3D geological model construction and error analysis of intelligent mining working face

The complexity of geological conditions is one of the key issues affecting the further development of current intelligent mining, and there is an urgent need to build a high-precision 3D geological model of the mining face. This article analyzes the construction method of the intelligent mining geological model, and takes an intelligent working face of Huangling No.1 Mine as an example, combines all the geological exploration data of the working face, and uses the TIM-3D modeling software to construct the initial static model and the working face respectively. The dynamic model of the working face is equipped with a transparent face digital twin system to display the intelligent mining geological model; by comparing the actual coal thickness value revealed by the mining and the geological model predicting the coal thickness value, the error between the static geological model and the dynamic geological model was analyzed. The reasons for the model errors were explained. The analysis concluded that: The accuracy of the static geological model cannot meet the geological requirements of intelligent mining; the updated dynamic geological model can significantly reduce the coal thickness prediction error and basically meet the geological requirements of intelligent mining; the error of the model is the measurement error and the amount of sampled data It is caused by the selection of its distribution and interpolation algorithm. It is comprehensively believe that the establishment of the model should fully integrate all the geological information of the working face, the interval between the roadway marker points in the model establishment should be less than 10 m, and the advancing and mining distance for the dynamic update of the model should be less than 15 m. The research results are of great significance for fully understanding the accuracy of the current intelligent mining geological model, and for the next step of the development of intelligent intelligent mining geological support technology.