Evaluation of Relative Permeability in Coalbed Methane Reservoirs Based on Production Data: A Case Study in Qinshui Basin, China
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Relative permeability is an important feature to characterize two-phase flow in coalbed methane (CBM) reservoirs, as it can be widely used in laboratory, simulation studies and field production. The main methods to derive relative permeability curves include history match, laboratory core test and production data. In China, most of the acquired CBM well data are the field production data, so this study intended to evaluate of CBM relative permeability based on production data. The Zhengzhuang area in Qinshui Basin was chosen as a case study. Since flow equations can only be used in radial flow, flow regime was first identified for radial flow. Then, the Palmer et al. (in: International coalbed methane symposium, Tuscaloosa, 2007) absolute permeability model was used to characterize absolute permeability, so that the effects of relative permeability and absolute permeability changes can be isolated. Material balance equation (MBE) was also applied to derive water saturation. Therefore, the relative permeability curve can be derived by combination of flow equations, Palmer et al. (2007) absolute permeability model and MBE based on real field production data. In addition, relative permeability curves of producing wells from different zones of the Zhengzhuang area were compared and the possible reason for the difference was also discussed. The work presented here can provide a useful and practical instruction for the derivation of relative permeability of China’s CBM wells.
KeywordsRelative permeability Coalbed methane Multiphase flow Production data
We would like to thank all anonymous reviewers and editor for their work. This research was funded by the National Special Coal Resources Comprehensive Evaluation and Information System Construction (Grant No. DD20160189), Energy Security Comprehensive Research and Dynamic Tracking Evaluation of Geological Mineral Investigation and Evaluation Project (Grant No. DD20160084).
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