The oil and water separation from surfactant produced water by using a flotation column
The objective of this paper is to study the effect of amphoteric surfactant at different operating conditions concerning the oil�water separation from Dulang Oil field by using a laboratory-scale flotation column. A model has been developed to optimize the flotation process by using response surfa...
محفوظ في:
| المؤلفون الرئيسيون: | , |
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| التنسيق: | مقال |
| منشور في: |
Springer
2020
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| الوصول للمادة أونلاين: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85077584911&doi=10.1007%2f978-981-13-7127-1_58&partnerID=40&md5=57c250b98b48b73d223af4921543985a http://eprints.utp.edu.my/32453/ |
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| الملخص: | The objective of this paper is to study the effect of amphoteric surfactant at different operating conditions concerning the oilâ��water separation from Dulang Oil field by using a laboratory-scale flotation column. A model has been developed to optimize the flotation process by using response surface method (RSM). The produced water containing surfactant was created by mixing the Dulang crude oil with the initial concentration of 1000 ppm, brines at 14000 ppm concentration, and MFOMAX amphoteric surfactant ranging from 0 to 500 ppm. A total of 32 experiments were conducted, and the effect of gas flowrate, MFOMAX concentration, and duration of flotation on the efficiency of oil removal from the flotation units has been analyzed. The experimental data results were then statistically analyzed, and the experiments were conducted for verification. The experimental results were found in fair agreement with the modelâ��s predicted value, suggesting that the model could define the relationship between parameters. With the presence of MFOMAX, the optimal combination of parameters was at 4 L/min gas flowrate at the duration of 9 min with the efficiency of 87.3. Confirmatory experiments were conducted at the optimum parameters to verify the model. The experimental value of 82.8 (STD 1.60) was obtained which indicated a good agreement with the predicted results. © Springer Nature Singapore Pte Ltd 2020. |
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