Estimation of Proximate Parameters of Coal Seams by Well Logs through Kriging Interpolation

In this paper, a new method is implemented based on the Kriging interpolation to estimate the proximate parameters of coal seams using the well logs. For this purpose, the data of seven boreholes were employed through a case study to explain the method and reliability of the results. According to this method we assume the data of two or more well logs as Cartesian coordinate axes and a proximate parameter as the variable distributed in this coordinate system. At first, the values of each log corresponding to the coal seams are extracted from the reference borehole data, and the coordinate axes are determined based on the type of logs. In the present case study, given the integrity of gamma ray logs, sonic logs and porosity logs in all the boreholes of the region, three coordinate axes were defined and the distribution of proximate parameters was modelled in the coordinate system. Given the number of existing logs, it was possible to model all scenarios by a triple combination of logs, and the best cross correlated model was selected as the parameter distribution model. Using this model, the proximate parameters were eventually estimated in the borehole for which only well logging data were available. The estimation of proximate parameters based on the Kriging interpolation leads to improved results, especially for estimation of the ash content, compared with the conventional method which incorporates logs for estimation of the parameters based on the correlation between the log and the proximate parameter.