Three‐dimensional hydrofacies modeling based on soil surveys and transition probability geostatistics

Abstract

Typical hydrogeologic data sets consisting of information from boreholes provide excellent information on vertical variability of sedimentary deposits but very limited information on lateral distribution and variability. In cases where surface geomorphic features reflect processes similar to those responsible for past deposition, the soil survey offers a resource for assessing the lateral sediment variability. Facies mean length and transition probability measurements of C horizon textures from the soil maps on the Kings River alluvial fan, California, provide a basis for Markov chain models of spatial variability in the principal lateral directions and facies orientation information for the horizontal plane. Incorporation with a Markov chain model of vertical‐direction transitions based on well data yields a three‐dimensional Markov chain model of sediment variability which includes cross correlation between sediment types and representation of asymmetry (e.g., fining upward tendencies). Use of the model in geostatistical conditional simulation and simulated annealing produces a detailed, geologically plausible image of the subsurface hydrofacies distribution.