The application of very large correlation operators to vectors is an persistent challenge for variational data assimilation. It must be accurate, fast and scalable. This article proposes a new generic method that works for any model grid, relying on adaptive subgrids to achieve this goal, even with advanced correlation functions. It describes the motivations and advantages of this method and its limitations depending on a few key parameters of the problem.