PROBABILISTIC MODELS FOR ESTIMATING LITHOLOGY

The estimation of lithology within a volume of rock from surface mappi ng and borehole logging has been achieved using probabilistic models. The application of two geostatistical techniques (indicator kriging an d conditional simulation) allows the incorporation of observed litholo gies, taking cognisance of their statistical and spatial distributions . The newly developed probabilistic Bayes-Markov method additionally a llows for the sequences of lithologies to be modelled by the calculati on of transition probabilities and Markov chains. Verification of the estimates produced by these three methods has been enabled using the r ocks actually exposed during the driving of an access tunnel into the Aspo Hard Rock Laboratory in south-east Sweden.