1. A measurement clustering method, comprising: obtaining measurements of a downhole environment, each measurement being multi-dimensional and consisting of a plurality of variables in the downhole environment; obtaining prototypes defining expected relationships between the variables for predicting one or more physical properties of the downhole environment; determining errors of the measurements relative to the prototypes; assigning each of the measurements to one of the prototypes for which the determined error is least; fitting each of the prototypes to its cluster of assigned measurements; and predicting the one or more physical properties of the downhole environment based on the characteristics of the cluster-fitted prototypes relating the variables in the downhole environment, wherein determining the errors comprises determining that at least one of the clusters of the measurements violates an error constraint with respect to its original prototype and reassigning the measurements of the at least one cluster to newly initiated prototypes.