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Geological data plays an indispensable role in mining coal safely and efficiently. Traditional rock core method not only have some defects of high labor intensity, high cost and slow speed, but also difficultly got the rock of the weak interlayer. Based on this, parameter-based identification method of the rock characteristics during the drilling operation is a hot research topic. In this paper, a comprehensive prediction model was established to predict the rock Uniaxial Compressive Strength (UCS). Besides, the prediction results of the comprehensive prediction method, multiple linear regression model, and Mechanical Specific Energy (MSE) model were compared. Furthermore, the K-means clustering method is used to classify the rock formation based on the measured drilling parameters. The result indicates that torque work is significantly correlated with the UCS of rock. The comprehensive method has the best prediction result, and the prediction error of rock's UCS is within 5MPa. The prediction results of rock classification are different from the actual results, but from the perspective of rock strength, this classification method is better. The rapid identification method of rock formation based on MWD provides a reference for the roadway support scheme and parameter design, and is an important part of the intelligent development of coal mines.

A Comprehensive Prediction Model of Rock Strength and Its Application on Classifying the Rock During the Drilling