1. A method for predicting sand-grain composition and sand texture comprising: selecting a first set of system variables, said first set associated with sand-grain composition and sand texture; selecting a second set of system variables, said second set being directly or indirectly causally related to said first set of variables; obtaining or estimating data for each variable in the second set; forming a network with nodes comprising both sets of variables, having directional links connecting interdependent nodes, said directional links honoring known causality relationships; and using a Bayesian Network algorithm with said data to solve the network for said first set of variables and their associated uncertainties.