Open AccessApplication of Geostatistics for Cleat Data Validation in Sungai Lilin, Musi Banyuasin Region, South Sumatra
Author(s) -
Stevanus Nalendra Jati,
Idarwati,
Ildo M. Putra,
FadlanAtmaja Nursiwan
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1363/1/012045
Subject(s) - outlier , weathering , geostatistics , geology , soil science , mining engineering , computer science , artificial intelligence , geochemistry , mathematics , statistics , spatial variability
Cleat on coal seam is a slope stability controller, as well as permeability and porosity for fluidal flows. It also has become an interesting issue on coal mining, nevertheless the finite quantitative data. As a matter of facts, there is actually some available data about cleat as attributes, but this study only objecting on the orientation, cleat spacing, and cleat aperture. Cleat attributes measurement through field observation at two coalfields;Baturona and PMC in the area of Sungai Lilin, MusiBanyuasin Region. Next, those 667 faces and butt cleats were measured from 8 scanlines being analyzed using geostatistic methods. The purpose of geostatisticanalysis in this study is to see the relation between variables (cleat attributes) to evaluate data quantitatively until the normal distribution is obtained. The data filter was done as a treatment until valid data is reached through the boxplot model. Early boxplot result that almost entirely had outliers data in each seam. In fact, it is commonly seen some extreme outlier data. This suggests that outlier data filter is treated as a treatment until a normal distribution system is achieved on each cleat attribute. Identification of cleat outliers has been affected by mining activity, or due to weathering processes in the coal seams that have been exposed.