy of the microseismic source location. Notably, as the propagation path of microseismic waves in the goaf increased, the equivalent wave velocity decreased. The wave velocity structure in the goaf exhibited nonuniformity, with the relative error between the theoretical and measured values of equivalent wave velocity being limited to 10 %. The incorporation of this established wave velocity model into the location method resulted in a substantial 58.57 % increase in locating accuracy.

Experimental investigation of collapsible soils under oedometric loading: effect of internal erosion

Collapsible soils, geological formations characterized by pronounced structural instability upon saturation, present a significant challenge in geotechnical engineering. This experimental study aims to deepen our understanding of the mechanisms governing the behavior of these soils, which are particularly prevalent in arid and semi-arid regions subject to extreme hydrological cycles. Collapsible soils, sensitive to climatic variability, undergo profound alterations in their hydromechanical properties due to alternating periods of prolonged drought and intense rainfall events. These fluctuations induce significant modifications in the soil's pore structure, promoting the development of internal erosion phenomena such as suffusion. The results obtained from this experimental investigation on reconstituted samples highlight the combined influence of various factors, such as water content, dry density, particle size, and flow rate, on the collapse potential. It appears that fine particles play a predominant role in the formation of fragile structures, susceptible to collapse upon saturation. Moreover, the intensity and duration of infiltration significantly influence the propagation velocity of ultrasonic waves, thus offering a promising tool for monitoring the evolution of damage within the soil mass. Furthermore, this study provides essential insights for assessing the risks associated with collapsible soils and contributes to the development of more reliable characterization and modeling methods. It emphasizes the need to consider the complex interactions between the physical, chemical, and mechanical properties of the soil, as well as the influence of environmental conditions, for better control of the risks associated with these materials.

Environmental risk evaluation for radionuclide transport through natural barriers of nuclear waste disposal with multi-scale streamline approaches

Natural barriers, encompassing stable geological formations that serve as the final bastion against radionuclide transport, are paramount in mitigating the long-term contamination risks associated with the nuclear waste disposal. Therefore, it is important to simulate and predict the processes and spatial-temporal distributions of radionuclide transport within these barriers. However, accurately predicting radionuclide transport on the field scale is challenging due to uncertainties associated with parameter scaling. This study develops an integrated evaluation framework that combines upscaled parameters, streamline transport models, and response surface techniques to systematically assess environmental risk metrics and parameter uncertainties across different scales. Initially, upscaling methods are established to estimate the prior interval of critical transport parameters at the field scale, and streamline models are derived by considering the radionuclides transport with a variety of physicochemical mechanisms and geological characterizations in natural barriers. To assess uncertainty ranges of the risk metrics related to upscaled parameters, uncertainty quantification is performed on the ground of 5000 Monte Carlo simulations. The results indicate that the upscaled dispersivity of fractured media (αLf) has a relatively high sensitivity ranking on release dose for all nuclides, and upscaled matrix sorption coefficient (Kd) of Pu-242 strongly affects breakthrough time and release dose of Pu-242. Facilitated by robust response surface with the lowest R2 of 0.89, it is shown that the release doses of Pu-242 and Pb-210 increase under conditions of low Kd and αLf, respectively. Furthermore, statistical analysis reveals that employing limited laboratory-scale parameters results in narrower confidence intervals for risk metrics, while upscaling methods better account for the highly heterogeneous properties of large-scale field conditions. The developed risk evaluation framework provides valuable insights for utilizing upscaled parameters and modeling radionuclide transport within natural barriers under various scenarios.

REWARE: a seismic processing algorithm to retrieve geological information from the water column

SUMMARY When interpreting marine very high-resolution (VHR) single-channel seismic reflection data, the signal in the water column is generally considered as noise and is often eliminated by a water-mute application to focus on geological information under the seafloor. Alternatively, the signal in the water column can be used to study ocean currents or gas/fluid emissions. To provide images of the sedimentary formations and tectonic structures beneath the seafloor in shallow water regions, such as continental shelves and lakes, marine seismic reflection profiles are often acquired using a single-channel streamer and sparker-type source, providing VHR data, with limited penetration depth. To exploit the full potential of these single-channel data, we propose a simple algorithm, called REWARE (Recovery of Water-column Acoustic Reflectors). This algorithm allows to extract further geological information from the water-column data using open-source codes (Seismic Un*x), adding the coherent signal from the previous shots, recorded in the water column, to the previous traces. The record length becomes longer while maintaining a very high trace-to-trace consistency. To demonstrate its efficiency, we present two examples of the REWARE processing in two different geological contexts: the East Sardinia shelf (Italy) and the North Evia Gulf (Greece). This method provides deeper images than with original data for seismic data acquired across steep slopes, such as canyons or continental shelf breaks. Thus, depending on the seafloor geometry and subseafloor structures, it is possible to image or map sediment layers and tectonic structures at depth, keeping a very high structural resolution.

