Chebyshev Polynomials Based Interval Inversion Approach For The Analysis Of Borehole Geophysical Data: A Case Study From Egypt

In the last few years, the interval inversion approach has shown significant success in evaluating and characterizing the hydrocarbon-bearing zones, providing an optimal overdetermination ratio for more accurate and reliable solutions. In this study, the method is used with an alternative basis function to reveal the petrophysical properties of the reservoir rock in Komombo Basin, Upper Egypt. First, the depth-dependent response functions are utilized to formulate the forward problem. Then we expand the petrophysical parameters into a series by using Chebyshev polynomials as a basis function. The Marquardt algorithm is used to solve the inverse problem. Eventually, the petrophysical parameters – which include porosity, clay content, and water saturation in the invaded and uninvaded zone of W. Al Baraka-2 well – are derived from a relatively small number of expansion coefficients. The results are evaluated by computing the errors of the estimated parameters and measuring the misfit between the observed and calculated data. The reliable estimation of the petrophysical parameters assisted in figuring the hydrocarbon potentiality of the reservoir formation in the investigated area

Electrospun nanofiber-based niflumic acid capsules with superior physicochemical properties

The aim of this study was to assess whether nanofibrous drug mats have potential as delivery systems for poorly water-soluble drugs. Amorphous nanofiber mats from a model poorly water-soluble active pharmaceutical ingredient (API), niflumic acid, together with the polymer excipient, polyvinyl pyrrolidine, were prepared by nozzle-free electrospinning. This technique offers a scalable way for drug formulation, and by increasing the surface area of the drug, the dissolution rate and therefore bioavailability of the API can be improved. In this study, both the amount of the dissolved active ingredient and the dissolution kinetics has been improved significantly when the nanofibrous mats were used in the drug formulation. A 15-fold increase in the dissolved amount of the produced amorphous niflumic acid nanofiber was observed compared to the dissolved amount of the raw drug within the first 15 minutes. Capsule formulation was made by mixing the electrospun nanofibers with a microcrystalline cellulose filler agent. When comparing the dissolution rate of the capsule formulation on the market with the nanofibrous capsules, a 14-fold increase was observed in the dissolved drug amount within the first 15 minutes

Application of GIS-based machine learning algorithms for prediction of irrigational groundwater quality indices

Agriculture is considered one of the primary elements for socioeconomic stability in most parts of Sudan. Consequently, the irrigation water should be properly managed to achieve sustainable crop yield and soil fertility. This research aims to predict the irrigation indices of sodium adsorption ratio (SAR), sodium percentage (Na%), permeability index (PI), and potential salinity (PS) using innovative machine learning (ML) techniques, including K-nearest neighbor (KNN), random forest (RF), support vector regression (SVR), and Gaussian process regression (GPR). Thirty-seven groundwater samples are collected and analyzed for twelve physiochemical parameters (TDS, pH, EC, TH, Ca+2, Mg+2, Na+, HCO3−, Cl, SO4−2, and NO3−) to assess the hydrochemical characteristics of groundwater and its suitability for irrigation purposes. The primary investigation indicated that the samples are dominated by Ca-Mg-HCO3 and Na-HCO3 water types resulted from groundwater recharge and ion exchange reactions. The observed irrigation indices of SAR, Na%, PI, and PS showed average values of 7, 42.5%, 64.7%, and 0.5, respectively. The ML modeling is based on the ion’s concentration as input and the observed values of the indices as output. The data is divided into two sets for training (70%) and validation (30%), and the models are validated using a 10-fold cross-validation technique. The models are tested with three statistical criteria, including mean square error (MSE), root means square error (RMSE), and correlation coefficient (R2). The SVR algorithm showed the best performance in predicting the irrigation indices, with the lowest RMSE value of 1.45 for SAR. The RMSE values for the other indices, Na%, PI, and PS, were 6.70, 7.10, and 0.55, respectively. The models were applied to digital predictive data in the Nile River area of Khartoum state, and the uncertainty of the maps was estimated by running the models 10 times iteratively. The standard deviation maps were generated to assess the model’s sensitivity to the data, and the uncertainty of the model can be used to identify areas where a denser sampling is needed to improve the accuracy of the irrigation indices estimates

Innovative Hydrogeophysical Approaches as Aids to Assess Hungarian Groundwater Bodies

