Multivariate geostatistical simulation of coal quality data by independent components

Abstract

Quality of a lignite deposit can be characterized by many variables such as calorific value, ash content, and moisture content. These variables show complex spatial relationships with each other. Multivariate geostatistical simulation allows to reproducing such complex relations between the quality variables.In this paper we present independent component analysis and introduce this method as a factorization tool in multivariate geostatistical simulation based on factor approach. The method is based on deriving independent components of multivariate data and simulating each one independently. Independent component simulation technique is applied to geostatistical simulation of three quality variables for a part of the lignite seam subject to severe tectonic movement and regularly variable in quality. The lignite seam belongs to the Lower Coal succession deposited in the Soma coal field, Manisa, Turkey. Ash content, lower calorific value and moisture content are quality variables under consideration. For simulation purposes the independent factors are derived from a linear combination of these quality variables by using independent component analysis, the variograms for the factors are calculated and modeled. After ensuring that the factors are spatially orthogonal, they are independently simulated by direct sequential simulation and the simulated values are back-transformed into original space. The application shows that input statistics such as mean, histogram, variogram and correlation coefficient for the quality variables are reproduced well and independent component simulation can be used in simulation of multivariate data.