Arabian Journal of Geosciences最新文献

This paper revisits the theories of Q (quality factor) as a measure of the attenuation and velocity dispersion of a wave field. Q is a dimensionless measure of energy loss per cycle, and a proper understanding is important in a variety of fields, from seismology, geophysical prospecting to acoustics of materials. Measurements for standing modes and propagating waves differ and yield the temporal and spatial Q, respectively. This distinction is largely ignored in the literature. The relationship between these Qs is investigated for a power-law stress–strain relation based on spatial fractional derivatives that describes the behavior of compressional waves when combined with the conservation of momentum equation. In addition, the relationship between the quality factors for low-loss media proposed by Knopoff et al. 60 years ago is verified.

The Bissa orogenic gold deposit is located at the contact between basic (basalt) and felsic (dacite) volcanic formations through intermediates (andesite) and graphite-intercalated sandstone-pelitic sedimentary formations. This green schist facies metamorphosed ensemble is hosted by the 15-km-long Sabcé shear zone within the Goren greenstone belt. Field investigations combined with fine microscopy enable us to define the mineralization host formations, deformation phases, and hydrothermal alteration in the Sabcé zone. The host formations (metabasalt, metasediments, metagabbro, metadacite) are affected by two deformation phases. The first deformation phase, D_1B, is a shear-type deformation that globally controls mineralization. It is taken up by the D_2B, which has a ductile-breaking deformation. The hydrothermal alteration with which the mineralization is associated is white quartz-mica-pyrite ± carbonate ± arsenopyrite, crystallization of which was manifested by veins/veinlets subparallel to parallel to D_1B. Various electron microprobe, scanning electron microscope, and LA-ICP-MS analyses show that visible gold is present in type I and II pyrites as inclusions or as microfracture fillers. LA-ICP-MS shows that in type I and II pyrites, where no visible gold is present, invisible gold is present in their distorted crystal structure as nanoparticles. The chemical association between Au-As controls the distribution of this couple in type I and II pyrites. This clearly shows that the limpid parts of arsenic-rich pyrites are where visible and invisible gold like to concentrate.

Ensuring the structural integrity and safety of foundations depends on the accurate prediction of elastic settlement. In this study, machine learning (ML) techniques are used to predict the elastic or immediate settlement of a rectangular footing in cohesionless soil. Elastic settlement occurs when an imposed load compresses the soil initially beneath a footing, causing a drop in volume and subsequent settling of the soil as the particles reorganize and compress under pressure. The aim of this study is to propose a high-performance machine learning model to predict settlement. This study uses a dataset of 200 foundation settlements to compare the K-nearest neighbor (KNN), multi-layer perceptron (MLP), and support vector regression (SVR) techniques. Five input parameters are considered, namely foundation width (B), foundation length (L), foundation depth (D), load intensity (q), and average SPT blow count (N), which are used to predict the output. The predictive power of the models is assessed using various performance parameters, such as the coefficient of determination (R²), Willmott’s index (WI), A-20 index, variance account factor (VAF), scatter index (SI), root mean square error (RMSE), mean absolute error (MAE), and median absolute deviation (MAD). Additionally, other analyses are performed, including rank analysis, radar diagram, regression plot, reliability index, William’s plot, and error matrix, to assess the best predicting model. From this study, it is observed that the performance of SVR model is better due to its higher value of R² (tr = 0.879, ts = 0.784, and overall = 0.861) and the least value of RMSE (tr = 0.79, ts = 0.068, and overall = 0.101) while predicting the elastic settlement of the footing. To examine the influence of different input parameters on the output, sensitivity analysis is performed, revealing that q is the most influential parameter among all the inputs followed by B, L, D, and N-value.

The current study examines the metamorphism, petrography characteristics, and geological structures to construct a detailed geological map of the Tahtai Logomti region. The rock types include low-grade metavolcanic, metavolcanoclastic, carbonate, and clastic metasedimentary. Both petrographic description and field studies were conducted to accurately identify the different lithologies, structural features and mineral assemblages. Field and petrographic observations show rocks that have undergone low-grade metamorphism and fall within the lower greenschist facies. Three distinct phases of deformations (D1, D2, and D3) were identified and correlated with the previous classifications. According to the result, the rocks exhibit an NW–SE trend of joints oriented vertically to sub-vertical and a NE-SW trend of foliation, consistent with the regional trend of the Mai-Kenetal syncline. Hydrothermal-induced epidotization, chloritization, and sericitization are common in the study area.

