the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 29 Apr 2024
Correlation between seismic activity and acoustic emission on the basis of in-situ monitoring
Abstract. Since April 2023 an in-situ experimental campaign has started at a granite underground tunnel, which is a dedicated monitoring platform located in Southeast China. Acoustic Emission (AE) signals and seismic sequences were simultaneously recorded by installing the AE device together with the seismometer, in order to investigate, among other parameters, the b-value and the natural-time variance, κ1, of AE time series. In addition, AE and related temporal correlation with the incoming seismic events are analyzed using an appropriate multi-modal statistical analysis. The results show that AE has a strong correlation with seismic swarms in surrounding areas. The changing trend of AE temporal distribution occurs before that of the earthquake and regularly anticipates the seismic major event by approximately 17 hours. The AE bursts indicate that an earthquake is approaching. The dense clusters of AE are closely related to two major earthquakes with Richter magnitudes equal to 3.2 and 2.4. Approaching the earthquake occurrence, the b-value shows a downward trend, reaching its minimum value prior to the earthquake, whereas the natural-time variance κ1 rapidly decreases from 0.07 to a minimum value close to zero. κ1 occurs earlier than the minimum b-value and the AE bursts. Therefore, trends of the b-value and the natural-time variance derived from the AE time series can be used as effective earthquake precursors. It is also evident that there is widespread micro-seismic activity in the earthquake preparation zone before the earthquake occurrence. The micro-seismic activity represents the origin of microcracks in the nearby ground surface, resulting in the AE bursts. The results of this paper provide new experimental evidence for the application of fracto-emissions as seismic precursors.
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The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
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Preprint
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The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
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Journal article(s) based on this preprint
Interactive discussion
Status: closed
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RC1: 'Comment on egusphere-2024-688', Anonymous Referee #1, 15 May 2024
In this study, an in-situ experimental campaign was conducted on a granite underground tunnel located in Southeast China. The objective was to analyze precursor parameters employed on AE time series and its relationship with seismic events recorded. The AE and its temporal correlation to the incoming seismic events were analyzed by considering the multi-modal statistical analysis, b-value, and the natural-time variance. The research topic is important from the point of view of phase transition phenomena and mining engineering. However, some points should be improved.
It is recommended that the present manuscript be accepted following the implementation of significant revisions. Some general observations to improve the manuscript clarity and quality are listed:
(1) Figure 2 is similar to the one presented in [x1], therefore, it is recommended to clarify that this figure is modified or redrawn to avoid copyright issues.
[x1] https://doi.org/10.1016/j.engfracmech.2016.01.013
(2) Some sentences can be added about the recent application of natural time on AE time series in order to identify the imminent failure of materials and structures. The review and comments should cover more new studies, such as those presented in [x2-x5], but not limited to these.
[x2] https://doi.org/10.1016/j.physa.2019.123831
[x3] https://doi.org/10.3390/app12083918
[x4] https://doi.org/10.3390/app12041980
[x5] https://doi.org/10.3390/app13106261
(3) In order to clarify the article, please provide more details on how "the impact of environmental ultrasonic noise, such as that from traffic, human activities and wind" has been eliminated.
(4) Please provide the criteria used to identify the optimal Gaussian fit in the multimodal analysis and the parameters of the Gaussian fit used to plot Figure 12. This information is relevant for other researchers wishing to apply a similar approach.
(5) Please clarify the methodology employed to calculate the b-value. Was a moving event window employed, or was a time window considered?
(6) It is known that several parameters can be applied to the energy term (P_K) in the analysis of natural time, such as amplitude, rise angle and AE energy (see, for example, Refs [x2-x5]). Which parameter was used by the authors? Please clarify.
(7) Why is there no critical time for EQ.2 in the natural time analysis? Even if the natural time parameters do not converge to EQ.2, a future study can be proposed for this.
According to what said above, the reviewer's opinion is that the manuscript can be accepted for publication after the described major revisions.
Citation: https://doi.org/10.5194/egusphere-2024-688-RC1 - AC1: 'Reply on RC1', Zihan Jiang, 23 Jul 2024
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RC2: 'Comment on egusphere-2024-688', Anonymous Referee #2, 22 May 2024
In their submitted manuscript, the authors addressed the very interesting issue of earthquake precursors, in the context of simultaneously recording of the Acoustic Emission (AE) activity and seismic activity, over a short period of time (35 days) in a case study area, located in southern China.
