Abstract
The aqueous solubility of BaSO4 and SrSO4 in salt-containing solutions plays a crucial role in process industries and oilfield operations. Small variations in thermodynamic conditions result in precipitation and co-precipitation of these salts, mainly owing to their limited solubility in aqueous solutions. Understanding the environmental chemistry of BaSO4 and SrSO4 requires accurate knowledge of their solubility and thermodynamic behaviors. In this study, a general solubility prediction model based on a least square support vector machine and differential evolution algorithm was developed that is able to handle solubility predictions for BaSO4 in single Ksalt solutions containing NaCl, CaCl2, MgCl2, KCl, KBr, Na2SO4, and Na2B4O7, and for SrSO4 solubility, it can handle predictions for single, binary, and ternary salt solutions containing NaCl, CaCl2, and MgCl2 over a wide range of temperatures and pressures. Model predictions agree excellently with experimental measurements, yielding an overall correlation coefficient (R-2) of 0.9911 and an Average Absolute Error of 624%. A comparison of the general solubility prediction model with the Pitzer ion-interaction model revealed that both the models perform well in single salt solutions, while the Pitzer model fails to produce accurate solubility predictions when the aqueous system is extended to binary and ternary electrolyte mixtures. (C) 2019 Elsevier B.V. All rights reserved.