Jharia coalfield, located in Dhanbad district of the Jharkhand state, is one of the most important Gondwana coalfields in India in terms of its prime coking quality of coal and its vast coal resources. Various agencies had carried out exploration in the Jharia coalfield that led to generation of a huge exploration database. However, no exploration modelling had been carried out using geostatistics. In this context, the present paper has attempted to derive geostatistical models of coal seams using the exploration data of ten select coal seams with respect to various proximate coal constituents and seam thickness that were made available to the authors by Bharat Coaking Coal Limited, Dhanbad. Geostatistical structural modelling through semi-variography resulted into quantification of spatial relationship of coal quality parameters together with seam thickness. Block-wise quality estimation employing Ordinary Kriging technique provided improved estimates associated with error of estimation quantified by the magnitude of kriging variance. The uncertainty maps generated using kriging variances are of aid in identifying areas of high uncertainty that decide on further sampling to improve the accuracy of estimation. Simulated annealing algorithm has been applied to carry out geostatistical imaging of a representative coal seam. The technique provided a means to heterogeneity modelling of coal seams and its advantage over the kriged estimates (smoothing effect) is highlighted. Integration of these geostatistical model parameters with the geology of Jharia coalfield aids in characterization of the coal depositional environment (C) 2012 Elsevier B.V. All rights reserved.