Decline curve analysis (DCA) has been a popular technique to forecast production and estimate reserves using production data for about seven decades. The reliability of forecasts and reserves estimates obtained through DCA ultimately depends on the quality of the data collected and on the experience and judgment of the analyst. It is important to know what assumptions are being made during DCA analysis and under which conditions the application is valid. Originally DCA have been applied to conventional oil reservoirs. Later on, mathematical manipulations of rate versus time and cumulative versus rate decline equations defined by Arps (1) as well as combinations with other analysis techniques have extended the application of DCA to conventional and unconventional gas reservoirs.
The objective of this work is to investigate the applicability of DCA techniques for reserve estimation and production forecasting of Coal Seam Gas (CSG) wells using rate-cum and rate-time technique, and provide general guidelines and limitations for its use.
This paper compares production forecasts from reservoir simulation and DCA. It also presents guidelines for selection of DCA candidates based on field/well maturity and shows the application of DCA in well and reservoir management, i.e. statistical results from Arps DCA analysis can be used to identify production enhancement potential and to generate typical distributions of EUR and decline parameters for specific fields.
The results indicate that the ultimate recovery of CSG wells is dependent on such factors as gas content, seam thickness, well type, depth and well inseam length. Correlations developed to estimate ultimate recovery ranges can be used to estimate a well's EUR without the need for intensive dynamic reservoir simulation modeling and would enables efficient well-by-well analysis for development scenarios where it is not otherwise practical to perform DCA on each individual well.
The results of this paper can be used as a helpful guide to understand the importance of various parameters to CSG wells elsewhere.