Drill Bit Grading Using LiDAR and Imagery on the Apple Smart Devices

Abstract

[EN] Reservoir development in the petroleum industry starts with the drill bit. A drill bit’s dull condition must be closely monitored since it significantly influences the efficiency and the cost of drilling operations. The dull condition check procedure is called drill bit grading and is essentially a change detection problem to determine the state of the drill bit, in particular the wear of the cutting teeth inserts. Currently, the grading is conducted manually on-site, which is error-prone and highly subjective. Laser scanning technology offers a potential solution to overcome the shortcomings of existing practice. The integration of LiDAR (Light Detection and Ranging) on the newly-launched iDevices, the iPhone 12 Pro and the iPad Pro 2020 offers new opportunities for close-range measurement given their huge customer base and low cost. The goal of this research is to investigate the performance of these devices, and to develop a tool for the drill bit grading. Since bit grading is significantly impacted by the performance of the sensor, several basic tests were first conducted under controlled experimental conditions, e.g., the room temperature and ambient lighting and measurement surface. The temporal stability of the iDevices was examined by capturing a series of datasets of a flat wall over forty-five (45) minutes, then the effect of range, reflectivity and incidence angle on data quality was tested by measuring the Spectralon targets at different situations. The performance tests found that using only the LiDAR data was not sufficient for drill bit grading. Thus, a preliminary grading system based on the fusion of LiDAR and color camera is proposed by modelling the post-drilling bit and detecting the changes.