The formation of the gas emission zone in longwall mining and the potential amount of gas in this zone are factors of local geology and spatial variability within this geology. Therefore, geostatistical methods can be used tor modeling and prediction of gas amounts and for assessing its uncertainty in the gas emission zone of longwall mines. This study used core data obtained from 64 exploration boreholes drilled from the surface to the bottom of the Pittsburgh coal seam in a mining district in the Northern Appalachian basin. After identifying important coal layers for the gas emission zone, semivariogram modeling was conducted for different coal seams to define the distribution and continuity of various attributes. Sequential simulations were performed for stochastic assessment of these attributes to calculate gas-in-place (GIP) in each coal seam. GIP calculations for coals of various gas emissions zones were combined and ranked for their cumulative distribution function to find GIP in the caved zone and in the fractured zone at the 5%, 50%, and 95% quantiles. Fifty percent quantile results were later used to isolate a panel from the whole area and create a mosaic representation corresponding to the daily advance rate of the longwall face. This approach helped to estimate the daily emissions of this panel from the caved zone and from the fractured zone. Results showed that gas-in-place in the Pittsburgh coal seam, in the caved zone, and in the fractured zone showed spatial correlations that could be modeled and estimated using geostatistical methods. This study showed that gas-in- place volumes in the study area may be as high as 12.3 Bscf and as much as 3.5 MMscf per acre of mining.
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