In this study, the heavy metal pollution of the groundwater contiguous to the largest waste dump site in Aba, Abia State Nigeria was investigated to determine the variation of health risks of exposure to the heavy metals with distance away from the waste dumpsite so as to generate regression models that could predict distance to the dumpsite of tolerable health risks. The concentration of the heavy metals in the groundwater was measured using atomic absorption spectrometry (AAS). Heavy metals of common pollution sources and their likely sources were determined using principal component analysis (PCA). The extent of heavy metal pollution of the groundwater was evaluated using heavy metal pollution index (HPI) and heavy metal evaluation index (HEI). The risk index (RI) and hazard index (HI) were employed in ascertaining carcinogenic and non-carcinogenic health risks respectively. The models for prediction of distances of tolerable health risks were generated using linear and polynomial regression models. Results indicate that the concentration of the heavy metals decreased with distance away from the waste dump site. Lead and cadmium had concentrations exceeding that of WHO standard at all the Boreholes at concentrations ranging from 0.03 to 1.94 mg/L for lead and 0.03 to 0.19 mg/L for cadmium. The PCA results indicate that copper and zinc had same source whereas nickel, chromium, lead and cadmium had same source with nickel and cadmium also showing an auxiliary same source. The HEI values (21 to 1401) indicate that some of the boreholes have groundwater of low heavy metal pollution whereas others are either of medium or high heavy metals pollution. The HPI values (275–4307) indicate that the groundwater for all boreholes is heavy metal polluted. The HI and RI values were significant across all boreholes and also significantly decrease with distance away from the dumpsite. The polynomial regression models were more robust in predicting the distance of tolerable health risks. Consequently, polynomial regression models as opposed to linear regression models may find utility in water quality management that is geared towards minimization of health risks.

Rockfall, a rapid and high-impact landslide phenomenon, poses significant risks to lives, infrastructure, and transportation routes in hilly and mountainous regions. This hazard is characterized by sudden occurrences, widespread impact, fluctuating magnitudes, randomness, and a high fatality rate. The present study aims to provide a knowledge base for stakeholders in infrastructure projects in hilly regions by consolidating findings from reported studies on rockfall. Through a review of reported studies, three key aspects of rockfall are discussed: kinematics, source zone identification, and modelling approaches. Factors influencing rockfall detachment, modes of motion, impact force, and fragmentation are discussed, along with challenges in identifying potential source zones and proposed advanced methodologies for more precise identification and monitoring. Various modelling approaches for assessing rockfall characteristics and trajectories are evaluated, emphasizing the significance of numerical simulations and 3D modelling for accurate evaluation and mitigation strategy assessment. The study also highlights limitations in current modelling approaches and outlines future research directions including the integration of vegetation-related factors, incorporation of fragmentation phenomenon, utilization of advanced technologies for source zone identification, and advancements in rockfall detection and prediction through deep learning techniques. The ultimate goal is to apprise the stakeholders about present tools and techniques for conducting detailed rockfall trajectory simulation and prediction, so that the most suitable rockfall mitigation and/or protection strategy can be selected and implemented based on the specific characteristics of the site.

This paper presents the effects of the hydroelectric reservoir on the water quality in Bajo Anchicaya, a hydropower plant in the southwest of Colombia. The study implicated the comparison of water quality at five sites: before the reservoir, entering the reservoir, at the intake, in the reduced channel, and downstream of the hydropower plant discharge. The data collected were analyzed with the analysis of variance (ANOVA) statistical tool to investigate the significance of the reservoir, season, and the hydropower plant operation on the water quality. The IPOMO (pollution index by organic matter) showed that contamination by organic matter in all cases was none or low, the IPOSUS (pollution index by suspended solids) showed that there was no contamination by suspended solids, and the WQI (water quality index) showed good results. From the ANOVA results, season (flow) and hydropower plant are all significant about the water quality. ANOVA also showed a positive effect of the hydropower plant operation on water quality in terms of the Settleable solids and electrical conductivity in the water. Studies like these can improve the understanding of the influence of reservoirs and hydropower plants on water quality to implement water resource management strategies that maintain good water quality indices and prevent its deterioration.

