This paper focuses on the use of rotary-percussive drilling for hard rocks.In order to improve efficiency and reduce costs,it is essential to understand how operational parameters,bit wear,and drilling performance are...This paper focuses on the use of rotary-percussive drilling for hard rocks.In order to improve efficiency and reduce costs,it is essential to understand how operational parameters,bit wear,and drilling performance are related.A model is presented therein that combines multibody dynamics and discrete element method(DEM)to investigate the influences of operational parameters and bit wear on the rate of penetration and wear characteristics.The model accurately captures the motion of the bit and recreates rock using the cutting sieving result.Field experimental results validate the rod dynamic behavior,rock recreating model,and coupling model in the simulation.The findings indicate that hammer pressure significantly influences the rate of penetration and wear depth of the bit,and there is an optimal range for economical hammer pressure.The wear coefficient has a major effect on the rate of penetration,when wear coefficient is between 1/3 and 2/3.Increasing the wear coefficient can reduce drill bit button pressure and wear depth at the same drill distance.Gauge button loss increases the rate of penetration due to higher pressure on the remaining buttons,which also accelerates destruction of the bit.Furthermore,a more evenly distributed button on the bit enhances the rate of penetration(ROP)when the same number of buttons is lost.展开更多
设计了一种基于1 bit Sigma-Delta调制技术的数字磁通门磁强计,并利用Matlab Simulink工具对其进行仿真建模与分析,获得了系统在噪声、线性度、动态响应速度以及频率响应等方面的性能参数.在±1000 nT量程范围内,该磁强计系统在1 H...设计了一种基于1 bit Sigma-Delta调制技术的数字磁通门磁强计,并利用Matlab Simulink工具对其进行仿真建模与分析,获得了系统在噪声、线性度、动态响应速度以及频率响应等方面的性能参数.在±1000 nT量程范围内,该磁强计系统在1 Hz处的噪声为0.17 pT·Hz-1/2,最大线性误差为1.04 pT,动态响应速度为1.07×10^(3) nT·s^(-1),频率响应带宽超过30 Hz.仿真结果证实,采用1 bit Sigma-Delta调制技术显著提高了数模转换器(Digital-to-Analog Converter,DAC)的转换精度,有效降低了数字磁强计系统的本底噪声和非线性误差,显著提升了数字磁强计的性能.基于1 bit Sigma-Delta调制技术的数字磁通门磁强计性能指标能够满足高精度磁场探测任务的要求,为空间磁场探测领域提供了一种高精度、高可靠性的探测手段,在深空探测及空间科学领域具有广泛的应用前景.展开更多
This study aims to eliminate the subjectivity and inconsistency inherent in the traditional International Association of Drilling Contractors(IADC)bit wear rating process,which heavily depends on the experience of dri...This study aims to eliminate the subjectivity and inconsistency inherent in the traditional International Association of Drilling Contractors(IADC)bit wear rating process,which heavily depends on the experience of drilling engineers and often leads to unreliable results.Leveraging advancements in computer vision and deep learning algorithms,this research proposes an automated detection and classification method for polycrystalline diamond compact(PDC)bit damage.YOLOv10 was employed to locate the PDC bit cutters,followed by two SqueezeNet models to perform wear rating and wear type classifications.A comprehensive dataset was created based on the IADC dull bit evaluation standards.Additionally,this study discusses the necessity of data augmentation and finds that certain methods,such as cropping,splicing,and mixing,may reduce the accuracy of cutter detection.The experimental results demonstrate that the proposed method significantly enhances the accuracy of bit damage detection and classification while also providing substantial improvements in processing speed and computational efficiency,offering a valuable tool for optimizing drilling operations and reducing costs.展开更多
To optimize the bit selection for large-diameter wellbore in the upper section of an ultra-deep well S-1,a full-well dynamic model integrating drill string vibration and bit rock-breaking was established and then veri...To optimize the bit selection for large-diameter wellbore in the upper section of an ultra-deep well S-1,a full-well dynamic model integrating drill string vibration and bit rock-breaking was established and then verified using measured vibration data of drilling tools and actual rate of penetration(ROP)from Well HT-1 in northern Sichuan Basin.This model was employed to calculate and analyze drill string dynamic characteristics during large-diameter wellbore drilling in the Jurassic Penglaizhen Formation of Well S-1,followed by bit optimization.Research results show that during the drilling in Penglaizhen Formation of Well S-1,considering both the ROP of six candidate bits and the lateral/axial/torsional vibration characteristics of downhole tools,the six-blade dual-row cutter bit with the fastest ROP(average 7.12 m/h)was optimally selected.When using this bit,the downhole tool vibration levels remained at medium-low values.Field data showed over 90%consistency between actual ROP data and dynamic model calculation results after bit placement,demonstrating that the model can be used for bit program screening.展开更多
