Empirical and statistical methodologies have been established to acquire accurate permeability identification and reservoir characterization, based on the rock type and reservoir performance. The identification of rock facies is usually done by either using core analysis to visually interpret lithofacies or indirectly based on well-log data. The use of well-log data for traditional facies prediction is characterized by uncertainties and can be time-consuming, particularly when working with large datasets. Thus, Machine Learning can be used to predict patterns more efficiently when applied to large data. Taking into account the electrofacies distribution, this work was conducted to predict permeability for the four wells, FH1, FH2, F

This work intends to develop an effective heavy metal-free modifier having properties comparable to traditional stabilizers and flame retardants, simultaneously being environmentally friendly and may be superior in many aspects. The important requirement focused on is: how to increase thermal stability and flame retardancy of flexible poly(vinyl chloride). Due to the typical materials now used with poly(vinyl chloride), which increases health and environmental concerns, utilizing a novel heavy metal-free additive will make poly(vinyl chloride) substantially safer. We have used an artificial silicate for this aim, which proved to be an efficient flame retardant and surprisingly showed excellent heat stabilizing effect. Thermal stabi

Clean energy applications widely recognize Proton Exchange Membrane Fuel Cells (PEMFCs) for their high efficiency and environmental compatibility. Accurate parameter identification of PEMFC models is essential for enhancing system performance and reliability, particularly under dynamic operating conditions. This paper presents a novel optimization-based approach called Heterogeneous Comprehensive Learning-Bald Eagle Search (HCLBES) with enhanced exploration and exploitation capabilities for the effective modeling of PEMFC. The algorithm combines the exploration strength of the Bald Eagle Search with comprehensive learning and heterogeneity mechanisms to achieve a balanced global and local search space. In this algorithm, the number

The behavior corrosion inhibition of aluminum alloy (Al6061) in acidic (0.1 M HCl) and saline (3.5% NaCl) solutions was investigated in the absence and the presence of expired diclofenac sodium drug (DSD) as a corrosion inhibitor. The influence of temperature and was studied using electrochemical techniques. In addition, scanning electron microscopy (SEM) was used to study the surface morphology. The results showed that DSD acted as a powerful inhibitor in acidic solutions, while a moderate influence was observed with saline one. Maximum inhibition efficiency was 99.99 and 83.32% in acidic and saline solutions at 150 ppm of DSD, respectively. Corrosion current density that obtained using electrochemical technique was increased with temperat