As the need for food crops and other agricultural goods continues to rise, there is an apparent shift towards intensive agricultural land usage and growth in the Koch Bihar district of West Bengal. However, the quantity of land accessible for agriculture, its location and its suitability for farming have not been adequately investigated. Finding suitable land for agriculture in the Koch Bihar district with the aid of multiple physical, hydrological, climatic and infrastructural variables is the primary objective of this present study. Therefore, eighteen causative factors, including geomorphology, slope, elevation, land use and land cover, soil texture, rainfall, groundwater depth, modified soil adjusted vegetation index, temperature, river density, topographic wetness index, distance from road, organic carbon, soil pH, total nitrogen, cation exchange capacity, bulk density, and silt particles, were considered for land suitability analysis using Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and Vise Kriterijumska Optimizacijaik Ompromisno Resenje (VIKOR) models. Results showed that in the TOPSIS model, most of the region (36.88%) was classified as moderately suitable, followed by 27.60% as marginally suitable, 17.87% as highly suitable, 14.57% as currently not suitable and 3.08% as unsuitable for agriculture. In contrast, 34.26% of the region was categorized as moderately suitable and 20.56% as highly suitable in the VIKOR model. 350 Ground Control Points (GCP) from the study area that represented a variety of topographical and LULC conditions were examined for the model validation. With an appropriate degree of discrimination, shown by the area under the curve value of 0.911, VIKOR has demonstrated a great result between the two models. Identifying and mapping suitable agricultural land is essential for sustainable development because it provides food security, optimizes resource usage, protects the environment, enables land use planning and promotes economic growth.

Geophysical electrical resistivity surveys were carried out in a small lake named as “Nagi lake” located at Namthang, South District, Sikkim, India, for determining the source of in-situ seepage of lake water. Preliminary investigation suggests that the water seepage problem increased after the extension of the lake or after making a check dam surrounding the extended lake. The present study characterizes the origin of water seepage through an unknown fracture in the subsurface of “Nagi Lake.” Seepage path directions were demarcated with the help of an Azimuthal method, whereas sites of fractured areas causing lake water leakages were analyzed via Electrical sounding and profiling techniques. Maps of the fractured zone were developed with the help of a statistical analysis method, also known as the factor method of the traditional vertical electrical sounding (VES) that is ambiguous in method of curve matching. Main emphasis was given to locate subsurface fractures and their orientation. Delineation of location of subsurface fractures and their treatment will aid in minimizing the seepage of water from the lake. Retention of water throughout the year in lake will boost tourism near Nagi Lake area as well as aid in promoting water security in the region.

Unconventional oil and gas resources are characterized by low abundance and strong heterogeneity. Effective sweet spot prediction and mining technology are important for their efficient development. At present, the exploration and development of coalbed methane in the Santanghu Basin is still in the initial stage. Many problems in coalbed methane sweet spot prediction and mining technology seriously restrict the efficient development of coalbed methane resources. In order to study the most suitable evaluation indexes and methods for sweet spot prediction of coalbed methane development in Tiaohu-Malang Depression of Santanghu Basin, various technical means such as high-pressure mercury injection experiment, liquid nitrogen adsorption, and nuclear magnetic resonance are jointly used to analyze the occurrence state and mining technical conditions of coalbed methane in this area, establish a coalbed methane resource evaluation system, and accurately predict the sweet spot area of coalbed methane development. The results show that the main buried depth of the No.9 coal seam of Xishanyao Formation in Tiaohu-Malang Depression is 600–2600 m, and the thickness of coal seam is 5.0–60.9 m. The proportion of pore size volume of No.9 coal seam in the T1 well is mainly large pores and micropores, the proportion of mesopores is slightly smaller, and the specific surface area is opposite. The open pores of coal samples are more developed and the connectivity is better. The smaller pore size section of the coal sample is larger. When the P/P₀ value of the coal sample is about 0.5, there are sudden drop points and more ink bottle-shaped pores are developed. The lithology of the roof and floor is mainly mudstone, and the occurrence condition of coalbed methane is superior. Based on the geological conditions of coalbed methane in this area and the experience of coalbed methane exploration and development at home and abroad, 14 index evaluation indexes such as coal seam thickness, burial depth, lithology of coal seam roof and floor, structure, and so on are optimized and optimized. The sweet spot area of coalbed methane (type I area) is predicted to be mainly distributed in the northeast of Tiaohu Depression and the west of Malang Depression. Taking T1-5 well as an example, the five-stage dual-pressure control method is adopted in the drainage system. The bottom well flow pressure drop is controlled to be ≤ 0.02 MPa/d in the pressure holding and production release stages, and the bottom well flow pressure drop is ≤ 0.01 MPa/d in the stable production stage. The above methods and technologies have achieved initial results in the development of well T1-5, with the highest gas production of 2297 m³/d and the average gas production of 1300 m³/d, showing good gas production effect, which has important guiding significance for the subsequent efficient development of low-rank coalbed methane in Santanghu Basin.