We experimentally analyze the effect of the optical power on the time delay signature identification and the random bit generation in chaotic semiconductor laser with optical feedback.Due to the inevitable noise durin...We experimentally analyze the effect of the optical power on the time delay signature identification and the random bit generation in chaotic semiconductor laser with optical feedback.Due to the inevitable noise during the photoelectric detection and analog-digital conversion,the varying of output optical power would change the signal to noise ratio,then impact time delay signature identification and the random bit generation.Our results show that,when the optical power is less than-14 dBm,with the decreasing of the optical power,the actual identified time delay signature degrades and the entropy of the chaotic signal increases.Moreover,the extracted random bit sequence with lower optical power is more easily pass through the randomness testing.展开更多
Formation pore pressure is the foundation of well plan,and it is related to the safety and efficiency of drilling operations in oil and gas development.However,the traditional method for predicting formation pore pres...Formation pore pressure is the foundation of well plan,and it is related to the safety and efficiency of drilling operations in oil and gas development.However,the traditional method for predicting formation pore pressure involves applying post-drilling measurement data from nearby wells to the target well,which may not accurately reflect the formation pore pressure of the target well.In this paper,a novel method for predicting formation pore pressure ahead of the drill bit by embedding petrophysical theory into machine learning based on seismic and logging-while-drilling(LWD)data was proposed.Gated recurrent unit(GRU)and long short-term memory(LSTM)models were developed and validated using data from three wells in the Bohai Oilfield,and the Shapley additive explanations(SHAP)were utilized to visualize and interpret the models proposed in this study,thereby providing valuable insights into the relative importance and impact of input features.The results show that among the eight models trained in this study,almost all model prediction errors converge to 0.05 g/cm^(3),with the largest root mean square error(RMSE)being 0.03072 and the smallest RMSE being 0.008964.Moreover,continuously updating the model with the increasing training data during drilling operations can further improve accuracy.Compared to other approaches,this study accurately and precisely depicts formation pore pressure,while SHAP analysis guides effective model refinement and feature engineering strategies.This work underscores the potential of integrating advanced machine learning techniques with domain-specific knowledge to enhance predictive accuracy for petroleum engineering applications.展开更多
Based on the finite-discrete element method,a three-dimensional numerical model for axial impact rock breaking was established and validated.A computational method for energy conversion during impact rock breaking was...Based on the finite-discrete element method,a three-dimensional numerical model for axial impact rock breaking was established and validated.A computational method for energy conversion during impact rock breaking was proposed,and the effects of conical tooth forward rake angle,rock temperature,and impact velocity on rock breaking characteristics and energy transfer laws were analyzed.The results show that during single impact rock breaking with conical tooth bits,merely 7.52%to 12.51%of the energy is utilized for rock breaking,while a significant 57.26%to 78.10%is dissipated as frictional loss.An insufficient forward rake angle increases tooth penetration depth and frictional loss,whereas an excessive forward rake angle reduces penetration capability,causing bit rebound and greater energy absorption by the drill rod.Thus,an optimal forward rake angle exists.Regarding environmental factors,high temperatures significantly enhance impact-induced rock breaking.Thermal damage from high temperatures reduces rock strength and inhibits its energy absorption.Finally,higher impact velocities intensify rock damage,yet excessively high velocities increase frictional loss and reduce the proportion of energy absorbed by the rock,thereby failing to substantially improve rock breaking efficiency.An optimal impact velocity exists.展开更多
基金supported by the National Natural Science Foundation of China Youth Science Foundation of China(Grant No.52308388)the Key Project of High-speed Rail Joint Fund of National Natural Science Foundation of China(Grant No.U1934210).
