Uncertainty assessment of coal tonnage by spatial modeling of seam distribution and coal quality

Abstract

Coal reserve estimation requires comprehensive spatial analysis of geologic and geochemical data. For determination of coal reserve uncertainty associated with tonnage and grade (quality), we present a new approach that stands on spatial modeling of seam distribution and coal quality. A multilayer coal deposit in East Kalimantan, Indonesia was selected as a case study site. Coal quality was evaluated by ash and sodium contents, total sulphur, and heating value. Their spatial models were produced by geostatistical methods, ordinary kriging and sequential Gaussian simulation, which were effective to evaluate local or global uncertainty by honoring spatial correlation structures. The seam distribution was modeled by a binary transformation of the geologic data and the three-dimensional optimization method. It is demonstrated that the lower seam sequence has the highest degree of uncertainty because of low average coal accumulation (tonnage) and the sparseness of sample data points in the north part of the study area. This study demonstrates that uncertainty of coal accumulation is related to the seam distribution and that spatial variability patterns of coal qualities are opposing between ash content and total sulphur: this difference might have been caused by geological controls.