The information extracted from monitoring of rotary blasthole drills helps to optimize the overall mining operation. Rock hardness, drillability, blastability and specific energy of drilling are examples of parameters...The information extracted from monitoring of rotary blasthole drills helps to optimize the overall mining operation. Rock hardness, drillability, blastability and specific energy of drilling are examples of parameters that have been estimated in the past using measurement while drilling techniques. In order to be able to properly utilize measurement while drilling techniques, it is important to properly collect, analyze and interpret extracted data. This paper deals with processing of measurement while drilling data such as rate of penetration, rotary speed, rotary torque and pulldown force collected from rotary blasthole drills.Different methods are discussed to calculate a true rate of penetration which is the most important monitored drill variable for use in rock mass characterization. Then specific energy of drilling is defined and calculated based on electrical and mechanical inputs and the results are compared. The results show that specific energy of drilling can be estimated using the drill's primary drive systems' electrical responses with good accuracy when compared to values based on mechanical inputs.展开更多
In the electromagnetic wave measurement while drilling(EM MWD), the extra low frequency electromagnetic wave(ELF-EM) below 20Hz was usually chosen as the carrier because of its transmission characteristics in the form...In the electromagnetic wave measurement while drilling(EM MWD), the extra low frequency electromagnetic wave(ELF-EM) below 20Hz was usually chosen as the carrier because of its transmission characteristics in the formation. However, as the drilling depth increases, the electromagnetic wave signals received on the ground gradually weaken, becoming lower than a certain signal-to-noise ratio(SNR)and making it impossible to be decoded or transmitted.The attenuation of electromagnetic wave in the formation is definitely one of the causes, but what matters more is the influence of environment noise at the well site, especially the in-band interference noise and random noise. Targeting at the out-of-band noise, the bandpass filter, which is invalid to the in-band noise,can be used to eliminate the noise out of the carrier’s main band. To cope with the question, an algorithm based on the human-computer interaction detection(HCID) was proposed in this paper that improves the SNR of ELF-EM signals, with the effective transmission distance of EM MWD increased. In this paper,the validity of the proposed HCID algorithm was verified through communication processing performance simulation and field data comparison, thus providing a reference for engineers and technicians in this field.Theoretical analysis and experimental data verification show that the combined algorithm decodes effectively under the in-band interference noise of-80d B SNR and in-band random noise of-17d B SNR.展开更多
In view of the shortcomings of current intelligent drilling technology in drilling condition representation, sample collection, data processing and feature extraction, an intelligent identification method of safety ri...In view of the shortcomings of current intelligent drilling technology in drilling condition representation, sample collection, data processing and feature extraction, an intelligent identification method of safety risk while drilling was established. The correlation analysis method was used to determine correlation parameters indicating gas drilling safety risk. By collecting monitoring data in the safety risk period of more than 20 wells, a sample database of a variety of safety risks in gas drilling was established, and the number of samples was expanded by using the method of few-shot learning. According to the forms of gas drilling monitoring data samples, a two-layer convolution neural network architecture was designed, and multiple convolution cores of different sizes and weights were set to realize the vertical and horizontal convolution computations of samples to extract and learn the variation law and correlation characteristics of multiple monitoring parameters. Finally, based on the training results of neural network, samples of different kinds of safety risks were selected to enhance the recognition accuracy. Compared with the traditional BP(error back propagation) full-connected neural network architecture, this method can more deeply and effectively identify safety risk characteristics in gas drilling, and thus identify and predict risks in advance, which is conducive to avoid and quickly solve safety risks while drilling. Field application has proved that this method has an identification accuracy of various safety risks while drilling in the process of gas drilling of about 90% and is practical.展开更多
A numerical model and transmission characteristic analysis of DPSK （differential phase shift keying） pressure signals in mud channels is introduced. With the control logic analysis of the rotary valve mud telemetry,...A numerical model and transmission characteristic analysis of DPSK （differential phase shift keying） pressure signals in mud channels is introduced. With the control logic analysis of the rotary valve mud telemetry, a logical control signal is built from a Gate function sequence according to the binary symbols of transmitted data and a phase-shift function is obtained by integrating the logical control signal. A mathematical model of the DPSK pressure signal is built based on principles of communications by modulating carrier phase with the phase-shift function and a numerical simulation of the pressure wave is implemented with the mathematical model by MATLAB programming. Considering drillpipe pressure and drilling fluid temperature profile along drillpipes, the drillpipe of a vertical well is divided into a number of sections. With water-based drilling fluids, the impacts of travel distance, carrier frequency, drillpipe size, and drilling fluids on the signal transmission were studied by signal transmission characteristic analysis for all the sections. Numerical calculation results indicate that the influences of the viscosity of drilling fluids and volume fraction of gas in drilling fluids on the DPSK signal transmission are more notable than the others and the signal will distort in waveform with differential attenuations of the signal frequent component.展开更多
