Proceedings of the 2018 3rd International Conference on Control, Automation and Artificial Intelligence (CAAI 2018)

Characterization of Storage Energy for Rocks Based on Acoustic Wave Velocity Measurement

Authors
Chunde Ma, Chunzhi Guo, Yanan Zhou, Zelin Liu, Shan Long
Corresponding Author
Chunde Ma
Available Online August 2018.
DOI
https://doi.org/10.2991/caai-18.2018.43How to use a DOI?
Keywords
unloading wave velocity; elastic energy; linear model; composite exponential model; quantitative characterization
Abstract

To quantitatively characterize the stored energy in the rock. In the elastic range, the fluctuation characteristics and energy of marbles, granites, and red sandstones subjected to different stresses were studied, and the variation laws of wave velocity-stress, stress-energy of three types of rocks were analyzed and compared, and studied the feasibility of using the bridge of the longitudinal wave speed to characterize energy. The results show that after the three kinds of rocks are repeatedly loaded to 70% of their uniaxial compressive strength, 1) the longitudinal wave velocity and stress of the three rocks meet the established linear model. Comparing the fitted initial wave speed with the measured wave speed, the accuracy of red sandstone is lower than that of marble and granite; 2) The stress and energy are in agreement with the established composite exponential model, and the red sandstone has higher dissipation energy than marble and granite. 3) Through the model established by the unloaded wave velocity-stress and stress-elasticity, a relation model between the unloaded wave velocity and the elasticity is obtained, indicating the feasibility of using the wave velocity to characterize the energy. Based on this, a more feasible method of testing the quantitatively characterization of wave velocity for rock energy storage in the laboratory is proposed, and the test results also show that hard rock is more suitable than soft rock to quantify the stored energy in this way.

Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2018 3rd International Conference on Control, Automation and Artificial Intelligence (CAAI 2018)
Series
Atlantis Highlights in Intelligent Systems
Publication Date
August 2018
ISBN
978-94-6252-595-5
ISSN
2589-4919
DOI
https://doi.org/10.2991/caai-18.2018.43How to use a DOI?
Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Chunde Ma
AU  - Chunzhi Guo
AU  - Yanan Zhou
AU  - Zelin Liu
AU  - Shan Long
PY  - 2018/08
DA  - 2018/08
TI  - Characterization of Storage Energy for Rocks Based on Acoustic Wave Velocity Measurement
BT  - Proceedings of the 2018 3rd International Conference on Control, Automation and Artificial Intelligence (CAAI 2018)
PB  - Atlantis Press
SP  - 181
EP  - 185
SN  - 2589-4919
UR  - https://doi.org/10.2991/caai-18.2018.43
DO  - https://doi.org/10.2991/caai-18.2018.43
ID  - Ma2018/08
ER  -