scholarly journals Extra-Heavy Crude Oil Viscosity Reduction Using and Reusing Magnetic Copper Ferrite Nanospheres

Processes ◽  
2021 ◽  
Vol 9 (1) ◽  
pp. 175
Author(s):  
Lucía Mateus ◽  
Esteban A. Taborda ◽  
Carlos Moreno-Castilla ◽  
María Victoria López-Ramón ◽  
Camilo A. Franco ◽  
...  
Keyword(s):  
Crude Oil ◽  
Heavy Oil ◽  
Solvothermal Method ◽  
Sio2 Nanoparticles ◽  
Viscosity Reduction ◽  
Copper Ferrite ◽  
Dynamic Rheology ◽  
Oil Viscosity ◽  
Fixed Concentration ◽  
Heavy Crude

The main objective of this study is the synthesis, use, and reuse of magnetic copper ferrite nanospheres (CFNS) for extra-heavy oil viscosity reduction. The CFNS were synthesized using a solvothermal method resulting in mean particle size of 150 nm. Interactions of CFNS with the crude oil were evaluated through asphaltene adsorption isotherms, as well as static and dynamic rheology measurements for two cycles at 25 °C. Adsorption and desorption experiments corroborated that most of the asphaltenes adsorbed can be removed for nanoparticle reuse. During the rheology tests, nanoparticles were evaluated in the first cycle at different concentrations from 300 to 1500 mg/L, leading to the highest degree of viscosity reduction of 18% at 500 mg/L. SiO2 nanoparticles were evaluated for comparison issues, obtaining similar results regarding the viscosity reduction. After measurements, the CFNS were removed with a magnet, washed with toluene, and further dried for the second cycle of viscosity reduction. Rheology tests were performed for a second time at a fixed concentration of 500 mg/L, and slight differences were observed regarding the first cycle. Finally, changes in the extra-heavy oil microstructure upon CFNS addition were observed according to the significant decrease in elastic and viscous moduli.

Heavy crude oil viscosity reduction and rheology for pipeline transportation

Fuel ◽  
2010 ◽  
Vol 89 (5) ◽  
pp. 1095-1100 ◽  
Author(s):  
Shadi W. Hasan ◽  
Mamdouh T. Ghannam ◽  
Nabil Esmail
Keyword(s):  
Crude Oil ◽  
Viscosity Reduction ◽  
Heavy Crude Oil ◽  
Pipeline Transportation ◽  
Oil Viscosity ◽  
Heavy Crude

Heavy crude oil viscosity reduction by dilution with hydrocarbons obtained via pyrolysis of polypropylene and polystyrene

2020 ◽  
Vol 38 (8) ◽  
pp. 651-658
Author(s):  
Gerardo Martínez-Narro ◽  
Cuauhtémoc Pozos-Vázquez ◽  
Alejandro Núñez-Delgado ◽  
Daniela Morán-Medellín ◽  
Virginia Elizabeth Lara-Zárate
Keyword(s):  
Crude Oil ◽  
Viscosity Reduction ◽  
Heavy Crude Oil ◽  
Oil Viscosity ◽  
Heavy Crude

scholarly journals Reduction of heavy oil viscosity through ultrasound cavitation assisted by NiO nanocrystals-functionalized SiO2 nanoparticles

DYNA ◽  
2018 ◽  
Vol 85 (207) ◽  
pp. 153-160 ◽  
Author(s):  
Daniel Montes ◽  
Farid B. Cortés ◽  
Camilo A Franco
Keyword(s):  
Heavy Oil ◽  
Metal Oxide Nanoparticles ◽  
Catalytic Decomposition ◽  
Sio2 Nanoparticles ◽  
Viscosity Reduction ◽  
Oil Viscosity ◽  
Asphaltene Content ◽  
Before And After ◽  
Heavy Fractions ◽  
Nio Nanocrystals

The objective of this study is to reduce heavy oil viscosity through the catalytic decomposition of heavy fractions by ultrasound cavitation using metal oxide nanoparticles and water as a hydrogen donor, leading to the reduction of asphaltene content through its conversion into lighter components. NiO nanoparticles were synthesized over a 7 nm silica support using the incipient wetness technique. Emulsified heavy oil (HO) with 40%v/v of water and 13°API was used to evaluate the ultrasound cavitation process over different exposure times and nanoparticle dosages. The viscosity of the emulsified HO before and after ultrasound cavitation was measured with and without nanoparticles. Significant viscosity reduction was obtained, showing best results at 90 minutes of ultrasound exposure time with a nanoparticle dosage of 2000 mg/L, leading to a viscosity reduction at 10 s-1 and 25°C, and an asphaltene content reduction of 44 and 16%, respectively.

scholarly journals Artificial Neural Network (ANN) for Prediction of Viscosity Reduction of Heavy Crude Oil using Different Organic Solvents

2020 ◽  
Vol 26 (6) ◽  
pp. 35-49
Author(s):  
Firas K. AL-Zuhairi ◽  
Rana Abbas Azeez ◽  
Muna Kheder Jassim
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Crude Oil ◽  
Organic Solvents ◽  
Heavy Oil ◽  
Viscosity Reduction ◽  
Superior Performance ◽  
Heavy Crude Oil ◽  
Heavy Crude ◽  
Artificial Neural

The increase globally fossil fuel consumption as it represents the main source of energy around the world, and the sources of heavy oil more than light, different techniques were used to reduce the viscosity and increase mobility of heavy crude oil. this study focusing on the experimental tests  and modeling with Back Feed Forward Artificial Neural Network (BFF-ANN) of the dilution technique to reduce a  heavy oil viscosity that was collected from the south- Iraq oil fields using organic solvents, organic diluents with different weight percentage  (5, 10 and  20 wt.% )  of  (n-heptane, toluene, and a mixture of  different ratio toluene / n-Heptane)  at constant temperature. Experimentally the higher viscosity reduction was about from 135.6 to 26.33 cP when the mixture of toluene/heptane (75/25 vol. %) was added. The input parameters for the model were solvent type, wt. % of solvent, RPM and shear rate, the results have been demonstrated that the proposed model has superior performance, where the obtained value of R was greater than 0.99 which confirms a good agreement between the correlation and experimental data, the predicate for reduced viscosity and DVR was with accuracy 98.7%, on the other hand, the μ and DVR% factors were closer to unity for the ANN model.

Heavy Crude Oil Viscosity Reduction and the Impact of Asphaltene Precipitation

2013 ◽  
Vol 27 (12) ◽  
pp. 7267-7276 ◽  
Author(s):  
Osamah A. Alomair ◽  
Abdulwahab S. Almusallam
Keyword(s):  
Crude Oil ◽  
Viscosity Reduction ◽  
Heavy Crude Oil ◽  
Asphaltene Precipitation ◽  
Oil Viscosity ◽  
Heavy Crude ◽  
The Impact
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