However, the simultaneous monitoring of AE and seismic activity has been reported in the past by one of the authors, namely A. Carpinteri and his coworkers, in a different studied area (see Refs 1.2 and 4) with a quite similar analysis, based on multi-modal statistical analysis (Gaussian fittings of AE rate). Noteworthy that, additional fracto-emission phenomena, such as EM radiation and neutron emission had been considered in those cases (Ref. 1). In that sense, the present work, in my opinion, does not contribute any additional knowledge and innovation to the important subject of earthquake precursors, such as the physical mechanism of AE preceding the seismic activity, and/or an advanced data analysis method. In the latter case, the b-value and the natural time analyses that carried out in AE data are quite common methods in the literature that may “predict” the occurrence of critical states in complex systems, such as earthquake and AE series (see for example related papers from Vallianatos and his coworkers, Triantis and his coworkers, etc).
Some important issues that the authors should consider are the following:
1/ Figures 1, 2 and 3 have been reported exactly the same in the authors’ previous works, i.e., in Refs 1, 2 and 4.
2/ The monitoring period is quite short, with only 2 major earthquake events. It should be expanded further to include more ΕQ events and become feasible the b-value and natural time analysis, in both datasets, i.e. AE data and the regional seismic catalogue. The latter correlation would be very important.
3/ A set of 8 AE sensors are used to monitor AE activity but all of them are located at the same position, next to each other. What is the point of using all these AE sensors? It would be meaningful to locate them at different sites of the so called “preparation zone” and not at the same point, just to increase the recorded AE rate.
4/ The authors refer to AE events, but how they can be sure that each recorded hit in the 8 channels corresponds to a different generated micro-crack? With the specific arrangement of the 8 sensors (refer to Fig. 5), I believe that source location is not possible, so the recording AE activity is actually the hit rate of all channels. This misunderstanding need to be clarified.
5/ Regarding AE data, only the hit rate is considered and no other useful information is provided. It would be important to include plots of representative AE waveforms and their frequency content, the time evolution of various hit-based AE parameters such energy, duration, average frequency, etc, and not only the hit rate. Actually, the energy rate could be considered as a more reliable AE parameter that the hit rate.
6/ The presentation of the results should be more concise but also more informative. For example, Fig. 9 does not add any additional information and should be omitted, while the cumulative distribution would be better to be included in Fig. 8 as an additional curve. Additionally, Figures 11, 12 and 13 actually present the same information and should be incorporated in a single figure.
7/ Some “technical” issues about b-value and natural time analysis should be included, for example, the time window and overlapping that was used, etc. Furthermore, natural time analysis should be carried out also for the other main event, and generally, for all major events when a broader period will beconsidered.
I believe that the manuscript should be thoroughly revised to overcome the above limitations and weaknesses and resubmitted for consideration.
Citation: https://doi.org/10.5194/egusphere-2024-688-RC2 - AC2: 'Reply on RC2', Zihan Jiang, 23 Jul 2024
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2024-688', Anonymous Referee #1, 15 May 2024
In this study, an in-situ experimental campaign was conducted on a granite underground tunnel located in Southeast China. The objective was to analyze precursor parameters employed on AE time series and its relationship with seismic events recorded. The AE and its temporal correlation to the incoming seismic events were analyzed by considering the multi-modal statistical analysis, b-value, and the natural-time variance. The research topic is important from the point of view of phase transition phenomena and mining engineering. However, some points should be improved.
It is recommended that the present manuscript be accepted following the implementation of significant revisions. Some general observations to improve the manuscript clarity and quality are listed:
(1) Figure 2 is similar to the one presented in [x1], therefore, it is recommended to clarify that this figure is modified or redrawn to avoid copyright issues.
[x1] https://doi.org/10.1016/j.engfracmech.2016.01.013
(2) Some sentences can be added about the recent application of natural time on AE time series in order to identify the imminent failure of materials and structures. The review and comments should cover more new studies, such as those presented in [x2-x5], but not limited to these.
[x2] https://doi.org/10.1016/j.physa.2019.123831
[x3] https://doi.org/10.3390/app12083918
[x4] https://doi.org/10.3390/app12041980
[x5] https://doi.org/10.3390/app13106261
(3) In order to clarify the article, please provide more details on how "the impact of environmental ultrasonic noise, such as that from traffic, human activities and wind" has been eliminated.