Measurement while drilling systems are becoming an important part of excavation operations for rock characterization and ground support design that require reliable information on rock strength and location ＆ frequen...Measurement while drilling systems are becoming an important part of excavation operations for rock characterization and ground support design that require reliable information on rock strength and location ＆ frequency of joints or voids. This paper focuses on improving rock characterization algorithms for instrumented roof-boRer systems. For this purpose, an improved void detection algorithm is proposed, where the underlying theory is built upon the concept of mean change detection based on the feed pressure signals. In addition, the application of acoustic sensing for void detection is examined and it is shown that the variance of the filtered acoustic signal is correlated to the strength of the material being drilled. The proposed algorithm has been validated on the data collected from full-scale drilling tests in various concrete and rock samples at the J. H. Fletcher facility.展开更多
This article presents a novel approach to integrate a throughput prediction model for the ball mill into short-term stochastic production scheduling in mining complexes.The datasets for the throughput prediction model...This article presents a novel approach to integrate a throughput prediction model for the ball mill into short-term stochastic production scheduling in mining complexes.The datasets for the throughput prediction model include penetration rates from blast hole drilling(measurement while drilling),geological domains,material types,rock density,and throughput rates of the operating mill,offering an accessible and cost-effective method compared to other geometallurgical programs.First,the comminution behavior of the orebody was geostatistically simulated by building additive hardness proportions from penetration rates.A regression model was constructed to predict throughput rates as a function of blended rock properties,which are informed by a material tracking approach in the mining complex.Finally,the throughput prediction model was integrated into a stochastic optimization model for short-term production scheduling.This way,common shortfalls of existing geometallurgical throughput prediction models,that typically ignore the non-additive nature of hardness and are not designed to interact with mine production scheduling,are overcome.A case study at the Tropicana Mining Complex shows that throughput can be predicted with an error less than 30 t/h and a correlation coefficient of up to 0.8.By integrating the prediction model and new stochastic components into optimization,the production schedule achieves weekly planned production reliably because scheduled materials match with the predicted performance of the mill.Comparisons to optimization using conventional mill tonnage constraints reveal that expected production shortfalls of up to 7%per period can be mitigated this way.展开更多
文摘The information extracted from monitoring of rotary blasthole drills helps to optimize the overall mining operation. Rock hardness, drillability, blastability and specific energy of drilling are examples of parameters that have been estimated in the past using measurement while drilling techniques. In order to be able to properly utilize measurement while drilling techniques, it is important to properly collect, analyze and interpret extracted data. This paper deals with processing of measurement while drilling data such as rate of penetration, rotary speed, rotary torque and pulldown force collected from rotary blasthole drills.Different methods are discussed to calculate a true rate of penetration which is the most important monitored drill variable for use in rock mass characterization. Then specific energy of drilling is defined and calculated based on electrical and mechanical inputs and the results are compared. The results show that specific energy of drilling can be estimated using the drill's primary drive systems' electrical responses with good accuracy when compared to values based on mechanical inputs.
基金supported by National Natural Science Foundation of China(No.61771366)StableSupport Scientific Project of China Research Institute of Radiowave Propagation(Grant No.A132201068 and No.A132107W08)。
文摘In the electromagnetic wave measurement while drilling(EM MWD), the extra low frequency electromagnetic wave(ELF-EM) below 20Hz was usually chosen as the carrier because of its transmission characteristics in the formation. However, as the drilling depth increases, the electromagnetic wave signals received on the ground gradually weaken, becoming lower than a certain signal-to-noise ratio(SNR)and making it impossible to be decoded or transmitted.The attenuation of electromagnetic wave in the formation is definitely one of the causes, but what matters more is the influence of environment noise at the well site, especially the in-band interference noise and random noise. Targeting at the out-of-band noise, the bandpass filter, which is invalid to the in-band noise,can be used to eliminate the noise out of the carrier’s main band. To cope with the question, an algorithm based on the human-computer interaction detection(HCID) was proposed in this paper that improves the SNR of ELF-EM signals, with the effective transmission distance of EM MWD increased. In this paper,the validity of the proposed HCID algorithm was verified through communication processing performance simulation and field data comparison, thus providing a reference for engineers and technicians in this field.Theoretical analysis and experimental data verification show that the combined algorithm decodes effectively under the in-band interference noise of-80d B SNR and in-band random noise of-17d B SNR.