The Construction and Application of a Digital Coal Seam for Shearer Autonomous Navigation Cutting.

Accurately obtaining the geological characteristic digital model of a coal seam and surrounding rock in front of a fully mechanized mining face is one of the key technologies for automatic and continuous coal mining operation to realize an intelligent unmanned working face. The research on how to establish accurate and reliable coal seam digital models is a hot topic and technical bottleneck in the field of intelligent coal mining. This paper puts forward a construction method and dynamic update mechanism for a digital model of coal seam autonomous cutting by a coal mining machine, and verifies its effectiveness in experiments. Based on the interpolation model of drilling data, a fine coal seam digital model was established according to the results of geological statistical inversion, which overcomes the shortcomings of an insufficient lateral resolution of lithology and physical properties in a traditional geological model and can accurately depict the distribution trend of coal seams. By utilizing the numerical derivation of surrounding rock mining and geological SLAM advanced exploration, the coal seam digital model was modified to achieve a dynamic updating and optimization of the model, providing an accurate geological information guarantee for intelligent unmanned coal mining. Based on the model, it is possible to obtain the boundary and inclination information of the coal seam profile, and provide strategies for adjusting the height of the coal mining machine drum at the current position, achieving precise control of the automatic height adjustment of the coal mining machine.

Hydrogen adsorption kinetics in organic-Rich shale reservoir rocks for seasonal geological storage

The geo-storage of hydrogen (H2) is essential for advancing a robust and industrial-scale H2-based economy. The efficient H2 storage in a geological formation depends on the presence of a secure and impermeable caprock, such as a shale formation. However, the existing literature lacks information on the kinetics of H2 adsorption in actual shale formations with diverse organic contents and mineral compositions. Therefore, the kinetics of H2 adsorption in organic-rich shale samples from a Jordanian oil (JO) source rock formation are experimentally investigated herein at various temperatures (193, 273, 303, and 333 K) and two equilibrium pressures (15 and 45 bar) by using a volumetric method. The impact of mineral compositions and total organic content (TOC) on H2 adsorption is studied using two samples with distinct mineralogy and TOC values. Thermodynamic calculations are performed, and common adsorption models are used to analyze the experimental data. The results indicate that the H2 adsorption rate increases with pressure and decreases with temperature, being characterized by an initial rapid adsorption phase followed by a slower adsorption period as the uptake of H2 approaches equilibrium. More interestingly, the rate of H2 adsorption is higher in the sample with a high TOC and a richer composition of carbonate minerals. Both the applied adsorption isotherm models and adsorption kinetics models fit the experimental data remarkably well, thereby indicating their suitability for analyzing the kinetics of H2 adsorption in the JO shale. The unipore model matches the H2 kinetics data well, with R2 > 0.91. The H2 diffusion coefficient increases with pressure and temperature, where the H2 diffusion in shale accelerates with thermal motion intensity. This study provides fundamental insights into the adsorption kinetics of H2 and is expected to assist in implementing an industrial H2-based economy.

Hydrogen storage with gravel and pipes in lakes and reservoirs

Climate change is projected to have substantial economic, social, and environmental impacts worldwide. Currently, the leading solutions for hydrogen storage are in salt caverns, and depleted natural gas reservoirs. However, the required geological formations are limited to certain regions. To increase alternatives for hydrogen storage, this paper proposes storing hydrogen in pipes filled with gravel in lakes, hydropower, and pumped hydro storage reservoirs. Hydrogen is insoluble in water, non-toxic, and does not threaten aquatic life. Results show the levelized cost of hydrogen storage to be 0.17 USD kg−1 at 200 m depth, which is competitive with other large scale hydrogen storage options. Storing hydrogen in lakes, hydropower, and pumped hydro storage reservoirs increases the alternatives for storing hydrogen and might support the development of a hydrogen economy in the future. The global potential for hydrogen storage in reservoirs and lakes is 3 and 12 PWh, respectively. Hydrogen storage in lakes and reservoirs can support the development of a hydrogen economy in the future by providing abundant and cheap hydrogen storage.

