Simulation study demonstrates accurate prediction of sour gas desulfurization using kinetic modeling in an industrial Thiopaq plant, highlighting a scalable framework for process optimization.
Natural gas remains a primary global energy source, but toxic H2S requires using efficient, sustainable recovery technologies. Thiopaq process offers a sustainable biological alternative to physicochemical methods. However, industrial-scale simulation models that accurately capture the biological complexity remain scarce. This study presents a detailed simulation model of an industrial Thiopaq plant using Aspen Plus v14, employing the ENRTL-RK method to model the carbonate-bicarbonate buffer system. Unlike previous models with fixed conversions, this work integrates kinetic rate equations for sulfide biological oxidation to sulfur and sulfate. Validation against industrial design data showed strong agreement with the process key performance indicators: H2S in treated gas reduced to 22.9 ppm, the liquid stream pH deviated by less than 4%, and the calculated sulfur selectivity was 72%. Systemic loop discrepancies in CO2 absorption (11.4% error) were identified and attributed to the equilibrium-based model limitations. Furthermore, model sensitivity analysis demonstrated the model predictive capability. Increasing the solution circulation rate by 15% reduced the H2S concentration by 42%. The developed model provides a framework for further validation with plant data, industrial troubleshooting, process optimization, and evaluation of the Thiopaq process techno-economic and environmental performance.
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Aboelwafa et al. (2026) studied this question.
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