Estimation of fracture distribution in a CO2-EOR system through Ensemble Kalman filter

CO2-EOR can serve as a method to jointly enhance oil production and reduce CO2 emissions into the atmosphere. In a fractured reservoir, it is crucial to characterize the spatial and geometrical properties of fractures when designing a CO2-enhanced oil recovery (EOR) strategy, since the existence of fractures may lead to the early CO2 breakthrough and can significantly impact the sweep efficiency. Compared with the traditional continuum model, discrete fracture model (DFM) can explicitly maintain the full geometrical properties of the individual fractures and accurately simulate the performance of a CO2-EOR system. However, the spatial distribution of fractures should be reasonably understood to ensure the effectiveness of CO2-EOR project. In this work, an approach combining ensemble Kalman filter (EnKF) with DFM is developed to estimate the fracture distribution by matching the history of production data. The spatial distribution of each fracture is characterized by the coordinates of endpoints, length, and orientation. These geometrical properties are treated as the adjustable model parameters during the history matching process. The difficulty to estimate such parameters lies in the non-linear relationship between parameters and the observed production data. The EnKF method has been found to an effective method to resolve this issue. Here the available production data is assimilated sequentially to update the geometrical parameters of each fracture via the EnKF method, which has the capability to quantify the production dynamics under estimation uncertainty. (c) 2017 Society of Chemical Industry and John Wiley & Sons, Ltd.