The increasing demand for freshwater supplies and the effects of climate change in arid and hyper-arid regions are pushing governments to explore new water resources for food security assurance. Groundwater is one of the most valuable water resources in these regions, which are facing water scarcity due to climatic conditions and limited rainfall. In this manuscript, we provide an integrated approach of remote sensing, geographic information systems, and analytical hierarchical process (AHP) to identify the groundwater potential zone in the central Eastern Desert, Egypt. A knowledge-driven GIS-technique-based method for distinguishing groundwater potential zones used multi-criteria decision analysis and AHP. Ten factors influencing groundwater were considered in this study, including elevation, slope steepness, rainfall, drainage density, lineament density, the distance from major fractures, land use/land cover, lithology, soil type, and the distance from the channel network. Three classes of groundwater prospective zones were identified, namely good potential (3.5%), moderate potential (7.8%), and poor potential (88.6%) zones. Well data from the study area were used to cross-validate the results with 82.5% accuracy. During the last 8 years, the static water level of the Quaternary alluvium aquifer greatly decreased (14 m) due to excessive over pumping in the El-Dir area, with no recorded recharges reaching this site. Since 1997, there has been a noticeable decline in major rainfall storms as a result of climate change. The current study introduces a cost-effective multidisciplinary approach to exploring groundwater resources, especially in arid environments. Moreover, a significant modern recharge for shallow groundwater aquifers is taking place, even in hyper-arid conditions.

Sand production is one of the major challenges in the oil and gas industry, so a comprehensive geomechanical analysis is necessary to mitigate sand production in mature fields. As the pore pressure drastically decline in depleted reservoirs, the sand production risk becomes more critical and needs to be studied. However, the absence of key logs in many wells is a big challenge in the petroleum industry, and most geologists and engineers use empirical equations to predict missed log intervals. We conducted a comprehensive geomechanical modeling study on a full set of logs from two wells from the Hilal field, Gulf of Suez, Egypt, to infer the geomechanical elements and predict sand production. We have used the multi-arm calipers to calculate the actual depth of damage ratio to validate the geomechanical parameters in the prognosis model and confirm the stress orientations. We used machine learning approach to infer key sonic log in X-10 well to replace the empirical equations. The multi-arm calipers analysis showed an observed anisotropy in the hole diameter size with more enlargement in the ENE direction and fits with the minimum horizontal stress direction in the direction of N 60^oE. The later also deduced the maximum horizontal stress direction in N150 ° based on the induced fractures from borehole image data in a nearby field. We developed and compared two sand management models: one using empirical equation and the other using machine learning. The model driven by the Gardner equation suggests sand production from day one, which is not matched with the production data, while the model driven by machine learning suggests no sand production risk, which is matched with the actual production data. Our results demonstrate the advantage of using machine learning technique in geomechanical studies on the classical empirical equations in the area of study that can be applied in other basins. The findings of this study can help with a better understanding of the implications of machine learning on geomechanical characterization and sand management.

The Abu Gharadig Basin is regarded as one of the most essential in Egypt, serving as the country’s second most important reservoir for hydrocarbon production. Our present study is focused on the investigation of geothermal resources in the Abu Gharadig Basin. Using airborne magnetic and gravity surveys, as well as temperature well records, we can identify possible geothermal sources in this region. Power spectral analysis was used on the airborne magnetic measurements to compute the Curie Point Depths (CPDs) and display the temperature gradients and heat flows regime in the study area, while on the gravity data, 3-D density inversion was used to identify the basement surface. Real data from bottom-hole temperature (BHT) logs and geological data (structural and stratigraphic data from prior studies) were used to cross-validate the geophysical maps and to ascertain the stratigraphy and structural setting beneath the study location. The depth of the basement rock, according to the studies, ranges from 4.5 to 7 km, and the CPDs run from 17 to 22 km. Furthermore, the estimated temperature gradients vary from 25 to 34 degrees Celsius per kilometer, whereas the heat flows vary from 52 to 86 mW/m². Generally, there is a correlation between shallow curie depths, uplifts on basement rocks, and sites of high heat flow, indicating that basement rocks are primarily accountable for the geothermal potential of the basin.

Quaternary deposits represent the main aquifer in investigated region. currently, Groundwater contamination has become an important issue. The goal of this research is to determine the hydrochemical properties and the impact of anthropogenic activity on the groundwater. To do that, 40 water samples from surface and groundwater were collected and examined for major ions and trace elements. The western regions of the area have high TDS, Na, Ca, SO4, and Cl levels, indicating the presence of local pollution sources arising from the seepage from household, agricultural, and industrial wastes of a densely populated area. The concentration of iron, cadmium, aluminum, and manganese are above permissible levels at most of the groundwater area. Piper and Chadha diagrams revealed that The water type evolved from Ca–Mg–HCO3 in Nile waters to Na–Cl–SO4 at the western side, and then from Na–Cl–SO4 to Ca–Mg–HCO3 due to the dilution and mixing of (Ca–Mg–HCO3) infiltrated water from (EL-Ibrahimia canal, irrigation canals and agriculture land). The PCA, binary plots, and saturation indices revealed that weathering of carbonates and evaporites, cation exchange, and human activities are the main factors behind the geochemical evolution of groundwater.

Analysis of microtremors, especially the high-frequency seismic signals (HFSS), emitted from shallow sources in the frequency domain 20–20,000 Hz, can be used in investigating various hazard causes, such as landslides, sinkholes, avalanches, shallow cavities and many other applications. These seismic signals can provide knowledge about shallow Earth structure in soil investigations aimed at reducing geological hazards. This technique integrated other geophysical techniques to determine the possible locations of future sinkhole collapses in the Gharabanyat area, located west of Alexandria, Egypt, which is extremely vulnerable to this kind of hazard. Approximately 1 km profile of electrical resistivity tomography, multichannel analysis of surface waves, seismic refraction tomography, and deep ground penetrating radar, combined with borehole drilling data, were used to reconstruct how these sinkholes occurred within the study area. No single geophysical tool was able to predict impending collapse events; however, their integration highlighted the possible locations of collapses expected in the near future, and the study of high-frequency seismic signals (HFSS) in the audible frequency range of 20–20,000 Hz proved particularly helpful for this purpose. This was achieved by recording "high-frequency microtremor signals" at 42 stations, whose analysis showed a possible correlation between areas where only low-frequency signals are detected and the areas of previous collapses. It was concluded that low-frequency signals can be used to identify the possible locations of future collapses and as part of a warning system. The phenomenon of sinkhole collapses is expected to keep taking place unless an adequate solution is found to control the flow of water into the subsurface of the Gharabanyat region.