Title
Rigorous modeling of gypsum solubility in Na---Ca---Mg---Fe---Al---H---Cl---H2O system at elevated temperatures
Abstract
Precipitation and scaling of calcium sulfate have been known as major problems facing process industries and oilfield operations. Most scale prediction models are based on aqueous thermodynamics and solubility behavior of salts in aqueous electrolyte solutions. There is yet a huge interest in developing reliable, simple, and accurate solubility prediction models. In this study, a comprehensive model based on least-squares support vector machine (LS-SVM) is presented, which is mainly devoted to calcium sulfate dihydrate (or gypsum) solubility in aqueous solutions of mixed electrolytes covering wide temperature ranges. In this respect, an aggregate of 880 experimental data were gathered from the open literature in order to construct and evaluate the reliability of presented model. Solubility values predicted by LS-SVM model are in well accordance with the observed values yielding a squared correlation coefficient (R 2) of 0.994. Sensitivity of the model for some important parameters is also checked to ascertain whether the learning process has succeeded. At the end, outlier diagnosis was performed using the method of leverage value statistics to find and eliminate the falsely recorded measurements from assembled dataset. Results obtained from this study indicate that LS-SVM model can successfully be applied in predicting accurate solubility of calcium sulfate dihydrate in Na---Ca---Mg---Fe---Al---H---Cl---H2O system over temperatures ranging from 283.15 to 371.15 K.
Year
DOI
Venue
2014
10.1007/s00521-014-1587-z
Neural Computing and Applications
Keywords
DocType
Volume
aqueous solutions,solubility,least-squares support vector machine,calcium sulfate dihydrate,gypsum,outlier diagnosis
Journal
25
Issue
ISSN
Citations 
3-4
1433-3058
0
PageRank 
References 
Authors
0.34
10
6