Applying Fast and Quantitative Screening Methods to Understand the Reservoir Dynamics in Complex Carbonate Reservoirs

Abstract

This study explores how very fast screening methods, so called “flow diagnostics”, can help us to explore how a realistic range of geological uncertainties and model scenarios impact flow behaviours in a complex carbonate reservoir. Flow diagnostics are normally performed using streamline simulations but here we use an implementation in the Matlab Reservoir Simulation Toolbox (MRST) that allows us to compute approximate dynamic properties (e.g. time-of-flights and dynamic Lorenz coefficients) directly on the grid of the reservoir model. We show that the flow diagnostic simulations take negligible time (i.e. on the order of seconds). Hence a large number of model scenarios and realisations can be explored, which allows us to investigate for more models how geology and well placements impact reservoir behaviors, and subsequently rank and cluster the models based on their dynamic behaviors. This in turn will enable us to select appropriate models for full-physics simulations that capture the full uncertainty inherent to the reservoir description and helps us to develop better reservoir management approaches.