Evaluating production behaviour of CBM wells from Raniganj Coalfield through reservoir characterization under constrained field data conditions

There remains a good level of uncertainty in peak gas rate and the time to reach the peak for coalbed methane (CBM) wells owing to reservoir heterogeneity. The novelty of the present study lies in predicting the production behavior of wells in the emerging CBM block of Raniganj through extensive reservoir characterization coupled with reservoir simulation and validation. Ten regional (R-I to R-X) and two local seams intercepted in the six exploratory boreholes drilled in Raniganj Coalfield were investigated. The reservoir characterization approach was used for uncertainty analysis of the key parameters viz. isotherms, gas content, permeability and porosity, and their impact on the production behavior of the CBM wells. Low, mid and high cases of the parameters were determined through regression analysis. Isotherm and gas content data were experimentally determined while in situ permeability data were obtained from the pressure transient analysis of injection/fall-off test. Reiss model was used for porosity-permeability transformation and Corey's model was used to define the range of relative permeability. The experimental values of Langmuir volume varies between 17.4 and 29.8 cc/gm (daf); Langmuir pressure 2451-7827 kPa; gas content 2.07-13.03 cc/gm (daf); and fracture permeability 0.79-7.12 mD. The model was set up in CMG-GEM simulator to represent a single well producing under commingled completion strategy for all the 12 seams being perforated. Production profiles of both gas and water show a wide range of variation up to 56,201 m3/day and up to 129.84 m3/day, respectively. Data analysis reveals that Raniganj coals are having a wide range of saturation distribution (between 27% and 100%) with a huge upside potential going towards 100% saturation case. Gas content and permeability are found to be the two key factors controlling the CBM production in Raniganj Coalfield. The model results were validated with actual well performance.