Standard Practice for Statistical Modeling of Uncertainty in Assessment of In-place Coal Resources

Importancia y uso:

5.1 Traditional methods for expressing geological uncertainty consist of preparing reliability categories based simply on the distance between drill hole data points, such as the one described by Wood et al. (5) that uses only the drill holes within the coal bed. A major drawback of distance methods is their weak to null association with estimation errors. This practice provides a methodology for effectively assessing the uncertainty in coal resource estimates utilizing stochastic simulation. In determining uncertainty for any coal assessment, stochastic simulation enables consideration of other important factors and information beyond the geometry of drill hole locations, both in and out of the coal bed, including: non-depositional channels, depth of weathering, complexity of seam boundaries, coal seam subcrop projections, and varying coal bed geology for different seams due to fluctuating peat depositional environments. Olea et al. (6) explains in detail the methodology behind this practice and illustrates it with an example.

5.2 For multi-seam deposits, uncertainty can be expressed on an individual seam basis as well as an aggregated uncertainty for an entire coal deposit.

5.3 The uncertainty is expressed directly in tons of coal. Additionally, this practice allows the statistical analysis to be presented according to widely-accepted conventions, such as percentiles and confidence intervals. For example, there is a 90 % probability that the actual tonnage in place is 314 million metric tons ± 28.8 million metric tons (346 million tons ± 31.7 million tons) of coal.

5.4 The results of an uncertainty determination can provide important input into an overall risk analysis assessing the commercial feasibility of a coal deposit.

5.5 A company may rank coal resources per block (cell) based on the degree of uncertainty.

Subcomité:

D05.07

Volúmen:

05.06

Número ICS:

35.240.70 (IT applications in science), 73.020 (Mining and quarrying)

Palabras clave:

coal resources; confidence interval; estimation; geostatistics; probability distribution; realization; simulation;