Geostatistical modeling is one of the most important tools for building an ensemble of
probable realizations in earth science. Among them, multiple-point statistics (MPS) has …

Abstract Markov chain Monte Carlo methods such as the Gibbs sampler and the Metropolis
algorithm can be used to sample solutions to non-linear inverse problems. In principle, these …

Geometallurgy is a team-based multidisciplinary approach aimed at integrating geological,
mineralogical and metallurgical information and yielding a spatial quantitative predictive …

The open pit mine production scheduling problem determines a sequence of three-
dimensional, notional block extraction that maximises net present value (NPV) of future cash …

In the mid-1980s, still in his young 40s, André Journel was already recognized as one of the
giants of geostatistics. Many of the contributions from his new research program at Stanford …

Volumetric medical images are widely used in diagnosing and detecting health problems of
patients. Large datasets of volumetric medical images required huge storage space and …

Most current multiple-point statistics (MPS) algorithms are based on a sequential simulation
procedure, during which grid values are updated according to the local data events …

Training image‐based geostatistical methods are increasingly popular in groundwater
hydrology even if existing algorithms present limitations that often make real‐world …

High-order sequential simulation techniques for complex non-Gaussian spatially distributed
variables have been developed over the last few years. The high-order simulation approach …

Stochastic long-term mine planning has evolved to account for different sources of
uncertainty. Typically, the uncertainty and local variability of boundaries in geological …