  A method (Ember) for non-stationary spatial modelling with multiple secondary
variables by combining Geostatistics with Random Forests is applied to a
three-dimensional Reservoir Model. It extends the Random Forest method to an
interpolation algorithm retaining similar consistency properties to both
Geostatistical algorithms and Random Forests. It allows embedding of simpler
interpolation algorithms into the process, combining them through the Random
Forest training process. The algorithm estimates a conditional distribution at
each target location. The family of such distributions is called the model
envelope. An algorithm to produce stochastic simulations from the envelope is
demonstrated. This algorithm allows the influence of the secondary variables as
well as the variability of the result to vary by location in the simulation.
