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.
A number of coalbed methane (CBM) to liquefied natural gas (LNG) projects are currently advancing in Australia, among which is the Arrow LNG project. To ensure reliable supply to an LNG plant, production availability of the integrated CBM system consisting of a large amount of wells and production facilities needs to be understood, including the behavior of CBM wells after planned and unplanned shutdowns. This paper provides an analysis of post-shutdown recovery behavior of horizontal CBM wells based on a large volume of field data. There is no known published work on shutdown recovery for CBM wells to date, so there are no comparison data.Arrow Energy has produced CBM for domestic consumption since 2004 and currently supplies about 20 per cent of Queensland's gas from fields in the Bowen and Surat basins. A shutdown recovery analysis is conducted on Arrow's Moranbah Gas Project (MGP) in the Bowen Basin. Field data for 6,436 shutdown periods are used, including: gas rates, water rates and bottomhole pressures (BHP). The following effects on recovery times are analyzed: shutdown duration, pre-shutdown water rate, pre-shutdown gas-water ratio, and pre-shutdown producing days.The results indicate that approximately 70% of wells, shutdown for one day, return to 90% of their previous gas rates within one day. Approximately 20% wells recover in a week and the remaining 10% wells come back to 90% of original rates within 2 months. Furthermore, shutdown periods longer than five days have significantly higher recovery times. Wells with a lower water rate and higher gas-water ratio before the shutdown return to their preshutdown gas rate faster than wells with a higher water rate and lower gas-water ratio. Also, late life wells recover faster than wells in early production life.These findings are critical for planning well shutdown and ramp-up strategies (well classifications and priority lists) to manage required gas supply during the operational phase of integrated CBM-LNG projects.
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