ASSESSMENT OF THE IMPACT OF WELL GRID DENSITY ON OIL RECOVERY UNDER CONDITIONS OF UNCERTAINTY

The density of the well grid is one of the most important parameters that has a significant impact on the rate and amount of oil reserves extraction. As practice shows, existing approaches to the reliable assessment and identification of the degree of influence of this indicator on oil recovery do not allow us to adequately form an idea of the dynamics of reservoir processes and their role in making managerial decisions in conditions of uncertainty. Taking into account the decrease in the number of hydrodynamic and geophysical studies conducted in relation to the total number of wells in operation at fields that are being developed for a long time or just being put into development, the issue of predicting the oil recovery coefficient according to the list of geological and field parameters remains open and requires an urgent solution, including those related to the use of unique complex algorithms. The purpose of the work is to determine the relationship between the density of the well grid and the final coefficient of oil recovery in the development of fields in natural conditions using computer modeling systems. The research methodology consists of the use of existing scientific and methodological approaches to the processing of geological and commercial information in conditions of different densities in combination with the use of various advanced systems for identifying hidden patterns. Geological and statistical models have been defined for the oil deposits of the Famensk tier of the South Tatar arch of the Volga-Ural oil and gas province, allowing for the forecasting procedure for groups of objects identified during differentiation, subject to the dynamic density of geological and field information and various technical and economic indicators of field development. A comprehensive interpretation of the nature and degree of influence of geological and technological parameters on the amount of oil reserves production has been carried out. The need for preliminary differentiation of deposits based on identification with the subsequent use of the presented geological and statistical models to reduce the risks of making erroneous decisions during activities aimed at optimizing the development of analog facilities and rational extraction of residual oil reserves is reliably substantiated.

Integrated Sequence Stratigraphic and Seismic Facies Analysis for Hydrocarbon Prospectivity of the Taranaki Basin, New Zealand

This study analyses the hydrocarbon potential and basin characteristics of the Taranaki Basin in New Zealand, the country's primary petroleum-producing region. The research, which uses a robust methodology involving 2D seismic data, well logs, and other geological information, examines the basin's stratigraphy, structural features, and petroleum systems. Key findings include the identification of two genetic sequences with associated system tracts, multiple reservoir and source rock units, and both structural and stratigraphic trapping mechanisms. Seismic facies analysis revealed eight distinct facies types which characterize the depositional environments. Play fairway mapping identified sweet spots where all petroleum system elements overlap. Risk assessment highlighted factors like gas chimneys and fault-compromised seals. The study concludes by presenting the geologic chance of success for three identified plays and one prospect in different stratigraphic intervals. This comprehensive analysis provides new insights into the under-explored portions of the Taranaki Basin and its hydrocarbon potential. By enhancing the understanding of the basin's stratigraphic architecture and depositional history, this study aims to improve reservoir distribution and quality predictability. Moreover, integrating seismic facies analysis with sequence stratigraphy offers a robust tool for delineating potential hydrocarbon-bearing zones, thereby reducing exploration risk and aiding the efficient reassessment of existing prospective zones and future exploration efforts.

Multidisciplinary hydrogeochemical and isotopic assessment of the Pordenone Plain (Northeastern Italy) for water resources sustainability

This study aims to comprehensively characterize the hydro-geochemical and isotopic features of the complex groundwater system in the Pordenone Plain (northeastern Italy). The area is an important industrial and agricultural area exposed to severe anthropogenic pressure and climate change, which put its water resources at risk in terms of quantity and quality, making it of high scientific and social interest. The hydrogeological setting of the Pordenone Plain has been previously simplified as a phreatic continuous aquifer in the High Plain that changes into a multilayered aquifer system towards the Low Plain. However, this study reveals significant lithological and structural heterogeneities in the High Plain that exert a strong influence on its subsurface hydrodynamics. All waters exhibit a Ca(Mg)–HCO3 composition with relatively high Na–K values in the aquifers of the Low Plain likely related to cation exchange processes. Water stable isotopes (δ2H–H2O and δ18O–H2O) indicate that the deep aquifers in the Low Plain are confined by impermeable geological formations, such as clays and siltstones, which entirely restrict water mixing with shallower aquifers. Concurrently, tritium analysis provides evidence of slow recharge and flow rate. Three primary groundwater flows have been identified within the plain, as follows: 1) a surface flow that affects the unconfined or semi-confined aquifers of the High Plain hosted in gravelly sediments; 2) an intermediate flow fed by the pedemontane zone, which includes unconfined deep aquifers of the High Plain, semi-confined/shallow aquifers (at a depth of 40–50 m) located near the resurgence belt area and karst springs located in eastern pedemontane of the Cansiglio Plateau; 3) a deep flow fed by the mountainous zone that affects the deep confined aquifers of the Low Plain. A reliable hydrogeochemical conceptual model has been developed to explain the compositional variability of the studied waters, providing valuable insights for the sustainable management of groundwater resources in the Pordenone Plain.

