A Comprehensive Prediction Model of Rock Strength and Its Application on Classifying the Rock During the Drilling

Lu Yang; Yinan Guo; Cancan Liu

doi:doi:10.11648/j.aas.20200503.15

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A Comprehensive Prediction Model of Rock Strength and Its Application on Classifying the Rock During the Drilling

Lu Yang, Yinan Guo, Cancan Liu

Published in Advances in Applied Sciences (Volume 5, Issue 3)

Received: 10 September 2020 Accepted: 21 September 2020 Published: 29 September 2020

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Abstract

Geological data plays an indispensable role in mining coal safely and efficiently. Traditional rock core method not only have some defects of high labor intensity, high cost and slow speed, but also difficultly got the rock of the weak interlayer. Based on this, parameter-based identification method of the rock characteristics during the drilling operation is a hot research topic. In this paper, a comprehensive prediction model was established to predict the rock Uniaxial Compressive Strength (UCS). Besides, the prediction results of the comprehensive prediction method, multiple linear regression model, and Mechanical Specific Energy (MSE) model were compared. Furthermore, the K-means clustering method is used to classify the rock formation based on the measured drilling parameters. The result indicates that torque work is significantly correlated with the UCS of rock. The comprehensive method has the best prediction result, and the prediction error of rock's UCS is within 5MPa. The prediction results of rock classification are different from the actual results, but from the perspective of rock strength, this classification method is better. The rapid identification method of rock formation based on MWD provides a reference for the roadway support scheme and parameter design, and is an important part of the intelligent development of coal mines.

Published in	Advances in Applied Sciences (Volume 5, Issue 3)
DOI	10.11648/j.aas.20200503.15
Page(s)	82-87
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2020. Published by Science Publishing Group

Keywords

Measurement While Drilling, Parameters While Drilling, Rock Classification, Support Parameter, Uniaxial Compressive Strength

References

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APA Style

Lu Yang, Yinan Guo, Cancan Liu. (2020). A Comprehensive Prediction Model of Rock Strength and Its Application on Classifying the Rock During the Drilling. Advances in Applied Sciences, 5(3), 82-87. https://doi.org/10.11648/j.aas.20200503.15

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ACS Style

Lu Yang; Yinan Guo; Cancan Liu. A Comprehensive Prediction Model of Rock Strength and Its Application on Classifying the Rock During the Drilling. Adv. Appl. Sci. 2020, 5(3), 82-87. doi: 10.11648/j.aas.20200503.15

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AMA Style

Lu Yang, Yinan Guo, Cancan Liu. A Comprehensive Prediction Model of Rock Strength and Its Application on Classifying the Rock During the Drilling. Adv Appl Sci. 2020;5(3):82-87. doi: 10.11648/j.aas.20200503.15

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@article{10.11648/j.aas.20200503.15,
  author = {Lu Yang and Yinan Guo and Cancan Liu},
  title = {A Comprehensive Prediction Model of Rock Strength and Its Application on Classifying the Rock During the Drilling},
  journal = {Advances in Applied Sciences},
  volume = {5},
  number = {3},
  pages = {82-87},
  doi = {10.11648/j.aas.20200503.15},
  url = {https://doi.org/10.11648/j.aas.20200503.15},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.aas.20200503.15},
  abstract = {Geological data plays an indispensable role in mining coal safely and efficiently. Traditional rock core method not only have some defects of high labor intensity, high cost and slow speed, but also difficultly got the rock of the weak interlayer. Based on this, parameter-based identification method of the rock characteristics during the drilling operation is a hot research topic. In this paper, a comprehensive prediction model was established to predict the rock Uniaxial Compressive Strength (UCS). Besides, the prediction results of the comprehensive prediction method, multiple linear regression model, and Mechanical Specific Energy (MSE) model were compared. Furthermore, the K-means clustering method is used to classify the rock formation based on the measured drilling parameters. The result indicates that torque work is significantly correlated with the UCS of rock. The comprehensive method has the best prediction result, and the prediction error of rock's UCS is within 5MPa. The prediction results of rock classification are different from the actual results, but from the perspective of rock strength, this classification method is better. The rapid identification method of rock formation based on MWD provides a reference for the roadway support scheme and parameter design, and is an important part of the intelligent development of coal mines.},
 year = {2020}
}

