Abstract History matching is an essential tool for providing reliable and accurate reservoir models that are useful for prediction and optimization and are routinely used in the petroleum industry. By updating the model based on available dynamic data, the modeling error and uncertainty are reduced systematically. Traditional history matching updates static parameters like porosity and permeability. This work focuses on relative permeability and shows how the relative permeability can be included in the history matching workflow systematically and efficiently, to further improve the predictive capabilities of the updated reservoir model. Our approach’s novelty is associating unique relative permeability curves, based on the LET formulation, to flow regions associated with each well. These flow regions are computed by solving tracer transport equations on the flow field and thus represent the streamlines connecting the injectors and the producers. The data used for the history matching is the production data in the wells. Therefore, flow regions are a natural choice for localizing the update to avoid over-fitting and ensemble collapse. The workflow is demonstrated on the Drogon reservoir model and shows an excellent match of the data both in the training and validation periods. The Drogon model is a synthetic reservoir model made openly available by Equinor for realistic testing of history matching and optimization workflows.
Lomeland et al. (Thu,) studied this question.