Geostatistical Coal Resource Characterization Using Intervariable Correlations

Coal resource characterization usually calls for estimating more than one variable over a block or node simultaneously. Within the realm of geostatistics, each variable has been evaluated independently from the others assuming a lack of significant correlation. Research conducted with coal seams, however, has shown that the variables of immediate interest, such as seam thickness, ash, sulfur content, and density depict some correlation schemes in distinct zones, if not throughout the entire area. The above findings have two immediate consequences : (1) correlation analyses provide guidelines to determine the geologically distinct zones, and (2) where possible, cokriging should be used instead of kriging. This will maximize data utilization decreasing the frequently criticized high estimation errors. The cokriging formulation will also provide more accurate estimates for under sampled variables using better-sampled ones. This is a common case with coal with regard to the non-cored reconnaissance drill holes for which only very few variables were recorded. A case study illustrates the improvements that may be obtained by taking advantage of the intervariable correlations.