Investigating the effect of TiO2-based nanofluids in the stability of crude oil flow: parametric analysis and Gaussian process regression modeling

Abstract

Study has shown that the precipitation of asphaltenes could be the most detrimental mechanism that significantly influences well productivity during crude oil processing. The flow of the crude oil could seriously be affected if the effect of the asphaltenes is not inhibited. This study aims to investigate the effect of TiO2-based nanofluid in stabilizing crude oil flow. The effect of the ratio of TiO2/SiO2 nanocomposite in the organic nanofluid, the salinity of the nanofluid, and pH on the amount of organic solvent (n-heptane) added to stabilize the crude oil flow was investigated using Gaussian Process Progression (GPR) with five kernel functions [exponential square kernel (model 1), rotational quadratic (model 2), Matern 5/2 (model 3), exponential (model 4), and non-isotopic rotational quadratic (model 5)]. The GPR using the various kernel function had good modeling of the relationship between the ratio of TiO2/SiO2 nanocomposite in the organic nanofluid, the salinity of the nanofluid, the pH, and the amount of organic solvent (n-heptane) added to stabilize the crude oil flow. This is evidence from the R2 of 0.820, 0.999, 0.999, 0.999, 0.999 for model 1, model 2, model 3, model 4, and model 5, respectively. Each of the models had low prediction errors as indicated by the MSE, RMSE, and MAE. Based on the sensitivity analysis, the ratio of TiO2/SiO2 nanocomposite in the organic nanofluid had the most significant influence on the amount of n-heptane added to stabilize the crude oil.