The Role of Geomechanical Observation in Continuous Updating of Thermal-Recovery Simulations With the Ensemble Kalman Filter
- Ali Azad (Shell Canada) | Richard Chalaturnyk (University of Alberta)
- Document ID
- Society of Petroleum Engineers
- SPE Journal
- Publication Date
- May 2013
- Document Type
- Journal Paper
- 1,043 - 1,056
- 2013. Society of Petroleum Engineers
- 5.3.9 Steam Assisted Gravity Drainage, 5.8.5 Oil Sand, Oil Shale, Bitumen, 5.3.4 Integration of geomechanics in models, 5.5 Reservoir Simulation
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- 251 since 2007
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In-situ thermal methods such as steam-assisted gravity drainage (SAGD) and cyclic steam stimulation (CSS) are widely used in oil-sand reservoirs. The physics of such thermal processes is generally well-understood, and it has been shown that rock properties are highly influenced by the geomechanical behavior of the reservoir during these recovery processes. Geomechanics improves the process dynamically, and its response can depict the progress of production within a reservoir. However, the potential of geomechanical monitoring is not usually practiced. With increased implementation of highly instrumented wells and communication technologies providing real-time monitoring data from different sources, combining available data into reservoir geomechanical simulations can improve updating numerical models and the prediction process.This research explores effective uses of geomechanical observation data for history matching and types of geomechanical observation sources adequate for thermal recovery. The ensemble Kalman filter (EnKF), combined with an iterative geomechanical coupled simulator, has been chosen as the data-assimilation algorithm to update the model continuously on the basis of geomechanical observations and production data. The results show that considering geomechanical modeling and observation improves history matching when geomechanical behavior plays a role in the process.
|File Size||2 MB||Number of Pages||14|
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