An overview to geostatistical modeling methods of the categorical variables for mineral resources and hydrocarbon reservoirs

Considering the key role of the mineral resources and hydrocarbon reservoirs and consequently, the inevitability of having their precise models, geostatistical tools are regarded as efficient and functional solutions for these problems. They not only provide accurate predictions, but they also quantify the corresponding uncertainties. To obtain a precise geostatistical models, an exact estimation of their categorical variables such as lithofacies and alteration zones are necessary. In this article, four geostatistical methods of modeling categorical variables were reviewed and their advantages and disadvantages were mentioned. The discussed methods include Sequential Indicator Simulation (SIS), Truncated Gaussian simulation (TGS) and Truncated Pluri-Gaussian Simulation (PGS), methods based on using Markov chain and transition probabilities.

An overview to geostatistical modeling methods of the categorical variables for mineral resources and hydrocarbon reservoirs Keywords:

Sequential Indicator Simulation (SIS) , Truncated Gaussian and Pluri-Gaussian Simulation (TGS and PGS) , Markov Chains , Transition Probabilities.