In this review, strategies for crude oil desulfurization are evaluated by reviewing desulfurization literature. The most important characteristics of crude oil that affect the market price are its sulfur content and gravity. Low sulfur content of crude oil is particularly preferred. Petroleum includes crude oil, natural gas, and heavy oil. Petroleum refineries convert crude oils and other input streams into dozens of refined (co)products. Two properties are especially useful for quickly classifying and comparing crude oils: API gravity (a measure of density) and sulfur content. Sulfur is naturally present as an impurity in fossil fuels. The removal of organosulfur compounds from crude oil is an important aspect of all countries to reduce air pollution. The sulfur compounds from gasoline are generally removed by treatment with an alkaline solution sodium plumbite. At large scales, the most economical technology for converting hydrogen sulfide into sulfur is the Claus process. This well-established process uses partial combustion and catalytic oxidation to convert about 97% of the H₂S to elemental sulfur.

The steady magnetohydrodynamic ternary hybrid nanofluid flow over a slender surface under the effects of activation energy, Hall current, chemical reactions, and a heat source has been reported. A numerical model is developed to increase the rate of energy transfer and boost the efficiency and outcome of heat energy dissemination for a diverse range of biological applications and commercial uses. The rheological properties and thermal conductivity of the base fluids are improved by framing an accurate combination of nanoparticles (NPs). The ternary hybrid nanofluid has been prepared, in the current analysis, by the dispersion of magnesium oxide, titanium dioxide (TiO₂), and cobalt ferrite (CoFe₂O₄) NPs in the base fluid. The physical phenomena have been expressed in the form of a system of nonlinear PDEs, which are degraded to a dimensionless system of ODEs through the similarity replacement and numerically solved by employing the MATLAB software package bvp4c. The graphical and tabular results are estimated for velocity, mass, and energy curves vs distinct physical factors. It has been noticed that the variation in the magnetic effect enhances the energy profile while the increasing number of ternary nanocomposites (MgO, TiO₂, and CoFe₂O₄) in water lowers the energy curve. Furthermore, the effect of both Lewis and Peclet numbers weakens the motile microbe’s profile.

Scale deposits can reduce equipment efficiency in the oil and petrochemical industry. The gamma attenuation technique can be used as a non-invasive effective tool for detecting scale deposits in petroleum pipelines. The goal of this study is to propose a dual-energy gamma attenuation method with radial basis function neural network (RBFNN) to determine scale thickness in petroleum pipelines in which two-phase flows with different symmetrical flow regimes and void fractions exist. The detection system consists of a dual-energy gamma source, with Ba-133 and Cs-137 radioisotopes and two 2.54-cm × 2.54-cm sodium iodide (NaI) detectors to record photons. The first detector related to transmitted photons, and the second one to scattered photons. The transmission detector recorded two signals, which were the counts under photopeak of Ba-133 and Cs-137 with the energy of 356 keV and 662 keV, respectively. The one signal recorded in the scattering detector, total counts, was applied to RBFNN as the inputs, and scale thickness was assigned as the output.