Development of Conceptual Model to Characterize Uncertainty in Coal Resource Estimates: ABSTRACT

Abstract

Published coal reserve estimates for the United States have traditionally differed by wide margins, e.g., Electric Power Research Institute estimating 135 billion tons and U.S. Geological Survey estimating 212 billion tons. These differences in reserve estimates possibly result from mechanically following the USGS/USBM resource classification system, without appreciation of lateral variability in seam thickness and seam discontinuity. Variability and discontinuity are dependent in part upon depositional history. For example, coals accumulated on an ancient alluvial plain or in a back barrier setting are more variable and, thus, more difficult to characterize as to resources than are those that accumulated on a delta plain. A statistical model for characterizing uncertainty in End_Page 745------------------------------ coal resource estimates is proposed. This model is based upon defining the area of influence of bore holes in different depositional settings with respect to consistency of coal thickness and coal quality. The model is being developed through evaluation of lignite occurrences in the Texas Gulf Coast Tertiary basin. In this basin, lignites occur in three Eocene stratigraphic units, the Wilcox Group, Yegua Formation, and Jackson Group, as component facies of three depositional systems--fluvial, deltaic, and strand plain/lagoonal. Within a particular depositional setting, densely-drilled deposits are being compared with areas of sparse drilling to characterize variability and, thus, determine the optimum spacing necessary to define seam geometry. Geostatistical analyses such as variogram , which estimate the range of influence of a bore hole as a measure of spacing, should aid in determining optimum spacing for a specific degree of certainty, within a given depositional setting. In this way, certainty ranges could be established for different depositional systems within a given coal basin. It is anticipated that this evaluation could lead to more reliable coal resource estimates. End_of_Article - Last_Page 746------------