Studies on turbulent diffusion processes and evaluation of diffusivity values from hydrodynamic observations in Corpus Christi Bay

The physical process of dispersion which can be attributed to turbulence (turbulent diffusion) or shear (shear-augmented diffusion) within the flow field is very important as it ultimately governs the distribution of constituents of interest within the environment. A series of diffusion experiments were conducted in Corpus Christi Bay, TX with the purpose of characterizing turbulent diffusion through dispersion coefficients or turbulent diffusivity, K_i (i=x, y, z) dependent on the degree of randomness or turbulence intensity, I.Measured with a boat-mounted acoustic doppler current profiler (ADCP), the Eulerian velocity time-series of fluid particles in random motion, u_i was used in the evaluation of the Eulerian time-scale of turbulence, T^E based on the velocity correlation function, R^E with T^E being related to the Lagrangian time-scale T^L through a scaling parameter, β(=T^L/T^E). Surface currents were obtained with high frequency (HF) Radar equipment deployed over the study area from which the horizontal velocity gradients were determined.Within the spatial scale of the experiment (1000 m), the observed low horizontal gradients (10⁻⁴ s⁻¹) allowed for the generation of velocity time-series from an ADCP mounted on a moving platform. A numerical scheme for evaluating turbulent diffusivity values was developed on the basis of Eulerian current measurements and calibrated through the statistics of an evolving dye patch for the scaling parameter β which in this scheme was found to be in the range 1–3.     

Classification and Diagenetic Characteristics of the Cretaceous Sandstones in the Southern Bredasdorp Basin,Offshore South Africa

A systematic petrographic and geochemical studies of 92 representative sandstone samples from exploration wells E-AH1, E-AJ1, E-BA1, E-BB1 and E-D3 in the southern part of the Bredasdorp Basin was undertaken to classify the sandstones as well as unravel the main diagenetic processes and their time relations. Petrographic study shows that the sandstones are largely subarkosic arenite and arkosic litharenite, which have underwent series of diagenetic processes as a result burial, rifting and subsequent uplift. The main diagenetic processes that have affected the reservoir properties of the sandstones are cementation by authigenic clay, carbonate and silica, growth of authigenic glauconite, dissolution of minerals and load compaction. The major diagenetic processes reducing the porosity are calcite cementation in the subarkosic arenite, and compaction and quartz cementation in arkosic litharenite. On the other hand, the formation of secondary porosity due to the partial to complete dissolution of early calcite cement, feldspars and minor grain fracturing has improved the reservoir property of the sandstone to some extent. The clay minerals in the sandstones commonly acts as pore choking cement, which reduces porosity. In general, there is no particular diagenetic process that exclusively controls the type or form of porosity evolution in the sandstones.     

Spatial prediction of landslide susceptibility in western Serbia using hybrid support vector regression (SVR) with GWO,BAT and COA algorithms

In this study, we developed multiple hybrid machine-learning models to address parameter optimization limitations and enhance the spatial prediction of landslide susceptibility models. We created a geographic information system database, and our analysis results were used to prepare a landslide inventory map containing 359 landslide events identified from Google Earth, aerial photographs, and other validated sources. A support vector regression (SVR) machine-learning model was used to divide the landslide inventory into training (70%) and testing (30%) datasets. The landslide susceptibility map was produced using 14 causative factors. We applied the established gray wolf optimization (GWO) algorithm, bat algorithm (BA), and cuckoo optimization algorithm (COA) to fine-tune the parameters of the SVR model to improve its predictive accuracy. The resultant hybrid models, SVR-GWO, SVR-BA, and SVR-COA, were validated in terms of the area under curve (AUC) and root mean square error (RMSE). The AUC values for the SVR-GWO (0.733), SVR-BA (0.724), and SVR-COA (0.738) models indicate their good prediction rates for landslide susceptibility modeling. SVR-COA had the greatest accuracy, with an RMSE of 0.21687, and SVR-BA had the least accuracy, with an RMSE of 0.23046. The three optimized hybrid models outperformed the SVR model (AUC = 0.704, RMSE = 0.26689), confirming the ability of metaheuristic algorithms to improve model performance.     

Exposure of children to heavy metals from artisanal gold mining in Nigeria: evidences from bio-monitoring of hairs and nails

Acta Geochimica - In recent times, there had been reported cases of Pb poisoning in Anka gold mining area, Northwest Nigeria. Therefore, this study was carried out to determine the extent of...     

Geochemical Evaluation of the Permian Ecca Shale in Eastern Cape Province,South Africa: Implications for Shale Gas Potential

Shale gas has been the exploration focus for future energy supply in South Africa in recent time. Specifically, the Permian black shales of the Prince Albert, Whitehill, Collingham, Ripon and Fort Brown Formations are considered to be most prospective rocks for shale gas exploration. In this study,outcrop and core samples from the Ecca Group were analyzed to assess their total organic carbon(TOC), organic matter type, thermal maturity and hydrocarbon generation potential. These rocks have TOC ranging from 0.11 to 7.35 wt%. The genetic potential values vary from 0.09 to 0.53 mg HC/g,suggesting poor hydrocarbon generative potential. Most of the samples have Hydrogen Index(HI) values of less than 50 mg HC/g TOC, thus suggesting Type-Ⅳ kerogen. Tmax values range from 318℃ to601℃, perhaps indicating immature to over-maturity of the samples. The vitrinite reflectance values range from 2.22% to 3.93%, indicating over-maturity of samples. Binary plots of HI against Oxygen Index(OI), and HI versus Tmax show that the shales are of Type II and mixed Type Ⅱ-Ⅲ kerogen.Based on the geochemical data, the potential source rocks are inferred as immature to over-matured and having present-day potential to produce gas.