文摘This paper focuses on the use of rotary-percussive drilling for hard rocks.In order to improve efficiency and reduce costs,it is essential to understand how operational parameters,bit wear,and drilling performance are related.A model is presented therein that combines multibody dynamics and discrete element method(DEM)to investigate the influences of operational parameters and bit wear on the rate of penetration and wear characteristics.The model accurately captures the motion of the bit and recreates rock using the cutting sieving result.Field experimental results validate the rod dynamic behavior,rock recreating model,and coupling model in the simulation.The findings indicate that hammer pressure significantly influences the rate of penetration and wear depth of the bit,and there is an optimal range for economical hammer pressure.The wear coefficient has a major effect on the rate of penetration,when wear coefficient is between 1/3 and 2/3.Increasing the wear coefficient can reduce drill bit button pressure and wear depth at the same drill distance.Gauge button loss increases the rate of penetration due to higher pressure on the remaining buttons,which also accelerates destruction of the bit.Furthermore,a more evenly distributed button on the bit enhances the rate of penetration(ROP)when the same number of buttons is lost.
文摘设计了一种基于1 bit Sigma-Delta调制技术的数字磁通门磁强计,并利用Matlab Simulink工具对其进行仿真建模与分析,获得了系统在噪声、线性度、动态响应速度以及频率响应等方面的性能参数.在±1000 nT量程范围内,该磁强计系统在1 Hz处的噪声为0.17 pT·Hz-1/2,最大线性误差为1.04 pT,动态响应速度为1.07×10^(3) nT·s^(-1),频率响应带宽超过30 Hz.仿真结果证实,采用1 bit Sigma-Delta调制技术显著提高了数模转换器(Digital-to-Analog Converter,DAC)的转换精度,有效降低了数字磁强计系统的本底噪声和非线性误差,显著提升了数字磁强计的性能.基于1 bit Sigma-Delta调制技术的数字磁通门磁强计性能指标能够满足高精度磁场探测任务的要求,为空间磁场探测领域提供了一种高精度、高可靠性的探测手段,在深空探测及空间科学领域具有广泛的应用前景.
基金support of the CNPC International Collaborative Research Project(No.2022DQ0410)。
文摘This study aims to eliminate the subjectivity and inconsistency inherent in the traditional International Association of Drilling Contractors(IADC)bit wear rating process,which heavily depends on the experience of drilling engineers and often leads to unreliable results.Leveraging advancements in computer vision and deep learning algorithms,this research proposes an automated detection and classification method for polycrystalline diamond compact(PDC)bit damage.YOLOv10 was employed to locate the PDC bit cutters,followed by two SqueezeNet models to perform wear rating and wear type classifications.A comprehensive dataset was created based on the IADC dull bit evaluation standards.Additionally,this study discusses the necessity of data augmentation and finds that certain methods,such as cropping,splicing,and mixing,may reduce the accuracy of cutter detection.The experimental results demonstrate that the proposed method significantly enhances the accuracy of bit damage detection and classification while also providing substantial improvements in processing speed and computational efficiency,offering a valuable tool for optimizing drilling operations and reducing costs.
