Conditional co-simulation of continuous and categorical variables for geostatistical applications

Modelling of cement raw material compositional indices with direct sequential cosimulation

“…Sequential Gaussian simulation (SGS) and sequential indicator simulation (SIS) were the first versions used (Journel, 1989;Goovaerts, 1997;Deutsch and Journel, 1998). More recently, DSS such as that proposed by Caers (2000) and improved by Soares (2001) became widely used sequential simulation techniques for continuous variables, avoiding transformations to normal score space and facilitating the use of secondary information (Robertson et al, 2006;Emery and Silva, 2009). In the present work, direct sequential simulation and cosimulation were used (DSS and CoDSS).…”

“…They are often used in evaluation of reserves and mine/quarry exploitation planning (Taboada et al, 1999;Tercan and Özçelik, 2000;Emery and Silva, 2009).…”

Simulation of cement raw material deposits using plurigaussian technique

“…It is necessary for a lithological assessment to transfer the underground geological structure data to a digital media. There are a few methods used for this transferring process such as multipoint simulation with training image [16][17][18], multivariable stochastic model for indicator simulation [5,19], co-simulation [20], truncated Gaussian simulation [21,22]. Joint simulation also has superiorities on other techniques.…”

Geological Modelling and Validation of Geological Interpretations via Simulation and Classification of Quantitative Covariates

“…Several alternatives have been proposed to mitigate these discontinuities and to account for spatial correlation across the domain boundaries [6][7][8][9][10]. Another approach to produce gradual transitions near the domain boundaries is to model the quantitative variables of interest with no previous geological domaining by considering the controlling rock types or ore types as cross-correlated covariates [11][12][13][14][15][16]. Geostatistical simulation approaches have been designed to construct several geological scenarios in order to quantify uncertainty in the actual locations and extents of rock types or ore types, accounting for their spatial continuity and proportions (which may vary in space), and contact relationships, including chronological associations, allowable and non-allowable contacts, edge effects (preferential contacts), and directional effects (asymmetrical spatial relationships) between rock types or ore types ( [17][18][19][20] and references therein).…”