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In this research, a novel natural-based polymer, the Aloe Vera biopolymer, is used to improve the mobility of the injected water. Unlike most synthetic chemical polymers used for chemical-enhanced oil recovery, the Aloe Vera biopolymer is environmentally friendly, thermally stable in reservoir conditions, and compatible with reservoir rock and fluids. In addition, the efficiency of the Aloe Vera biopolymer was investigated in the presence of a new synthetic nanocomposite composed of KCl-SiO2-xanthan. This chemically enhanced oil recovery method was applied on a sandstone reservoir in Southwest Iran with crude oil with an API gravity of 22°. The Aloe Vera biopolymer’s physicochemical characteristics were initially examined using different analytical instruments. The results showed that the Aloe Vera biopolymer is thermally stable under reservoir conditions. In addition, no precipitation occurred with the formation brine at the salinity of 80,000 ppm. The experimental results showed that adding ethanol with a 10% volume percentage reduced interfacial tension to 15.3 mN/m and contact angle to 108°, which was 52.33 and 55.56% of these values, respectively. On the other hand, adding nanocomposite lowered interfacial tension and contact angle values to 4 mN/m and 48°, corresponding to reducing these values by 87.53 and 71.42%, respectively. The rheology results showed that the solutions prepared by Aloe Vera biopolymer, ethanol, and nanocomposite were Newtonian and fitted to the Herschel-Bulkley model. Finally, core flooding results showed that the application of a solution prepared by Aloe Vera biopolymer, ethanol, and nanocomposite was effective in increasing the oil recovery factor, where the maximum oil recovery factor of 73.35% was achieved, which could be attributed to the IFT reduction, wettability alteration, and mobility improvement mechanisms.

During production from oil wells, the deposition of asphaltene and wax at surface facilities and porous media is one of the major operational challenges. The crude oil production rate is significantly reduced due to asphaltene deposition inside the reservoir. In addition, the deposition of these solids inside the surface facilities is costly to oil companies. In this study, the efficiency of different solvents in dissolving asphaltene and wax was investigated through static and dynamic tests. The analysis of solid deposits from the surface choke of one of the Iranian carbonate oil fields showed that they consisted of 41.3 wt % asphaltene, and the balance was predominantly wax. In addition, the asphaltenes obtained from the surface choke solid deposits had a more complex structure than that of asphaltenes extracted from the crude oil itself. The static tests showed that xylene, toluene, gasoline, kerosene, and gas condensate had the highest efficiencies in dissolving solid deposits; conversely, diesel had a negative impact on dissolving solid deposits. Static tests on pure asphaltene showed that, among the tested solvents, gas condensate and diesel had a negative effect on the solubility of asphaltene. The dynamic core flooding results showed that asphaltene deposition inside the cores reduced the permeability by 79-91%. Among the tested solvents, xylene, gasoline, and kerosene resulted in the highest efficacy in restoring the damaged permeability, and higher efficiency was obtained with an equivalent solvent injection rate of 1 bbl/min versus 3 bbl/min.

Conocimiento del petróleo crudo La pirólisis y la combustión es una de las más importantes en la producción de petróleo utilizando el método de combustión in situ como una sección de los métodos de recuperación térmica de aceite mejorado (EOR). En este método, el petróleo crudo experimenta una serie de cambios físicos y químicos que pueden referirse a la pirólisis como la parte más importante de estos cambios. En este trabajo, hemos desarrollado modelos de Redes de Función Radial (RBFN) para predecir el peso restante de crudo durante el proceso de pirólisis del crudo. La densidad API, la viscosidad, la resina y el asfalteno y otros componentes del contenido de aceite crudo, la temperatura y la velocidad de calentamiento se seleccionan como parámetros de entrada RBFN, mientras que el peso restante de crudo en diferentes temperaturas se considera como salida de red. Los datos se obtuvieron mediante análisis termogravimétricos y experimentos de separación en seis muestras de diversos aceites crudos iraníes. Los resultados de este trabajo muestran que utilizando un RBFN, podemos predecir el peso restante de crudo durante su proceso de pirólisis con un error relativo absoluto medio (ARE) 5,88 por ciento y error cuadrático medio (MSE) 6,15 por la función newrbe y un promedio absoluto Error relativo (ARE) 7,25 por ciento y error cuadrático medio (MSE) 2,51 por función newrb para datos de prueba. Más aún, los resultados del análisis de regresión mostraron una muy buena coincidencia entre los resultados de laboratorio y los resultados previstos por la RBFN propuesta.