1. A method for estimating variability of future recovery of a natural resource, the method comprising: receiving, from a database, a plurality of model realizations of the natural resource, the plurality of model realizations representing uncertainty in determining model properties of the natural resource; determining, for each of the plurality of model realizations, respective principal flow pattern coefficients representing a reduced model space; identifying similar principal flow patterns amongst the received plurality of model realizations using the coefficients representing the reduced model space; clustering the received plurality of model realizations according to the identified similar principal flow patterns in the reduced model space, each cluster having a similar principal flow pattern and representing a prior input to a history matching process; determining a set of history matched models by applying the history matching process on a set of selected model prior realizations, wherein the selected model prior realizations are a subset of representative realizations selected from the clustered realizations; and determining variability in natural resource production by utilizing the set of history matched models as inputs to a prediction simulation tool, wherein the prediction simulation tool is configured to run simulations based on the set of history matched models to estimate the future production scenarios of the natural resource; wherein a processor connected to a memory device is configured to perform: the receiving the plurality of model realizations, the determining the respective principal flow pattern coefficients, the identifying similar principal flow patterns, the clustering the received plurality of model realizations, the determining the set of history matched models, the determining the variability, and running the prediction simulation tool.