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Prediction Model of Sulfur Deposition in the High Sulfur Gas Well Bore

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Fuzzy Information and Engineering Volume 2

Part of the book series: Advances in Intelligent and Soft Computing ((AINSC,volume 62))

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Abstract

Sulfur deposition in the well bore not only jams the equipment and pipeline, but also gets heavy corrosion of down-hole’s pipe string and rig on ground. The accurate prediction of sulfur deposition in the well bore is very important. Because sulfur solubility is a function of temperature and pressure in the high sulfur gas well bore, this paper addressed solubility mode of sulfur to build up sulfur deposition’s prediction model after we had analyzed the farces on grain under these different flows. The calculation’s results show that the model has practical value. All of the analytical methods of sulfur deposition in the current, including solubility characteristic analytical map, predict method of statistical model etc., can not only get the result of quantitative analysis on the deposit’s amount but also accurate position of sulfur deposition. An important reason about those is that kinetics characteristics of sulfur deposition are not considered, in another words, all of these methods are not considered the gas velocity’s and its gradient’s influence [1]. In order to resolve above issue and achieve performance prediction of sulfur deposition, basing on Sulfur solubility being a function of temperature and pressure in the high sulfur gas well bore, grain mechanics analysis under difference flow pattern was introduced to build up sulfur deposition’s prediction model in this article, assuming transient stable flow in the wellbore and non-stable heat transfer process. Applying this model to prediction gas well production (F-15 well, which is in the eastern Sichuan), the result was very similar to actual situation and showed that this method can be used to predict performance deposition of high sulfur gas well.

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References

  1. Editorial Board of Oil & Gas Field Corrosion And Protection Technical Manual. Petroleum Industry Press, Beijing (1999)

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© 2009 Springer-Verlag Berlin Heidelberg

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Xu, Cb., Wang, J., Zeng, Sp. (2009). Prediction Model of Sulfur Deposition in the High Sulfur Gas Well Bore. In: Cao, B., Li, TF., Zhang, CY. (eds) Fuzzy Information and Engineering Volume 2. Advances in Intelligent and Soft Computing, vol 62. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03664-4_48

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  • DOI: https://doi.org/10.1007/978-3-642-03664-4_48

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-03663-7

  • Online ISBN: 978-3-642-03664-4

  • eBook Packages: EngineeringEngineering (R0)

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