Predicting Gas Well Performance with Decline Curve Analysis: A Case Study on Semutang Gas Field
DOI:
https://doi.org/10.38032/scse.2025.3.14Keywords:
Decline-Curve Analysis, Production forecasting, Semutang gas fieldAbstract
Decline-curve analysis (DCA) is a widely utilized method for production forecasting and estimating remaining reserves in gas reservoir. Based on the assumptions that past production trend can be mathematically characterized and used to predict future performance. It relies on historical production data and assumes that production methods remain unchanged throughout the analysis. This method is particularly valuable due to its accuracy in forecasting and its broad acceptance within the industry. Wells in the same geographical area and producing from similar geological formations often exhibit similar decline curve parameters. This study applies DCA to forecast the future production performance and estimate the ultimate recovery for the Semutang gas field's well 5 in Bangladesh. Using historical production data, decline curves were generated based on exponential, hyperbolic, and harmonic model equations. The cumulative production estimations were 11,139.34 MMSCF for the exponential model, 11,620.26 MMSCF for the hyperbolic model, and 14,021.92 MMSCF for the harmonic model. In terms of the well's productive life, the estimates were 335.13 days, 1,152 days, and 22,611 days, respectively. Among these models, the hyperbolic decline provided the most realistic forecast, closely aligning with observed production trend. The study highlights the importance of selecting an appropriate decline model for accurate production forecasting and reserve estimation, which is essential for effective reservoir management and resource optimization.
Downloads
Downloads
Downloads
References
[1] T. Marhaendrajana and T. A. Blasingame, “Decline curve analysis using type curves — evaluation of well performance behavior in a multiwell reservoir system,” SPE Annual Technical Conference and Exhibition, Sep. 2001.
[2] H. Pratikno, J. A. Rushing, and T. A. Blasingame, “Decline curve analysis using type curves — fractured wells,” SPE Annual Technical Conference and Exhibition, Oct. 2003.
[3] D. Ilk, J. A. Rushing, A. D. Perego, and T. A. Blasingame, “Exponential vs. Hyperbolic Decline in Tight Gas Sands — Understanding the Origin and Implications for Reserve Estimates Using Arps’ Decline Curves,” All Days, Sep. 2008.
[4] J. J. Arps, Analysis of decline curves, vol. 160. *Transactions of the AIME*, 1945.
[5] D. Blasingame, Decline curve analysis for unconventional reservoirs. SPE Annual Technical Conference and Exhibition, 2000.
[6] R. a. Wiggins and M. R. Baber, Application of Arp’s equations for gas well performance prediction in the Barnett Shale. SPE Annual Technical Conference and Exhibition, 2003.
[7] Yilmaz, Evaluation of Arp’s decline models in mature oil fields. SPE Annual Technical Conference and Exhibition, 2005.
[8] S. H. Hosseini and M. Sadeghi, Comparative study of Arp’s decline models and alternative forecasting methods in carbonate reservoirs. SPE Annual Technical Conference and Exhibition, 2010.
[9] Y. Zhang and C. Liu, Using Arp’s equations for decline curve analysis in shale gas reservoirs, vol. 5. Journal of Natural Gas Science and Engineering, 2012.
[10] F. Nikkhah and R. Nikkhah, Integrating Arp’s equations with machine learning for reservoir forecasting, vol. 159. Journal of Petroleum Science and Engineering, 2017.
Published
Conference Proceedings Volume
Section
License
Copyright (c) 2025 Md. Shakil Rahaman, Ahmed Sakib, Ataharuse Samad, Md. Ashraful Islam (Author)

This work is licensed under a Creative Commons Attribution 4.0 International License.
All the articles published by this journal are licensed under a Creative Commons Attribution 4.0 International License
