TOWARDS AN INTEGRATED SUBJECTIVE PROBABILISTIC ASSESSMENT METHODOLOGY FOR POTENTIALLY MINEABLE COAL

Current coal resource assessments are deterministic and are designed to answer the question, "How much coal exists in the XYZ coal bed?" The answer is commonly supplied in terms of tonnages divided into reliability categories, such as "measured, indicated, inferred, and hypothetical," based on the number and spacing of coal thickness data points. A subjective probabilistic assessment, instead, would ask the question, "How much coal might be mined from the XYZ coal bed in the next 20 (or 30) years?" The answer would be a probability distribution that would yield the 95, 50, 5, and mean probabilities in percent.

Input data for a subjective assessment of potentially mineable coal, in tons, would mimic input data for assessments of conventional oil and gas assessment units (plays). Critical data would include the numbers and sizes of existing mines currently producing coal from a coal bed, where the size of the mine is defined as its cumulative production plus reserves at the mine; the input data would also include an estimate of the numbers and sizes of mines expected to be opened within the assessment period. Monte Carlo simulations of the numbers and sizes of mines expected to be opened would be combined by utilizing appropriate computer software to produce the probability distributions of potential coal reserves in tons.

The estimate of the numbers and sizes of future mines would be based upon historical mining data and knowledge of the coal system that defines the coal bed. Minimum data required would include the mapped extent of the coal bed, area mined out, coal thickness maps, structure maps, and overburden maps, and some knowledge of the quality of the coal bed.

Subjective probability assessments would not attempt to answer questions concerning how much coal would actually be produced within a given time period. Answering that question would require knowledge of the impact of potential regulatory, societal, technical, and economic conditions, including an estimate of the competitiveness of alternative energy sources.