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Geostatistical techniques are used to estimate recoverable reserves at unsampled locations and to quantify uncertainty. Several variables are often measured and important for reserve evaluation. Using more variables improves the quality of modeling, but quantifying the relationships between the variables is difficult. The traditional linear model of coregionalization has been used to quantify the relationship between multiple variables, but ensuring the mathematical validity of the model is cumbersome. This research proposes an approximate method that improves the speed and practicality of the numerical modeling process by easily modeling multiple regionalized variables. The proposed algorithm is based on block LU simulation and takes local transformation into consideration. Application to a nickel deposit demonstrates the proposed methodology. / Mining Engineering