基金Supported by the National Natural Science Foundation of China(52225401)。
文摘To optimize the bit selection for large-diameter wellbore in the upper section of an ultra-deep well S-1,a full-well dynamic model integrating drill string vibration and bit rock-breaking was established and then verified using measured vibration data of drilling tools and actual rate of penetration(ROP)from Well HT-1 in northern Sichuan Basin.This model was employed to calculate and analyze drill string dynamic characteristics during large-diameter wellbore drilling in the Jurassic Penglaizhen Formation of Well S-1,followed by bit optimization.Research results show that during the drilling in Penglaizhen Formation of Well S-1,considering both the ROP of six candidate bits and the lateral/axial/torsional vibration characteristics of downhole tools,the six-blade dual-row cutter bit with the fastest ROP(average 7.12 m/h)was optimally selected.When using this bit,the downhole tool vibration levels remained at medium-low values.Field data showed over 90%consistency between actual ROP data and dynamic model calculation results after bit placement,demonstrating that the model can be used for bit program screening.
基金Project supported in part by the National Natural Science Foundation of China(Grant Nos.62005129 and 62175116)。
文摘We experimentally analyze the effect of the optical power on the time delay signature identification and the random bit generation in chaotic semiconductor laser with optical feedback.Due to the inevitable noise during the photoelectric detection and analog-digital conversion,the varying of output optical power would change the signal to noise ratio,then impact time delay signature identification and the random bit generation.Our results show that,when the optical power is less than-14 dBm,with the decreasing of the optical power,the actual identified time delay signature degrades and the entropy of the chaotic signal increases.Moreover,the extracted random bit sequence with lower optical power is more easily pass through the randomness testing.
基金supported by the National Natural Science Foundation of China(Grant numbers:52174012,52394250,52394255,52234002,U22B20126,51804322).
文摘Formation pore pressure is the foundation of well plan,and it is related to the safety and efficiency of drilling operations in oil and gas development.However,the traditional method for predicting formation pore pressure involves applying post-drilling measurement data from nearby wells to the target well,which may not accurately reflect the formation pore pressure of the target well.In this paper,a novel method for predicting formation pore pressure ahead of the drill bit by embedding petrophysical theory into machine learning based on seismic and logging-while-drilling(LWD)data was proposed.Gated recurrent unit(GRU)and long short-term memory(LSTM)models were developed and validated using data from three wells in the Bohai Oilfield,and the Shapley additive explanations(SHAP)were utilized to visualize and interpret the models proposed in this study,thereby providing valuable insights into the relative importance and impact of input features.The results show that among the eight models trained in this study,almost all model prediction errors converge to 0.05 g/cm^(3),with the largest root mean square error(RMSE)being 0.03072 and the smallest RMSE being 0.008964.Moreover,continuously updating the model with the increasing training data during drilling operations can further improve accuracy.Compared to other approaches,this study accurately and precisely depicts formation pore pressure,while SHAP analysis guides effective model refinement and feature engineering strategies.This work underscores the potential of integrating advanced machine learning techniques with domain-specific knowledge to enhance predictive accuracy for petroleum engineering applications.
基金Supported by Major Instrument Project of National Natural Science Foundation of China(52327803)Major Project of National Natural Science Foundation of China(52192622).
文摘Based on the finite-discrete element method,a three-dimensional numerical model for axial impact rock breaking was established and validated.A computational method for energy conversion during impact rock breaking was proposed,and the effects of conical tooth forward rake angle,rock temperature,and impact velocity on rock breaking characteristics and energy transfer laws were analyzed.The results show that during single impact rock breaking with conical tooth bits,merely 7.52%to 12.51%of the energy is utilized for rock breaking,while a significant 57.26%to 78.10%is dissipated as frictional loss.An insufficient forward rake angle increases tooth penetration depth and frictional loss,whereas an excessive forward rake angle reduces penetration capability,causing bit rebound and greater energy absorption by the drill rod.Thus,an optimal forward rake angle exists.Regarding environmental factors,high temperatures significantly enhance impact-induced rock breaking.Thermal damage from high temperatures reduces rock strength and inhibits its energy absorption.Finally,higher impact velocities intensify rock damage,yet excessively high velocities increase frictional loss and reduce the proportion of energy absorbed by the rock,thereby failing to substantially improve rock breaking efficiency.An optimal impact velocity exists.