基金Supported by National Key R&D Plan (2019YFA0708303)Key R&D Projects of Sichuan Science and Technology Plan (2021YFG0318)Key Projects of NSFC (61731016)。
文摘In view of the shortcomings of current intelligent drilling technology in drilling condition representation, sample collection, data processing and feature extraction, an intelligent identification method of safety risk while drilling was established. The correlation analysis method was used to determine correlation parameters indicating gas drilling safety risk. By collecting monitoring data in the safety risk period of more than 20 wells, a sample database of a variety of safety risks in gas drilling was established, and the number of samples was expanded by using the method of few-shot learning. According to the forms of gas drilling monitoring data samples, a two-layer convolution neural network architecture was designed, and multiple convolution cores of different sizes and weights were set to realize the vertical and horizontal convolution computations of samples to extract and learn the variation law and correlation characteristics of multiple monitoring parameters. Finally, based on the training results of neural network, samples of different kinds of safety risks were selected to enhance the recognition accuracy. Compared with the traditional BP(error back propagation) full-connected neural network architecture, this method can more deeply and effectively identify safety risk characteristics in gas drilling, and thus identify and predict risks in advance, which is conducive to avoid and quickly solve safety risks while drilling. Field application has proved that this method has an identification accuracy of various safety risks while drilling in the process of gas drilling of about 90% and is practical.
基金supported by High Technology Research and Development Program of China(No.2006AA06A101).
文摘A numerical model and transmission characteristic analysis of DPSK （differential phase shift keying） pressure signals in mud channels is introduced. With the control logic analysis of the rotary valve mud telemetry, a logical control signal is built from a Gate function sequence according to the binary symbols of transmitted data and a phase-shift function is obtained by integrating the logical control signal. A mathematical model of the DPSK pressure signal is built based on principles of communications by modulating carrier phase with the phase-shift function and a numerical simulation of the pressure wave is implemented with the mathematical model by MATLAB programming. Considering drillpipe pressure and drilling fluid temperature profile along drillpipes, the drillpipe of a vertical well is divided into a number of sections. With water-based drilling fluids, the impacts of travel distance, carrier frequency, drillpipe size, and drilling fluids on the signal transmission were studied by signal transmission characteristic analysis for all the sections. Numerical calculation results indicate that the influences of the viscosity of drilling fluids and volume fraction of gas in drilling fluids on the DPSK signal transmission are more notable than the others and the signal will distort in waveform with differential attenuations of the signal frequent component.
基金funded by National Institute of Occupational Safety and Health (NIOSH) ground control group under the contract No. 211-2011-41138
文摘Measurement while drilling systems are becoming an important part of excavation operations for rock characterization and ground support design that require reliable information on rock strength and location ＆ frequency of joints or voids. This paper focuses on improving rock characterization algorithms for instrumented roof-boRer systems. For this purpose, an improved void detection algorithm is proposed, where the underlying theory is built upon the concept of mean change detection based on the feed pressure signals. In addition, the application of acoustic sensing for void detection is examined and it is shown that the variance of the filtered acoustic signal is correlated to the strength of the material being drilled. The proposed algorithm has been validated on the data collected from full-scale drilling tests in various concrete and rock samples at the J. H. Fletcher facility.
基金the National Sciences and Engineering Research Council of Canada(NSERC)under CDR Grant CRDPJ 500414-16NSERC Discovery Grant 239019the COSMO mining industry consortium(AngloGold Ashanti,BHP,De Beers,AngloAmerican,IAMGOLD,Kinross Gold,Newmont Mining,and Vale).
文摘This article presents a novel approach to integrate a throughput prediction model for the ball mill into short-term stochastic production scheduling in mining complexes.The datasets for the throughput prediction model include penetration rates from blast hole drilling(measurement while drilling),geological domains,material types,rock density,and throughput rates of the operating mill,offering an accessible and cost-effective method compared to other geometallurgical programs.First,the comminution behavior of the orebody was geostatistically simulated by building additive hardness proportions from penetration rates.A regression model was constructed to predict throughput rates as a function of blended rock properties,which are informed by a material tracking approach in the mining complex.Finally,the throughput prediction model was integrated into a stochastic optimization model for short-term production scheduling.This way,common shortfalls of existing geometallurgical throughput prediction models,that typically ignore the non-additive nature of hardness and are not designed to interact with mine production scheduling,are overcome.A case study at the Tropicana Mining Complex shows that throughput can be predicted with an error less than 30 t/h and a correlation coefficient of up to 0.8.By integrating the prediction model and new stochastic components into optimization,the production schedule achieves weekly planned production reliably because scheduled materials match with the predicted performance of the mill.Comparisons to optimization using conventional mill tonnage constraints reveal that expected production shortfalls of up to 7%per period can be mitigated this way.