The primary porosity heterogeneity characteristics of braided river sandbody and implications for predicting the current physical properties heterogeneities

Understanding the heterogeneity of reservoirs is crucial for enhancing the efficiency of hydrocarbon exploration and development. The primary porosity of samples from modern braided river sands and outcrops of braided river sandstone was calculated using a model previously proposed by the authors. The characteristic parameters (Vx) for calculating primary porosity are closely related to the architectural–elemental configurations (AEC), and the AEC of braided river sand bodies (BRSD) has apparent effects on the distribution of the primary porosity heterogeneities. Analysis of our results has established a simple primary porosity heterogeneity model of BRSD. The center of braided river channel and mid-channel bars have excellent strong primary petrophysical properties with high primary porosity exceeding 38%. The contact areas between the braided river channel and channel bars exhibit relatively low primary porosities of less than 33%. The area between the center and edge of the braided bars and channels displays medium primary porosities. The nonlinear correlation in the Q–Q plot of the primary porosity and present porosity of samples from BRSD in the Ahe Formation is mainly caused by chemical diagenesis. The present porosity heterogeneity of BRSD in the Ahe Formation is less influenced by compaction and cementation, it predominantly arises from the differential of dissolution. Q–Q plots attempt to correlate the geological information from an individual sample with the heterogeneity of present porosity in BRSD. In addition, by utilizing Q–Q plots of the primary and current petrophysical properties of the sand body, the relative extent of heterogeneity modification caused by different diagenetic processes can be assessed. This assessment is crucial for modeling macroscopic models of physical properties during geological history periods.

Geological Setting and Formation of the Erosional Structure of Upper Miocene Deposits in Western Ciscaucasia

Geological Setting and Formation of the Erosional Structure of Upper Miocene Deposits in Western Ciscaucasia

Advancing geological image segmentation: Deep learning approaches for rock type identification and classification

This study aims to tackle the obstacles linked with geological image segmentation by employing sophisticated deep learning techniques. Geological formations, characterized by diverse forms, sizes, textures, and colors, present a complex landscape for traditional image processing techniques. Drawing inspiration from recent advancements in image segmentation, particularly in medical imaging and object recognition, this research proposed a comprehensive methodology tailored to the specific requirements of geological image datasets. To establish the dataset, a minimum of 50 images per rock type was deemed essential, with the majority captured at the University of Las Palmas de Gran Canaria and during a field expedition to La Isla de La Palma, Spain. This dual-source approach ensures diversity in geological formations, enriching the dataset with a comprehensive range of visual characteristics. The study involves the identification of 19 distinct rock types, each documented with 50 samples, resulting in a comprehensive database containing 950 images. The methodology involves two crucial phases: initial preprocessing of the dataset, focusing on formatting and optimization, and subsequent application of deep learning models—ResNets, Inception V3, DenseNets, MobileNets V3, and EfficientNet V2 large. Preparing the dataset is crucial for improving both the quality and relevance, thereby to ensure the optimal performance of deep learning models, the dataset was preprocessed. Following this, transfer learning or more specifically fine-tuning is applied in the subsequent phase with ResNets, Inception V3, DenseNets, MobileNets V3, and EfficientNet V2 large, leveraging pre-trained models to enhance classification task performance. After fine-tuning eight deep learning models with optimal hyperparameters, including ResNet101, ResNet152, Inception-v3, DenseNet169, DenseNet201, MobileNet-v3-small, MobileNet-v3-large, and EfficientNet-v2-large, comprehensive evaluation revealed exceptional performance metrics. DenseNet201 and InceptionV3 attained the highest accuracy of 98.49% when tested on the original dataset, leading in precision, sensitivity, specificity, and F-score. Incorporating preprocessing steps further improved results, with all models exceeding 97.5% accuracy on the preprocessed dataset. In K-Fold cross-validation (k = 5), MobileNet V3 large excelled with the highest accuracy of 99.15%, followed by ResNet101 at 99.08%. Despite varying training times, models on the preprocessed dataset showed faster convergence without overfitting. Minimal misclassifications were observed, mainly among specific classes. Overall, the study's methodologies yielded remarkable results, surpassing 99% accuracy on the preprocessed dataset and in K-Fold cross-validation, affirming the efficacy in advancing rock type understanding.

