Asphaltenes removal enhances the quality of the oil and facilitates the processing.In the present work,a NiO/AlPO-5 nanocomposite using green TMG was synthesized as a particular adsorbent for asphaltenes removal.NiO/A...Asphaltenes removal enhances the quality of the oil and facilitates the processing.In the present work,a NiO/AlPO-5 nanocomposite using green TMG was synthesized as a particular adsorbent for asphaltenes removal.NiO/AlPO-5 was characterized using FTIR,BET,TEM,and XRD techniques.The Response Surface Method was used to optimize three important independent operating parameters,including D/C0[(g)adsorbent/(mg/L)initial](X1),initial pH(X2)and temperature(X3),to remove asphaltenes by the NiO/AlPO-5 nanocomposites in a model oil solution.Applying a CCD,a quadratic mathematical model formula was obtained to calculate asphaltene removal.The results revealed that the model showed valid agreement with the experimental results,with R2=0.94.The optimum values for D/C0,pH as well as temperature would be 0.08[g/(mg/L)],3.39 and 298 K,respectively.It was revealed that the optimal asphaltenes removal was 83.73%at the optimum point.The isothermal models of Langmuir and Freundlich represented the asphaltenes adsorption on the new adsorbent with acceptable accuracy.展开更多
Cyclic steam stimulation(CSS)is widely used for production from heavy oil reservoirs where oil viscosity is manipulated by heat.Many analytical models have been developed to predict the temperature evolution in the re...Cyclic steam stimulation(CSS)is widely used for production from heavy oil reservoirs where oil viscosity is manipulated by heat.Many analytical models have been developed to predict the temperature evolution in the reservoir and estimate the oil recovery.However,they often suffer from a number of assumptions which ultimately reduce their efficiency in providing a realistic prediction.In this study,a numerical solution was proposed for two-dimensional heat conduction in heavy oil reservoirs to obtain the temperature evolution during the soaking period.For a better comparison,an industry widely accepted analytical model,knows as the Boberg and Lantz steam stimulation model,together with its modified version later proposed by Bensten and Donohue were considered to examine temperature changes in a synthetic case study.The results obtained indicated that the analytical solutions overestimate the average temperature of the reservoir by 42%after 300 days of injection while the numerical formulation can provide a close prediction.This numerical approach could be a useful tool to estimate the temperature and oil production from heavy oil reservoirs.展开更多
文摘Asphaltenes removal enhances the quality of the oil and facilitates the processing.In the present work,a NiO/AlPO-5 nanocomposite using green TMG was synthesized as a particular adsorbent for asphaltenes removal.NiO/AlPO-5 was characterized using FTIR,BET,TEM,and XRD techniques.The Response Surface Method was used to optimize three important independent operating parameters,including D/C0[(g)adsorbent/(mg/L)initial](X1),initial pH(X2)and temperature(X3),to remove asphaltenes by the NiO/AlPO-5 nanocomposites in a model oil solution.Applying a CCD,a quadratic mathematical model formula was obtained to calculate asphaltene removal.The results revealed that the model showed valid agreement with the experimental results,with R2=0.94.The optimum values for D/C0,pH as well as temperature would be 0.08[g/(mg/L)],3.39 and 298 K,respectively.It was revealed that the optimal asphaltenes removal was 83.73%at the optimum point.The isothermal models of Langmuir and Freundlich represented the asphaltenes adsorption on the new adsorbent with acceptable accuracy.
文摘Cyclic steam stimulation(CSS)is widely used for production from heavy oil reservoirs where oil viscosity is manipulated by heat.Many analytical models have been developed to predict the temperature evolution in the reservoir and estimate the oil recovery.However,they often suffer from a number of assumptions which ultimately reduce their efficiency in providing a realistic prediction.In this study,a numerical solution was proposed for two-dimensional heat conduction in heavy oil reservoirs to obtain the temperature evolution during the soaking period.For a better comparison,an industry widely accepted analytical model,knows as the Boberg and Lantz steam stimulation model,together with its modified version later proposed by Bensten and Donohue were considered to examine temperature changes in a synthetic case study.The results obtained indicated that the analytical solutions overestimate the average temperature of the reservoir by 42%after 300 days of injection while the numerical formulation can provide a close prediction.This numerical approach could be a useful tool to estimate the temperature and oil production from heavy oil reservoirs.
