A Robust Empirical Correlation for Predicting Strontium Sulfate Scaling in Oilfield Brines

Hosni Ezuber; Sabri Mrayed; Yahya Dalal; Layal Abuaziz; Wejdan Fardan

doi:10.66411/jer.v41i2.442

Authors

Hosni Ezuber College of Engineering, University of Bahrain, Bahrain Author
Sabri Mrayed College of Engineering, University of Bahrain, Bahrain Author
Yahya Dalal College of Engineering, University of Bahrain, Bahrain Author
Layal Abuaziz College of Engineering, University of Bahrain, Bahrain Author
Wejdan Fardan College of Engineering, University of Bahrain, Bahrain Author

DOI:

https://doi.org/10.66411/jer.v41i2.442

Keywords:

Scale, Strontium Sulfate, Prediction Method, Saturation Ratio, Gauss–Newton Regression Analysis

Abstract

A simple and reliable method for predicting strontium sulfate (SrSO4) scaling as a function of multiple variables; including temperature (25 to 300◦C), pressure (1 to 500 bar), and sodium chloride concentration up to 4 M, has been developed. Instead of relying on complex ion-interaction theories, an empirical polynomial correlation was utilized, which was fitted to experimental solubility data. By benchmarking this method against both existing literature and actual oilfield observations, it has been demonstrated that the developed simplified polynomial correlation can achieve accuracy comparable to complex thermodynamic models, thereby providing an accessible and robust predictive tool for oilfield environments.

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References

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