Multi-attribute dynamic modeling technique for transparent working face

In order to provide a high-precision geological model for intelligent mining,a multi-attribute dynamic model- ing method for a transparent working face was put forward. Features of multi-source heterogeneous data from the com- prehensive detection of working face,the multi-attribute data fusion algorithm and dynamic visualization modeling tech- nique were studied and applied. Multi-attribute, multi-dimension and multi-precision data can be acquired through some comprehensive detection technologies at different production stages. Based on phases and frequencies of modeling data generation,the multi-source heterogeneous detection data were divided to static data,dynamic data and real-time data. Dimension and scales of the multi-source heterogeneous data can be unified through data registration and can be verified through cross validation. Coal thickness,stratum velocity,resistivity and other attribute parameters can be ob- tained by log-seismic joint inversion,seismic-resistivity joint inversion and multi-parameters joint inversion. The geo- logical model can be rapidly updated by using local data search,interpolation and grid technologies. Efficient and real- time rendering was realized through locally rendering and CUDA drawing methods. Results show that the multi-source heterogeneous detection data can be unified in the same geological space. Data interpretation accuracy can be raised by cross validation. Spatial resolution can be raised and attributes can be added by joint inversion. Based on the primary geological model built by the static data and dynamic data generated by fine detection in working face,coal seam roof, floor and structure information in front of the mining face can be updated based on dynamic data and real-time data to improve the model precision continuously. Transparent working face dynamic model was built on the basis of multi-at- tribute heterogeneous data generated during mining process. Intelligent cutting plan can be calculated through constant interaction between the dynamic model and mining system.