Drill hole spacing optimization of non-stationary data for seam thickness and total sulfur: A case study of coal deposits at Balikpapan Formation, Kutai Basin, East Kalimantan

Abstract

The characteristics of coal deposits are relatively homogeneous in general; therefore, their geometric and quality parameters have stationary distributions. However, the geological setting could change this stationarity characteristic; thus, the coal may contain spatially different data trends. These data trends should be treated to derive an accurate estimation of the available coal resources. The general objective of this study is to optimize the drill hole spacing for the non-stationary dataset by applying some approaches to detrend the data. These approaches include spatially dividing the data into several domains (i.e., spatial clustering), extending the existing grid size (drill hole spacing), transforming the data, and using residuals data. The geometric and quality parameters used in this study were the seam thickness and total sulfur, respectively, from one coal seam in the Balikpapan Formation, Kutai Basin, East Kalimantan, Indonesia. The treated dataset was statistically and spatially analyzed to identify the data distribution changes. Nonetheless, the extended spacing, transformation, and residuals approaches resulted in almost similar data trends to the original. The study results indicated that the best approach to detrend the seam thickness and total sulfur at the study site was by dividing the dataset into three spatial domains (i.e., clusters). The global estimation variance method was used in the clustered dataset to produce optimum drill hole spacings of 1000 m, 2000 m, and 2600 m for the northern, central, and southern clusters, respectively, and the measured coal resources at the study site were obtained.