Drilling operations in polar regions and mountainous areas are complicated by nature of the extreme environment. Yet conventional rotary drilling technologies can be used to drill ice for scientific samples and oth- e...Drilling operations in polar regions and mountainous areas are complicated by nature of the extreme environment. Yet conventional rotary drilling technologies can be used to drill ice for scientific samples and oth- er research. Due to such reasons as power consumption and weight complications, it is hard to apply a conven- tional rotary drilling rig for glacial exploration. Use of small, relatively lightweight, portable engine-powered drilling systems in which the drill lifting from the borehole is carried by the winch. It is reasonable enough for near-surface shallow ice-drilling down to 50 m. Such systems can be used for near-surface ablation-stakes in- stallation, also temperature measurements at the bottom of active strata layer, revealing of anthropogenie pollu- tion, etc. The specified used in this research is an auger ice drill powered by a gasoline engine. At this stage, it is crucial to choose effective drilling parameters such as weight on bit （WOB） and drill bit rotation rate. Sen- sors equipped on the rig have measured the main parameters of the drilling process, such as drill speed, WOB, drill rotation speed, torque and temperature. This paper addresses research on drilling parameters of engine powered auger ice drill and supplies some recommendations for optimization of any ice-core drilling process.展开更多
Artificial Intelligence(AI)is becoming popular for the Rate of Penetration(ROP)estimation,hence,the need to study the best techniques and their advantages over empirical models.Various literatures were analysed to det...Artificial Intelligence(AI)is becoming popular for the Rate of Penetration(ROP)estimation,hence,the need to study the best techniques and their advantages over empirical models.Various literatures were analysed to determine the prevalence of AI in ROP computation and compare the computation accuracies with empirical models.Artificial Neural Network(ANN)accounted for over 92%of the AI techniques used for ROP computation and Weight on Bit(WOB)mostly influenced the computation accuracy.The accuracy of AI algorithms is better than the empirical models thus,will improve the drilling efficiency,reduce cost and enhance the development of pad wells.展开更多
基金Supported by projects of National Science Foundation of China(No.41327804)the Geological Survey of China(No.3R212W324424)
文摘Drilling operations in polar regions and mountainous areas are complicated by nature of the extreme environment. Yet conventional rotary drilling technologies can be used to drill ice for scientific samples and oth- er research. Due to such reasons as power consumption and weight complications, it is hard to apply a conven- tional rotary drilling rig for glacial exploration. Use of small, relatively lightweight, portable engine-powered drilling systems in which the drill lifting from the borehole is carried by the winch. It is reasonable enough for near-surface shallow ice-drilling down to 50 m. Such systems can be used for near-surface ablation-stakes in- stallation, also temperature measurements at the bottom of active strata layer, revealing of anthropogenie pollu- tion, etc. The specified used in this research is an auger ice drill powered by a gasoline engine. At this stage, it is crucial to choose effective drilling parameters such as weight on bit （WOB） and drill bit rotation rate. Sen- sors equipped on the rig have measured the main parameters of the drilling process, such as drill speed, WOB, drill rotation speed, torque and temperature. This paper addresses research on drilling parameters of engine powered auger ice drill and supplies some recommendations for optimization of any ice-core drilling process.
文摘Artificial Intelligence(AI)is becoming popular for the Rate of Penetration(ROP)estimation,hence,the need to study the best techniques and their advantages over empirical models.Various literatures were analysed to determine the prevalence of AI in ROP computation and compare the computation accuracies with empirical models.Artificial Neural Network(ANN)accounted for over 92%of the AI techniques used for ROP computation and Weight on Bit(WOB)mostly influenced the computation accuracy.The accuracy of AI algorithms is better than the empirical models thus,will improve the drilling efficiency,reduce cost and enhance the development of pad wells.
