SYNOPSIS The initial evaluation of a coal deposit often raises uncertainty with regard to the accuracy of the reported Resources and Reserves. Reconciliation of results from mining and beneficiation with the original raw field data highlights deficiencies in original estimations. Credible Resource and Reserve estimation forms the basis on which an entire mining enterprise is motivated, initiated, funded, and established as a commercially viable proposition. This is required for sustainable extraction purposes and to support vital downstream industries such as power generation. Accurate determination of the density of the matrix of the material being evaluated is the key to credible values being obtained for Resources and Reserves. Losses between 15% and 20% of the Resource/Reserve can be realized if incorrect densities are applied to the tonnage derivation. Coal plies and particles have different relative densities, determined by the maceral composition, rank, and mineral and moisture content. These factors in turn contribute to the moisture, volatile matter, ash and carbon contents of a coal, which affect the overall density of the raw coal. More specifically, the relationship of ash to density and the effective matrix porosity were found to be critical in solving the greater majority of the problems in predictive calculations. A major deficiency identified is the inability to determine effective porosity, allowing absorption of adventitious moisture and altering the mass of the core sample. Although the volume of the raw material is altered through crushing, the change in mass after controlled air-drying, used with the original geometrical volume of the raw material, provides a credible air-dry density and allows the determination of the volumetric change related to effective porosity. This parameter can be validated through the evaluation of proximate ash using the ash-adjusted algorithm and a correction for the inherent moisture applied to also give a credible relative density value for an air-dried sample. A combination of theoretical, empirical, and reconciliatory evaluations of the available data, taken from the exploration phase through the mining process to final production, has shown that an integrated approach using the ash-adjusted density (AAD) methodology, in conjunction with other evaluative techniques, provides credible results with a considerably higher degree of accuracy than is currently possible. Keywords: coal, deposit evaluation, Resources, Reserves, density determination, ash-adjusted density.
Command prediction based on early 3D modeling design logs by deep neural networks
