A new comprehensive dimensionless inflow performance relationship for gas wells
Journal of Petroleum Exploration and Production Technology, ISSN: 2190-0566, Vol: 12, Issue: 8, Page: 2257-2269
2022
- 5Citations
- 109Usage
- 10Captures
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
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Metrics Details
- Citations5
- Citation Indexes5
- Usage109
- Downloads92
- Abstract Views17
- Captures10
- Readers10
- 10
Article Description
Prediction of gas well deliverability is important for reservoir management. Conventional flow after flow, isochronal or modified isochronal tests are common methods for calculation of well deliverability. Single-point test using Vogel-type dimensionless inflow performance relationships (IPR) was also proposed to overcome the need for multi-point tests. However, analysis of field data showed that existing dimensionless IPR correlations fail to accurately predict well deliverability for some reservoir conditions. In this study, a wide range of reservoir rock and fluid data was used to develop a comprehensive dimensionless IPR correlation for calculation of gas well deliverability from single-point test data. Multi-point well test data from 61 different gas wells of 15 fields were used to compare predicted absolute open flow (AOF) and calculated AOF from multi-point test data. The data used for validation of the proposed dimensionless IPR cover a wide range of actual AOFs (2.1–1411 MMSCF/D). Good agreement between predicted well deliverability from new dimensionless IPR and that from multi-point test was achieved. In addition, superiority of the new dimensionless IPR to previous correlations was confirmed for a wide range of reservoir conditions through error analysis. The average absolute error for new model is 11.6% (standard deviation of 8.5%) while for the other models are 85.9% (standard deviation of 148.1%) and 68.6% (standard deviation of 115.3%) for a wide range of field data.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85123894136&origin=inward; http://dx.doi.org/10.1007/s13202-022-01457-6; https://link.springer.com/10.1007/s13202-022-01457-6; https://ro.ecu.edu.au/ecuworks2022-2026/236; https://ro.ecu.edu.au/cgi/viewcontent.cgi?article=1236&context=ecuworks2022-2026; https://dx.doi.org/10.1007/s13202-022-01457-6; https://link.springer.com/article/10.1007/s13202-022-01457-6
Springer Science and Business Media LLC
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