Real-time resource model updating for improved coal quality control using online data

Abstract

In recent years a real-time resource model updating concept has proven to increase the material quality control and process efficiency in geostatistics. The real-time resource model updating concept integrates online-sensor data, measured fromthe production line, into the resourcemodel. This integration quickly improves the accuracy of the resource model. The aim of this contribution is to adapt this concept into coal production and to apply the developed framework on an industrial case. The result of this study will provide an additional improvement to coal quality management, by mainly focusing on the ash content in the deposit. This includes high ash values in coal seams, which are caused by sand intrusions and are greatly affecting the operational process. A tailored Ensemble Kalman Filter approach, specifically applicable in coal production, is presented after a detailed literature review. For validation, a 2D case study is performed in a fully controllable environment. Further, the approach is benchmarked against an alternative proven approach. To demonstrate the value added a full scale industrial application is performed focusing on improving the lignite quality control in the production process. The results of integrating online measurement data into the resource model indicate a significant improvement (in the order of 70%) in coal quality production.