(4) Please provide the criteria used to identify the optimal Gaussian fit in the multimodal analysis and the parameters of the Gaussian fit used to plot Figure 12. This information is relevant for other researchers wishing to apply a similar approach.
(5) Please clarify the methodology employed to calculate the b-value. Was a moving event window employed, or was a time window considered?
(6) It is known that several parameters can be applied to the energy term (P_K) in the analysis of natural time, such as amplitude, rise angle and AE energy (see, for example, Refs [x2-x5]). Which parameter was used by the authors? Please clarify.
(7) Why is there no critical time for EQ.2 in the natural time analysis? Even if the natural time parameters do not converge to EQ.2, a future study can be proposed for this.
According to what said above, the reviewer's opinion is that the manuscript can be accepted for publication after the described major revisions.
Citation: https://doi.org/10.5194/egusphere-2024-688-RC1 - AC1: 'Reply on RC1', Zihan Jiang, 23 Jul 2024
-
RC2: 'Comment on egusphere-2024-688', Anonymous Referee #2, 22 May 2024
In their submitted manuscript, the authors addressed the very interesting issue of earthquake precursors, in the context of simultaneously recording of the Acoustic Emission (AE) activity and seismic activity, over a short period of time (35 days) in a case study area, located in southern China.
However, the simultaneous monitoring of AE and seismic activity has been reported in the past by one of the authors, namely A. Carpinteri and his coworkers, in a different studied area (see Refs 1.2 and 4) with a quite similar analysis, based on multi-modal statistical analysis (Gaussian fittings of AE rate). Noteworthy that, additional fracto-emission phenomena, such as EM radiation and neutron emission had been considered in those cases (Ref. 1). In that sense, the present work, in my opinion, does not contribute any additional knowledge and innovation to the important subject of earthquake precursors, such as the physical mechanism of AE preceding the seismic activity, and/or an advanced data analysis method. In the latter case, the b-value and the natural time analyses that carried out in AE data are quite common methods in the literature that may “predict” the occurrence of critical states in complex systems, such as earthquake and AE series (see for example related papers from Vallianatos and his coworkers, Triantis and his coworkers, etc).
Some important issues that the authors should consider are the following:
1/ Figures 1, 2 and 3 have been reported exactly the same in the authors’ previous works, i.e., in Refs 1, 2 and 4.
2/ The monitoring period is quite short, with only 2 major earthquake events. It should be expanded further to include more ΕQ events and become feasible the b-value and natural time analysis, in both datasets, i.e. AE data and the regional seismic catalogue. The latter correlation would be very important.
3/ A set of 8 AE sensors are used to monitor AE activity but all of them are located at the same position, next to each other. What is the point of using all these AE sensors? It would be meaningful to locate them at different sites of the so called “preparation zone” and not at the same point, just to increase the recorded AE rate.
4/ The authors refer to AE events, but how they can be sure that each recorded hit in the 8 channels corresponds to a different generated micro-crack? With the specific arrangement of the 8 sensors (refer to Fig. 5), I believe that source location is not possible, so the recording AE activity is actually the hit rate of all channels. This misunderstanding need to be clarified.
5/ Regarding AE data, only the hit rate is considered and no other useful information is provided. It would be important to include plots of representative AE waveforms and their frequency content, the time evolution of various hit-based AE parameters such energy, duration, average frequency, etc, and not only the hit rate. Actually, the energy rate could be considered as a more reliable AE parameter that the hit rate.
6/ The presentation of the results should be more concise but also more informative. For example, Fig. 9 does not add any additional information and should be omitted, while the cumulative distribution would be better to be included in Fig. 8 as an additional curve. Additionally, Figures 11, 12 and 13 actually present the same information and should be incorporated in a single figure.
7/ Some “technical” issues about b-value and natural time analysis should be included, for example, the time window and overlapping that was used, etc. Furthermore, natural time analysis should be carried out also for the other main event, and generally, for all major events when a broader period will beconsidered.
I believe that the manuscript should be thoroughly revised to overcome the above limitations and weaknesses and resubmitted for consideration.
Citation: https://doi.org/10.5194/egusphere-2024-688-RC2 - AC2: 'Reply on RC2', Zihan Jiang, 23 Jul 2024
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Zhiwen Zhu
Zihan Jiang
Federico Accornero
Alberto Carpinteri
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
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