Geologic Modeling and Ensemble-Based History Matching for Evaluating CO2 Sequestration Potential in Point bar Reservoirs - Dawuda, Ismael; Srinivasan, Sanjay (Frontiers in Energy Research, 2022)
The target reservoirs in many CO2 projects exhibit point bar geology characterized by the presence of shale drapes that act as barriers preventing the leakage of CO2. However, the extent of the flow barriers can also impede the displacement of CO2 in such reservoirs and restrict the storage volume. Therefore, developing a framework for modeling point bars and their associated heterogeneities is crucial. Yet, for the point bar model to be geologically realistic and reliable for evaluating CO2 sequestration potential, it should be calibrated to reflect historical data (e.g., CO2 injection data). This study is therefore in two parts. The first part focusses on the modeling of point bar heterogeneities (i.e., lateral accretions and inclined heterolithic stratifications). To ensure that the heterogeneities are preserved, we implemented a gridding scheme that generates curvilinear grids representative of the point bar curvilinear geometry. We subsequently incorporated a grid transformation scheme to facilitate geostatistical modeling of reservoir property distributions. The second part of this study is a model calibration step, where the point bar model is updated by assimilating CO2 injection data, in an ensemble framework. Ensemble-Kalman Filter was used first to update ensembles of point bar geometries, to select the geometry that yields the closest match to observed data. Within this geometry, indicator-based ensemble data assimilation was used to perform updates to the ensemble of point bar permeability models. The indicator approach overcomes the Gaussian limitation of the traditional ensemble Kalman filter. The workflow was run on the Cranfield, Mississippi CO2 injection dataset. It was observed, after model calibration, that the final updated ensemble of models yields a reasonable match with the historical data. The updated models were run in a forecast mode to predict the long-term CO2 sequestration potential of the Cranfield point bar reservoir. Results demonstrate that 1) preserving the heterogeneities in the point bar modeling process, and 2) constraining the point bar model to historical data (e.g., CO2 injection data) are essential for accurately evaluating the CO2 sequestration potential in point bar reservoirs.