The Role of Geomechanical Observation in Continuous Updating of Thermal Recovery Simulations Using the Ensemble Kalman Filter

摘要

In situ thermal methods such as steam-assisted gravity drainage (SAGD) and cyclic steam stimulation (CSS) are widelyemployed in oil sand reservoirs. The physics of such thermal processes is generally well understood, and it has been shownthat rock properties are highly influenced by the geomechanical behaviour 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 for application to closed-loop reservoir optimization is not usuallypracticed. With increased implementation of highly instrumented wells and communication technologies providing real-timemonitoring data from different sources, combining available data into reservoir-geomechanical simulations would improveupdating numerical models and prediction process. This research explores effective uses of geomechanical observation datafor history matching and types of geomechanical observation sources adequate for thermal recovery. The ensemble Kalmanfilter (EnKF), combined with an iterative geomechanical coupled simulator, has been chosen as the data assimilationalgorithm to update the model continuously based on geomechanical observations. The results show that consideringgeomechanical modelling and observation improves the history matching process when geomechanics is an issue.