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Parametric Investigation of Wettability Alteration of Reservoir Rocks by Asphaltene Deposition: Experimental and Modeling Approaches

Journal: Petroleum & Petrochemical Engineering Journal (Vol.4, No. 1)

Publication Date:

Authors : ; ;

Page : 1-8

Keywords : Wettability of sandstone rocks; Contact angle; Asphaltene content; Salinity; ANFIS-PSO algorithm; Predicting model;

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Abstract

Rock wettability plays an important role in water flooding process as it controls fluid flow, oil recovery and distribution of residual oil in any oil reservoir. In this context, polar oil components such as asphaltene contents may adsorb onto the pore mineral surfaces and alter wettability of the reservoir rock. Due to this importance, this study aims to investigate the effects of different parameters such as concentration of asphaltene, salinity, temperature and time on the rock wettability alteration process. For this purpose, dynamic contact angle measurement was performed. The results showed that the increment of asphaltene concentration in the oleic phase changes the wettability of water-wet sandstone rock to oil-wet condition; the increase in the concentration of asphaltene fraction from 0.1 to 5.0 g/lit increased the contact angle from 0 to 97 degrees. In addition, the increase in the brine salinity from 500 to 8000 ppm increased the ability of asphaltene to adsorb on the rock surface and consequently, increased oil wetness; the equivalent contact angle changed from 0 to 113 degree for 5 g/lit asphaltene content after 192 hours. Moreover, the results illustrated that a rise in temperature from 40 to 70o C accelerates adsorption of asphaltene, but it has not significant effect on the final contact angle. Furthermore, the Adaptive Neuro-Fuzzy Inference System (ANFIS) is incorporated into the Particle Swarm Optimization (PSO) algorithm to correlate contact angle with the aforementioned parameters. To this end, the obtained experimental data are used to train and test the algorithm. The outputs of ANFIS-PSO algorithm are compared with the measured contact angles in both graphical and statistical manners. The training and testing determination coefficients (R2 ) have been obtained as 0.99091 and 0.98761, respectively. The analysis indicates that the predictive model can be used with a high degree of confidence to investigate the effect of different parameters on wettability alteration.

Last modified: 2021-10-29 17:25:25