The Hungarian water management plan has lately identified 185 groundwater bodies based on the concepts given by the European Water Framework Directive. Achieving and maintaining the good quantitative and chemical status of these groundwater bodies is of primary importance. It is demonstrated how innovative hydrogeophysical methods can be applied successfully to assess the Hungarian or other international groundwater bodies. By applying geoelectric methods, horizontal layering or large uniform rock units can be well characterized by Wenner–Schlumberger array, also enabling accurate depth determination of the shallow groundwater table. Horizontal variations in the rock type or its state can be well described by dipole–dipole array or, even better, by the newly developed quasi-null arrays. Their joint application may be very straightforward to investigate different aquifer types by giving high-resolution resistivity images as input for hydrogeological modeling. In the identification of porous formations, multivariate statistical interpretation of wireline logs using cluster analysis allows reliable lithological separation of potential aquifers. Their clay content is estimated by robust factor analysis, while their hydraulic properties are directly derived from the resistivity log. For a more effective interpretation, a combination of surface and borehole geophysical methods can be recommended for meeting challenges in hydrogeology and groundwater management

Innovative Hydrogeophysical Approaches as Aids to Assess Hungarian Groundwater Bodies

The Hungarian water management plan has lately identified 185 groundwater bodies based on the concepts given by the European Water Framework Directive. Achieving and maintaining the good quantitative and chemical status of these groundwater bodies is of primary importance. It is demonstrated how innovative hydrogeophysical methods can be applied successfully to assess the Hungarian or other international groundwater bodies. By applying geoelectric methods, horizontal layering or large uniform rock units can be well characterized by Wenner–Schlumberger array, also enabling accurate depth determination of the shallow groundwater table. Horizontal variations in the rock type or its state can be well described by dipole–dipole array or, even better, by the newly developed quasi-null arrays. Their joint application may be very straightforward to investigate different aquifer types by giving high-resolution resistivity images as input for hydrogeological modeling. In the identification of porous formations, multivariate statistical interpretation of wireline logs using cluster analysis allows reliable lithological separation of potential aquifers. Their clay content is estimated by robust factor analysis, while their hydraulic properties are directly derived from the resistivity log. For a more effective interpretation, a combination of surface and borehole geophysical methods can be recommended for meeting challenges in hydrogeology and groundwater management

Factor Analysis of Well Logs for Total Organic Carbon Estimation in Unconventional Reservoirs

Several approaches have been applied for the evaluation of formation organic content. For further developments in the interpretation of organic richness, this research proposes a multivariate statistical method for exploring the interdependencies between the well logs and model parameters. A factor analysis-based approach is presented for the quantitative determination of total organic content of shale formations. Uncorrelated factors are extracted from well logging data using Jöreskog’s algorithm, and then the factor logs are correlated with estimated petrophysical properties. Whereas the first factor holds information on the amount of shaliness, the second is identified as an organic factor. The estimation method is applied both to synthetic and real datasets from different reservoir types and geologic basins, i.e., Derecske Trough in East Hungary (tight gas); Kingak formation in North Slope Alaska, United States of America (shale gas); and shale source rock formations in the Norwegian continental shelf. The estimated total organic content logs are verified by core data and/or results from other indirect estimation methods such as interval inversion, artificial neural networks and cluster analysis. The presented statistical method used for the interpretation of wireline logs offers an effective tool for the evaluation of organic matter content in unconventional reservoirs

Hydrogeological investigations in basement terrains using geological, geomorphological and geophysical methods, Western Hamissana Area, Ne Sudan

This study aims at identifying target zones for groundwater exploration in basement terrains using geological, geomorphological, and geoelectrical methods. The study area is located on the northwestern side of the Red Sea Hills in the western Hamissana area. It is part of the Arabian Nubian Shield (ANS), which dates to the Pan-African Era. The study area is covered by Precambrian basement rocks which are overlain by alluvial deposits. The climate in the region is arid. As a result, severe water shortage is experienced. The geological and geomorphological investigations were carried out to locate potential sites for groundwater prospecting. On this basis, three categories of groundwater potential zones were delineated as good, moderate, or poor. The electrical resistivity method using vertical electrical sounding (VES) technique was used to determine the vertical geological profile of the study area. The sequence was revealed to consist of four zones: a high-resistance unsaturated zone, an intermediate-resistance water-bearing formation, a low-resistance wet weathered basement, and high-resistance fresh basement rock. Catchment boundaries were delineated using digital elevation models, and potential locations for surface and subsurface dams were proposed to improve the groundwater recharge