Abstract
The efficient and rational development of tight gas reservoirs, most of which are deposit of multiple layers, is becoming a new global focus. The major tight gas reservoirs in China have multiple production layers. Gas wells are completed with multiple fracture treatments, and are commingled production. It is very difficult to effectively evaluate the single-layer production contribution and the use of each layer’s reserves. This paper presents an approach to solve the problem, which is basically based on the application of Pearson correlation analysis, catastrophe theory, and linear interpolation to calculate the single-layer production allocation rates. The method can quickly evaluate the stratified production of a large number of gas wells at different times through a computer program. The error of method validation, comparing the method prediction value with the production test data, is less than 10%. In field application, after the gas flows the discharge boundary, the production of the main layer will decrease due to the decrease in gas production of the multi-layer gas well, and other non-main layers may rise or have little change. In another case, the non-main layer can produce more natural gas for the gas well increases production. The method will also provide guidance for optimizing the perforation section of a gas well. Additionally, based on the production of a single gas well, the cumulative gas production of each layer can be calculated to evaluate the dynamic reserves of each layer and analyze the reserves utilization of each single layer. This work will finally provide guidance for gas well encryption to improve the multi-layer tight gas reservoir recovery.
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Zhang, Hb., Liu, Zj., Liu, Jj., Liu, Q., Jia, C. (2021). Production Allocation Analysis of Commingle Production Wells in Multi-layer Tight Gas Reservoirs. In: Lin, J. (eds) Proceedings of the International Field Exploration and Development Conference 2020. IFEDC 2020. Springer Series in Geomechanics and Geoengineering. Springer, Singapore. https://doi.org/10.1007/978-981-16-0761-5_64
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DOI: https://doi.org/10.1007/978-981-16-0761-5_64
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