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TY - JOUR
T1 - A Comprehensive Prediction Model of Rock Strength and Its Application on Classifying the Rock During the Drilling
AU - Lu Yang
AU - Yinan Guo
AU - Cancan Liu
Y1 - 2020/09/29
PY - 2020
N1 - https://doi.org/10.11648/j.aas.20200503.15
DO - 10.11648/j.aas.20200503.15
T2 - Advances in Applied Sciences
JF - Advances in Applied Sciences
JO - Advances in Applied Sciences
SP - 82
EP - 87
PB - Science Publishing Group
SN - 2575-1514
UR - https://doi.org/10.11648/j.aas.20200503.15
AB - Geological data plays an indispensable role in mining coal safely and efficiently. Traditional rock core method not only have some defects of high labor intensity, high cost and slow speed, but also difficultly got the rock of the weak interlayer. Based on this, parameter-based identification method of the rock characteristics during the drilling operation is a hot research topic. In this paper, a comprehensive prediction model was established to predict the rock Uniaxial Compressive Strength (UCS). Besides, the prediction results of the comprehensive prediction method, multiple linear regression model, and Mechanical Specific Energy (MSE) model were compared. Furthermore, the K-means clustering method is used to classify the rock formation based on the measured drilling parameters. The result indicates that torque work is significantly correlated with the UCS of rock. The comprehensive method has the best prediction result, and the prediction error of rock's UCS is within 5MPa. The prediction results of rock classification are different from the actual results, but from the perspective of rock strength, this classification method is better. The rapid identification method of rock formation based on MWD provides a reference for the roadway support scheme and parameter design, and is an important part of the intelligent development of coal mines.
VL - 5
IS - 3
ER -

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Author Information

Lu Yang

School of information and Control Engineering, China University of Mining and Technology, Xuzhou, China
Yinan Guo

School of information and Control Engineering, China University of Mining and Technology, Xuzhou, China
Cancan Liu

School of Mines, Key Laboratory of Deep Coal Resource Mining, Ministry of Education of China, China University of Mining and Technology, Xuzhou, China

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Plain Text BibTeX RIS

APA Style

Lu Yang, Yinan Guo, Cancan Liu. (2020). A Comprehensive Prediction Model of Rock Strength and Its Application on Classifying the Rock During the Drilling. Advances in Applied Sciences, 5(3), 82-87. https://doi.org/10.11648/j.aas.20200503.15

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ACS Style

Lu Yang; Yinan Guo; Cancan Liu. A Comprehensive Prediction Model of Rock Strength and Its Application on Classifying the Rock During the Drilling. Adv. Appl. Sci. 2020, 5(3), 82-87. doi: 10.11648/j.aas.20200503.15

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AMA Style

Lu Yang, Yinan Guo, Cancan Liu. A Comprehensive Prediction Model of Rock Strength and Its Application on Classifying the Rock During the Drilling. Adv Appl Sci. 2020;5(3):82-87. doi: 10.11648/j.aas.20200503.15

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@article{10.11648/j.aas.20200503.15,
  author = {Lu Yang and Yinan Guo and Cancan Liu},
  title = {A Comprehensive Prediction Model of Rock Strength and Its Application on Classifying the Rock During the Drilling},
  journal = {Advances in Applied Sciences},
  volume = {5},
  number = {3},
  pages = {82-87},
  doi = {10.11648/j.aas.20200503.15},
  url = {https://doi.org/10.11648/j.aas.20200503.15},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.aas.20200503.15},
  abstract = {Geological data plays an indispensable role in mining coal safely and efficiently. Traditional rock core method not only have some defects of high labor intensity, high cost and slow speed, but also difficultly got the rock of the weak interlayer. Based on this, parameter-based identification method of the rock characteristics during the drilling operation is a hot research topic. In this paper, a comprehensive prediction model was established to predict the rock Uniaxial Compressive Strength (UCS). Besides, the prediction results of the comprehensive prediction method, multiple linear regression model, and Mechanical Specific Energy (MSE) model were compared. Furthermore, the K-means clustering method is used to classify the rock formation based on the measured drilling parameters. The result indicates that torque work is significantly correlated with the UCS of rock. The comprehensive method has the best prediction result, and the prediction error of rock's UCS is within 5MPa. The prediction results of rock classification are different from the actual results, but from the perspective of rock strength, this classification method is better. The rapid identification method of rock formation based on MWD provides a reference for the roadway support scheme and parameter design, and is an important part of the intelligent development of coal mines.},
 year = {2020}
}

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