Improved Understanding of Reservoir Fluid Dynamics in the North Sea Snorre Field by Combining Tracers, 4D Seismic, and Production Data

Summary To obtain improved oil recovery (IOR), it is crucial to have a best-possible description of the reservoir and the reservoir dynamics. In addition to production data, information can be obtained from 4D seismic and from tracer monitoring. Interwell tracer testing (IWTT) has been established as a proven and efficient technology to obtain information on well-to-well communication, heterogeneities, and fluid dynamics. During such tests, chemical or radioactive tracers are used to label water or gas from specific wells. The tracers then are used to trace the fluids as they move through the reservoir together with the injection phase. At first tracer breakthrough, IWTT yields immediate and unambiguous information on injector/producer communication. Nevertheless, IWTT is still underused in the petroleum industry, and data may not be used to their full capacity--most tracer data are used in a qualitative manner (Du and Guan 2005). To improve this situation, we combine tracer-data evaluation, 4D seismic, and available production data in an integrated process. The integration is demonstrated using data from the Snorre field in the North Sea. In addition to production data, extensive tracer data (dating back to 1993) and results from three seismic surveys acquired in 1983, 1997, and 2001 were considered. Briefly this study shows thatSeismic and tracer data applied in combination can reduce the uncertainties in interpretations of the drainage patterns.Waterfronts interpreted independently by tracer response and seismic dimming compare well.Seismic brightening interpreted as gas accumulation is supported by the gas-tracer responses. Introduction The Snorre field is located in the Tampen Spur area on the Norwegian continental shelf and is a system of rotated fault blocks with beds dipping 4 to 10° toward the northwest. The reservoir sections are truncated by the Base Cretaceous unconformity. The reservoir sections consist of fluvial deposits of the Statfjord and Lunde formations. The reservoir units contain thin sand layers with alternating shale in a complex fault pattern. A challenge regarding optimization of the reservoir drainage, as well as oil production, is to understand how the different sand layers communicate and to what degree the faults act as barriers or not. The present work concentrates on the integration of 4D-seismic and tracer methods to obtain information on fluid flow in the Upper Statfjord (US) and Lower Statfjord (LS) formations in the Central Fault Block (CFB). The outline of this fault block is indicated in Fig. 1. The net/gross ratio is higher and the reservoir quality is generally better in the US than the LS formation. The CFB is produced by water-alternating-gas (WAG) injection as the drive mechanism, where the injectors are placed downdip and the producers updip. The average reservoir pressure in the CFB is 300 bar, and the reservoir temperature is 90°C. Tracer data are used to understand fluid flow in the reservoir. The data give valuable information about the dynamic behavior and well communication, but in some cases the interpretation may be complicated by reinjection of produced gas and water. Tracer studies in the Snorre field have been presented previously in several papers (Dugstad et al. 1999; Ali et al. 2000; Aurdal et al. 2001). To use the data fully, however, integration with other types of reservoir data is important. The main objectives of the seismic monitoring of Snorre are to contribute to increased oil recovery and to optimize placement of new wells. 4D analysis, together with tracers, should potentially increase the multidisciplinary understanding of the drainage pattern in the reservoirs. The results should, in addition to all the reservoir and production data, be used actively in target-remaining-oil processes and in well planning. In addition, the 4D data can give input to update the geological model and simulation model (history matching) and to identify possible well interventions. There is also a potential to include the data in workflows to identify lithology changes.