Evaluation of land use and geological effect on groundwater characteristics in Bandung metropolitan using a hydrochemical and statistical approach

Abstract Groundwater is often used as clean water since it requires less water treatment. However, the quality will depend on the environmental conditions and human activities. Our research is conducted in Bandung Metropolitan, an urbanized area where groundwater is preferable, but the quality is becoming concerning. The objective of this study is to determine whether natural or human activities have a greater impact on groundwater quality. A total of 113 samples were collected from nine geological conditions spanning three primary land use types. The samples were analyzed for seven major ions (Na+, K+, Ca2+, Mg2+, HCO3 −, SO4 2 −, and Cl−), which occur naturally in natural water but may be elevated due to human activities. Based on the Piper diagram, fifty-three samples are categorized as Ca-HCO3, with the dominant cation being Ca2+ and the dominant anion being HCO3 −. Furthermore, the multivariate statistical analysis reveals that 74% of all ions are related to geological conditions and anthropogenic activities. In detail, high contents of Ca2+, as the dominant cation, are significantly correlated by all land uses and most geological formations. In addition, cation contents were significantly correlated with land uses, but the correlation varied for each type of geological formation. All land uses surely correlate with all major ions, but the geology depends on the type of formation.

Heterogeneous reservoir seepage characterized by geophysical, hydrochemical, and hydrologic methods

Seepage characterization from reservoirs is challenging for various environmental and water resource applications. Nonintrusive geophysical methods can achieve excellent detection results, but they cannot provide a quantitative description of the amount of seepage. Integrating geophysical methods with traditional hydrochemical and hydrologic methods enables simultaneous localization and quantitative analysis of heterogeneous reservoir seepage. Ground and waterborne electrical resistivity tomography are used to scan a reservoir under a typical cutoff wall antiseepage system, and the measurements reveal the northern preferential infiltration area. The hydrochemical results reveal that the seepage bypass of the cutoff wall has led to evident ion concentration variations in groundwater near the dam. Based on the geologic stratum information, the typical cutoff wall antiseepage system is divided into three scenarios for numerical simulation to calculate the seepage. The total seepage of the reservoir over 15 months is approximately 7.15 × 106 m3, which is consistent with traditional water budget methods. However, in the northern part of the reservoir, only 27% of the entire dam contributes 77% of the total seepage. All methods have confirmed that the heterogeneous seepage is caused by the absence of an antiseepage seal in the northern region, which should be a primary focus for future monitoring and operational efforts. With the geophysical results undergoing extensive cross-validation, the results from the preceding methods are comprehensively leveraged, effectively lowering uncertainties and overcoming the limitations of geophysical methods in quantitatively characterizing seepage.

GIS based Soil Erosion Susceptibility Mapping in Middle Himalayas using MCDM: A Case Study of Rajouri District.

The Pirpanjal range, nestled within the Himalayan region, confronts substantial soil erosion challenges owing to its diverse topography and the inherent instability of geological formations. This study focuses on the Rajouri region, to assess soil erosion susceptibility and spatially prioritize vulnerable zones. Utilizing a Geographical Information System (GIS)-based approach, we employed the Analytic Hierarchy Process (AHP) and the Weighted Sum Method (WSM). Various datasets, including precipitation records, geological maps, soil maps, and satellite imagery, were incorporated to derive eleven critical factors. These factors encompassed topographical derivatives; land use and land cover (LULC), soil properties, drainage patterns, rainfall data, lithological characteristics, wetness index, and the vegetative health of the area. The methodology employed yielded unbiased and reliable ratings and weightages, as substantiated by a Consistency Ratio (CR) of 0.095. The results reveal that 41% of the total area in the study region is exceedingly vulnerable to soil erosion. Slope variations range from 0 to 67.14 degrees, delineating high and very high susceptibility zones spanning 531.79 km² (19.82%) and 316.20 km² (11.78%) of the area, respectively. Additionally, assessments based on the Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI) underscore the severity of soil erosion, covering 40% and 25% of the highly susceptible zones, respectively. High drainage density and curvature zones were identified in 13% and 31% of the study area, respectively. This comprehensive study contributes valuable insights for the planning and implementation of effective soil conservation measures in the Rajouri region.