Research and application of downhole drilling depth based on computer vision technique

Abstract

Gas drainage and water detection and release by drilling are essential to prevent gas and water disasters in China. The accurate drilling depth substantially affects gas drainage, water exploration, and safety problems. Consequently, it is essential to precisely monitor drilling depth by counting drill pipe to assure drilling efficacy. Based on increasingly sophisticated subterranean video surveillance technology, this paper leverages computer vision technology to implement precise drill pipe counting and calculates the corresponding drilling depth determined by the number of drill pipes. First, the operation of the drilling rig was examined, and the movement trajectory of the impact power head on the drilling rig feeding mechanism was estimated to quantify the number of drilling pipes. The optimized Retinex mine image enhancement algorithm is used to preprocess the initial underground image with issues including an unreliable light source, considerable light and shadow fluctuation, and blurred lens. Furthermore, the challenges of fixed scale and easy loss of target tracking in the Kernel Correlation Filter Algorithm are addressed by employing an adaptive scale algorithm and a re-detection approach to boost target location data accuracy. Eventually, the amount of drill pipes is calculated by the effective peak count of the displacement, the precise drilling depth is achieved, and the result is consistent with the actual drilling construction condition by evaluating the on-site drilling video. This study adopted computer vision tracking technology to tackle the challenge of calculating drilling depth and building progress accurately, ensuring the safe and efficient output of the mine.