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Development and Application of a Production Data Analysis Model for a Shale Gas Production Well

Dongkwon Han, Sunil Kwon*

Department of Energy and Mineral Resources, Dong-A University, Busan, 49315, Korea

* Corresponding Author: Sunil Kwon. Email: email

Fluid Dynamics & Materials Processing 2020, 16(3), 411-424. https://doi.org/10.32604/fdmp.2020.08388

Abstract

This paper presents the development and application of a production data analysis software that can analyze and forecast the production performance and reservoir properties of shale gas wells. The theories used in the study were based on the analytical and empirical approaches. Its reliability has been con- firmed through comparisons with a commercial software. Using transient data relating to multi-stage hydraulic fractured horizontal wells, it was confirmed that the accuracy of the modified hyperbolic method showed an error of approximately 4% compared to the actual estimated ultimate recovery (EUR). On the basis of the developed model, reliable productivity forecasts have been obtained by analyzing field production data relating to wells in Canada. The EUR was computed as 9.6 Bcf using the modified hyperbolic method. Employing the Pow Law Exponential method, the EUR would be 9.4 Bcf. The models developed in this study will allow in the future integration of new analytical and empirical theories in a relatively readily than commercial models.

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APA Style
Han, D., Kwon, S. (2020). Development and application of a production data analysis model for a shale gas production well. Fluid Dynamics & Materials Processing, 16(3), 411-424. https://doi.org/10.32604/fdmp.2020.08388
Vancouver Style
Han D, Kwon S. Development and application of a production data analysis model for a shale gas production well. Fluid Dyn Mater Proc. 2020;16(3):411-424 https://doi.org/10.32604/fdmp.2020.08388
IEEE Style
D. Han and S. Kwon, “Development and Application of a Production Data Analysis Model for a Shale Gas Production Well,” Fluid Dyn. Mater. Proc., vol. 16, no. 3, pp. 411-424, 2020. https://doi.org/10.32604/fdmp.2020.08388



cc Copyright © 2020 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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