Browsing by Author "Sulaimon, A.A."

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Evaluation of drilling muds enhanced with modified starch for HPHT well applications
(Springer, 2020) Sulaimon, A.A.; Akintola, S.A.; Mohd Johari, A.B.M.; Isehunwa, S.O.
The use of carboxymethyl cellulose (CMC) in oil and gas well drilling operations has improved the filtration loss and mud cake properties of drilling muds. The introduction of starch has also reduced, for example, the viscosity, fluid loss, and mud cake properties of the drilling fluids. However, normal starch has some drawbacks such as low shear stress resistance, thermal decomposition, high retrogradation, and syneresis. Hence, starch modification, achieved through acetylation and carboxy-methylation, has been introduced to overcome these limitations. In this study, modified starches, from cassava and maize, were used to enhance the properties of water-based muds under high-pressure high temperature (HPHT) conditions, and their performances were compared with that of the CMC. The mud samples added with acetylated cassava or maize starch exhibited the smallest filtrate volumes and filtrate losses within the American Petroleum Institute specification. Therefore, these modified starch-added muds could replace CMC as fluid loss agents since, unlike it, they can withstand HPHT conditions.
Imidazolium-based ionic liquids as demulsifier for water-crude oil emulsion
(Elsevier Inc., 2022) Masri, A.N.; Sulaimon, A.A.; Zakaria, M.Z.; Akintola, S.A.
Most of the crude oils in the world are produced as water-crude oil emulsions. Removal of water from the emulsions is one of the major issues in industry and the process is completed before transportation and refining. One of the methods to remove water is through demulsification. In the present study, ionic liquids, non-volatile and non-toxic solvents, are used as demulsifiers. Three ionic liquids (ILs), namely 1-ethyl-3-methylimidazolium acetate (EMIM-AC), 1-butyl-3-methylimidazolium chloride (BMIM-Cl) and 1-butyl-3-methylimidazolium hydrogensulfate (BMIM-HSO4), were evaluated to treat a heterogeneous mixture of crude oil and water. The bottle tests were conducted at 60 °C and a salinity of 50,000ppm. Response surface methodology (RSM) was used to study the effect of IL type, its concentration, and residence time towards demulsification efficiency. The developed correlation gave a high correlation coefficient, R2 of 0.924. Analysis shows that the IL concentration gives the highest influence on the demulsification efficiency, followed by the residence time and the type of ionic liquid. Among the three ILs investigated, 1000ppm BMIM-HSO4 achieved the highest demulsification efficiency, where complete separation (100% demulsification efficiency) was attained within 30 minutes. BMIM-Cl achieved 72% efficiency after an hour while the EMIM-AC reached maximum separation after 52 minutes with 45% efficiency.
Screening of ionic liquids for CO2 capture using data analytics techniques
(UTP Press , Malaysia, 2023) Sulaimon, A.A.; Salang, A.R.T.; Qasim, A.; Akintola, S.A.; Wifred, C.D.A.P.
Carbon dioxide (CO2) is the most prominent greenhouse gas (GHG) present in the atmosphere, making it the most accountable for global warming. CO2 capture is capable of greatly reducing carbon emissions. The current method of CO2 capture by amine-based solvent has drawbacks, such as high demand for energy and intense corrosion, making it a less reliable method. More attention is given to ionic liquids (ILs) for their negligible vapour pressure, low melting point, and high chemical and thermal stability advantage. This study uses data analytics techniques to develop a predictive model for screening ILs for CO2 capture, moving away from the experimental approach, which is burdensome, costly, and less environmental-friendly. Data on the properties and parameters of ILs are collected from COSMO-RS software. CO2 solubility is the function of collected data and developed into 15 models of three different methods: Support Vector Machine (SVM), Neural Networks (NN), and Gaussian Process Regression (GPR). The use of data analytics in this field is new and can provide valuable insight towards CO2 solubility in ILs. The dataset is distributed randomly at 80/20% for training and testing. Each model is evaluated using R-squared and root mean square error (RMSE). The rational Quadratic GPR model shows the lowest RMSE of 0.0002 for training and testing, with R-squared the closest to one. Rational Quadratic GPR is the best model to be used for screening IL for CO2 capture.