oa Assimilation of Time-lapse CSEM Data for Fluid Flow Monitoring

The feasibility of marine CSEM for reservoir monitoring is supported by several model studies suggesting that there may be a detectable time-lapse signal in CSEM data. However, the detectability of these signals for field cases will depend on careful acquisition design and reliable inversion methodology. To mitigate the inherent non-uniqueness associated with these large scale geophysical problems, the integration of additional data types is required. Constraining the solution space by including different data types in the model calibration process can help reducing the model uncertainty and lower production related risk. In this talk, the use of statistical ensemble based methods (EnKF) for the integration of CSEM data and other geophysical data types (i.e. gravimetric data) will be discussed. By the utilization of a statistical inversion method, an assessment of the uncertainty in the estimated flow patterns is obtained as part of the solution.