The naturally fractured reservoirs are one of the most challenging due to the tectonic movements that are caused to increase the permeability and conductivity of the fractures. The instability of the permeability and conductivity effects on the fluid flow path causes problems during the transfer of the fluids from the matrix to the fractures and fluid losses during production. In addition, these complications made it difficult for engineers to estimate fluid flow during production. The fracture properties’ study is important to model the fluid flow paths such as the fracture porosity, permeability, and the shape factor, which are considered essential in the stability of fluid flow. To examine this, this research introduced new models including decision tree (DT), random forest (RF), K-nearest regression (KNR), ridge regression (RR), and LASSO regression model,. The research studied the fracture properties in naturally fractured reservoirs like the fracture porosity (FP) and the shape factor (SF). The datasets used in this study were collected from previous studies “i.e., Texas oil and gas fields” to build an intelligence-based predictive model for fluid flow characteristics. The prediction process was conducted based on interporosity flow coefficient, storativity ratio, wellbore radius, matrix permeability, and fracture permeability as input data. This study revealed a positive finding for the adopted machine learning (ML) models and was superior in using statistical accuracy metrics. Overall, the research emphasized the implementation of computer-aided models for naturally fractured reservoir analysis, giving more details on the extensive execution techniques, such as injection or the creation of artificial cracks, to minimize hydrocarbon losses or leakage.
For companies, notably in the realms of energy and power supply, the essential requirement for highly efficient thermal transport solutions has become a serious concern. Current research highlighted the use of metallic oxides and carbon-based nanofluids as heat transfer fluids. This work examined two carbon forms (PEG@GNPs & PEG@TGr) and two types of metallic oxides (Al2O3 & SiO2) in a square heated pipe in the mass fraction of 0.1 wt.%. Laboratory conditions were as follows: 6401 ≤ Re ≤ 11,907 and wall heat flux = 11,205 W/m2. The effective thermal–physical and heat transfer properties were assessed for fully developed turbulent fluid flow at 20–60 °C. The thermal and hydraulic performances of nanofluids were rated in terms of pumping power, performance index (PI), and performance evaluation criteria (PEC). The heat transfer coefficients of the nanofluids improved the most: PEG@GNPs = 44.4%, PEG@TGr = 41.2%, Al2O3 = 22.5%, and SiO2 = 24%. Meanwhile, the highest augmentation in the Nu of the nanofluids was as follows: PEG@GNPs = 35%, PEG@TGr = 30.1%, Al2O3 = 20.6%, and SiO2 = 21.9%. The pressure loss and friction factor increased the highest, by 20.8–23.7% and 3.57–3.85%, respectively. In the end, the general performance of nanofluids has shown that they would be a good alternative to the traditional working fluids in heat transfer requests.
The current research includes study the effect of internal sulfate (Calcium sulfate) on mechanical properties of normal and light weight concrete. The mechanical properties included compressive, splitting tensile, and flexural strength. The experimental work consists of casting and testing 216 cubes (150×150×150) mm, 216 cylinders (200×100) mm, and 144 prisms (400×100×100) mm having different condition including: ratio of the sulfate, the age test, type of concrete, and type of cement. This research consists of two part normal and light weight concrete, each part divided to three groups according to type of cement (type I cement, type V cement, and type I cement with 15% silica fume replacing from weight of cement). Each group consisting of four set with different ratio of sulfate (0.28% (reference SO3), 0.5%, 1% and 1.5%) by weight of fine aggregate where these ratios approximate the actual reality of the sulfates present in internal concrete components such as sand, each set having nine cubes tested in a different age (28, 60, and 90) days. The experimental results show that the harmful effect of internal sulfate in concrete on mechanical properties was decreased by using type I cement with 15% silica fume replacement whether normal and light weight concrete. Using of silica fume concrete is more effective to enhance the concrete resistance to internal sulfate attack.
Extreme climatic conditions and natural hazard-related phenomenon have been affecting coastal regions and riverine areas. Floods, cyclones, and climate change phenomena have hammered the natural environment and increased the land dynamic, socio-economic vulnerability, and food scarcity. Saltwater intrusion has also triggered cropland vulnerability and, therefore, increased the area of inland brackish water fishery. The cropland area has decreased due to low soil fertility; around 252.06 km2 of cropland area has been lost, and 326.58 km2 of water bodies or inland fishery area has been added in just thirty years in the selected blocks of the North 24 Parganas district, West Bengal, India. After saltwater intrusion, soil fertility appears to have been decreased and crop production has been greatly reduced. The cropland areas were 586.52 km2 (1990), 419.92 km2 (2000), 361.67 km2 (2010) and 334.46 km2 (2020). Gradually the water body areas were increased 156.21 km2 (1990), 328.15 km2 (2000), 397.77 km2 (2010) and 482.78 km2 (2020). The vegetated land area also decreased due to it being converted into inland fishery areas, and around 79.15 km2 were degraded during the last thirty years. The super cyclone Aila, along with other super cyclones and other environmental stresses, like water-logging, soil salinity, and irrigation water scarcity were the reasons for the development of the new fishery areas in the selected blocks. There is a need for proper planning for sustainable development of this area.
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