Abstract
This review was initially motivated by the author's own experience in attempting to reconcile run-of-mine production tons with the Coal Resource and Reserve estimation of mineable, in-situ tonnages. The primary scientific measurements and observations that are collected during exploration at the beginning of the value chain will have a profound effect on the future of the mining operation. Due diligence must be exercised during the planning of a new mine and during the life of an existing mine. The comments provided by the technical and economic assessment group of Venmyn Deloitte confirmed the need for this critical review. They found the reporting of Coal Resources in South Africa to be inconsistent. This was particularly problematic in the Waterberg Coalfield in Limpopo Province. In this coalfield there are two types of coal deposit present. The first is comprised of the thick intercalated, cyclic coal and shale/mudstone sequences of the Volksrust Formation. This overlies multiple coal seams within the Vryheid Formation, each of which is thick enough to be extracted as an individual raw coal unit. On the other hand, the interbedded coal and shale seams of the Volksrust Formation require beneficiation to separate the coal from the shale. The review examines practices and methods, investigates alternatives, provides checks and balances, and tests these against actual production reconciliations. In conclusion, the best estimates of the mineable, in-situ tonnage will be obtained from the air-dry raw material density. These estimates should be adjusted afterwards to allow for free moisture content. The adjustments are derived from reconciliation data. The greatest contributing factor to the over-estimation of Reserve tonnages is the moisture content of the raw material. This fluctuates significantly under varying conditions in situ, as well as upon exposure to the natural environment. The air-dried density of the raw material includes inherent (structurally bound) moisture within the matrix. It provides credible tonnage estimations of raw material available while also providing an indication of voids within the volume of material being assessed. The calculated solids percentage can be used to adjust the specific gravity, which is determined via the Archimedes principle. This will supply a representative estimate of the material to be mined.
Highlights
Problems related to the reconciliation of product predictions and run-of-mine tonnages obtained from the geological model led to two major projects, initiated by the author, being undertaken at Grootegeluk Coal Mine in Limpopo Province
Groundwater levels, porosity, and permeability would greatly influence the in-situ density of the material being assessed. By implication this requires exploration core to be impeccably preserved on recovery so that the adventitious moisture content may be accurately determined in the laboratory
Information with regard to in-situ densities determined during the exploration phase and used for mineable tons in-situ determinations will no longer be valid since the moisture content in the subsurface environment has changed over time
Summary
Problems related to the reconciliation of product predictions and run-of-mine tonnages obtained from the geological model led to two major projects, initiated by the author, being undertaken at Grootegeluk Coal Mine in Limpopo Province. The prediction of run-of-mine feedstock and the expected product yields should be optimal and realistically based on the mining process, the beneficiation plants, products required, and material available This has been accomplished by a back-to-basics evaluation, starting at the exploration phase, through core recovery, depth corrections, lithological demarcation, lithological logging of the core, profile generation, and subsequent correlation for sample delineation, sampling, and preparation prior to dispatch to accredited laboratories for analyses, and an evaluation of laboratory results. The first is an ash-adjusted density algorithm derived from a regression of 31 000 float and sink data-sets to obtain an accurate absolute dry density value for each float fraction within a set range of fixed density values, and adjusting these with reference to the inherent moisture content determined in the laboratory to give a credible air-dry density value for the sample. Coal values from descriptive statistics based on original data-set used for AAD evaluation
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