Next Article in Journal
Visual Enhancement Capsule Network for Aspect-based Multimodal Sentiment Analysis
Previous Article in Journal
Association between Body Mass Index and the Use of Digital Platforms to Record Food Intake: Cross-Sectional Analysis
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Applied Sciences
Volume 12
Issue 23
10.3390/app122312145
applsci-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Study of the Evolution Characteristics of Microseismic Events during the Excavation of Underground Caverns under High Geostress

by
Xin Lin
1,
Biao Li
1,*,
Peng Li
2,
Quanfu Ding
3 and
Mengting Huang
1
1
School of Geoscience and Technology, Southwest Petroleum University, Chengdu 610500, China
2
Sichuan Dadu River Shuangjiangkou Hydropower Development Co., Ltd., Maerkang 624099, China
3
State Key Laboratory of Hydraulics and Mountain River Engineering, College of Water Resource and Hydropower, Sichuan University, Chengdu 610065, China
*
Author to whom correspondence should be addressed.
Appl. Sci. 2022, 12(23), 12145; https://doi.org/10.3390/app122312145
Submission received: 10 November 2022 / Revised: 20 November 2022 / Accepted: 22 November 2022 / Published: 28 November 2022
Browse Figures
Versions Notes

Abstract

:
A microseismic (MS) monitoring system was established, and numerical modeling was performed using Fast Lagrangian Analysis of Continua in 3 Dimensions (FLAC3D) to examine the evolution characteristics of MS events during the excavation of underground caverns under high geostress. Specifically, the spatial and temporal damage characteristics of the rock mass, the dynamic relationship between the evolution of MS events, the site construction conditions, and the geological structures under high geostress were also analyzed. In addition, a three-dimensional numerical model of underground caverns was built to demonstrate the deformation characteristics of the rock mass. As a result, the characteristics of a large number of MS events, multiple concentration zones of MS events, and long periods of stress adjustment were discovered in underground caverns under high geostress. It was found that the primary cause of MS events was site blasting construction. In particular, the distribution of the MS events was strongly correlated with the location of the site blasting construction, and the frequency of the MS events was positively correlated with it. The structural plane is a discontinuous plane with very low or no tensile strength, and its presence also increased the number of MS events and raised the possibility of the surrounding rock becoming unstable. Moreover, the MS monitoring data agreed with the numerical modeling results, which can be useful in estimating damage to underground caverns under high geostress and predicting disasters.

1. Introduction

Southwest China is rich in hydropower resources, with the provinces of Sichuan and Yunnan and the Tibet Autonomous Region accounting for two-thirds of the total in China. They are concentrated in the basins of the Jinsha, Yalong, Dadu, Yarlung Zangbo, and Lancang rivers [1]. With the increasing demand for energy in China’s rapid economic development, numerous large hydropower projects are being built or will be built in Southwest China, such as the Wudongde hydropower station and the Baihetan hydropower station on the Jinsha river, the Lianghekou hydropower station and the Yangfanggou hydropower station on the Yalong river, and the Shuangjiangkou hydropower station and the Jinchuan hydropower station on the Dadu river. Large hydropower projects often include tunnel spillways and various tunnels, such as access tunnels, headrace tunnels, diversion tunnels, spillway tunnels, and tailrace tunnels. Generally, these hydraulic tunnels follow long routes, go through a variety of complex strata, are buried deeper, have larger excavation sections, and occasionally exhibit the multitunnel effect. As a result, instability problems, including rock deformation and rock bursts caused by tunnel excavation and unloading, are prominent, which represents a great challenge to tunnel construction safety.
Field monitoring is being applied more frequently in underground projects, which not only ensures the safety of a construction site to a certain extent but also provides the data basis for other methods, such as mechanical analysis, numerical modeling, and physical model tests [2]. It can also be used to demonstrate the safety of projects in many different ways and assess the stability of the surrounding rocks. Traditional monitoring tools (such as multipoint displacement meters and rock bolt stress meters) are mainly used to measure rock deformation and bolt stress, as they directly collect field data of changes in rock deformation and bolt stress, thus, playing an important role in the analysis and control of rock stability. Field remedies, however, are challenging to provide promptly since traditional monitoring tools frequently obtain monitoring results after the rock mass has already sustained damage or perhaps has become unstable [3]. In contrast, the data on MS events in advance, such as time, location, and strength, can be collected by MS monitoring before the rock becomes unstable or large deformations occur during geotechnical engineering. The stability of engineering rocks can be assessed. Therefore, it allows for a timely warning of large deformations or even instability of the surrounding rock and provides important technical support for engineering construction safety.
Currently, MS monitoring is widely used in western countries for studying and preventing dynamic disasters, particularly in mines [4,5,6], tunnels [7,8], exploitation of oil, gas, and geothermal energy [9,10,11], and underground storage [12]. Hassani et al. [5] located MS events at the Schlema-Alberoda uranium mine in Southwest Saxony, Germany, to study the nature of seismicity and the long-term role of mining-induced and triggered seismicity. Himanshu et al. [6] used MS data recorded during underground mine developments for 3D attenuation tomography, which can help to delineate the ore body using seismic waves and other measurement methods, such as gravity inversion and borehole sampling. Young and Collins [7] used MS monitoring techniques to determine the excavation disturbed zone (EDZ) of tunnels and set up engineering barriers to prevent fluid seepage through granite fractures in the tunnels. Lisjak et al. [11] employed MS monitoring techniques to assess the process of increasing oil and gas productions during hydraulic fracturing. Akono [12] examined the geochemical reactions caused by carbon dioxide in underground reservoirs and their possible impact on the mechanical properties of the reservoirs and MS events. China has only recently started researching and applying MS monitoring. In particular, the Mentougou mine was the first to employ MS monitoring in 1959 [13] to keep track of rock bursts. MS monitoring has been widely promoted and applied to assess the stability of the rock surrounding mines since mining areas now face a variety of safety issues as the mining industry develops [14,15,16,17]. For example, Tang Li-zhong et al. [14] applied MS monitoring in the Dongguashan mine and employed moment tensor theory to study the failure mechanism of the surrounding rock. Dou Lin-ming et al. [15] introduced MS monitoring in the Hujiahe coal mine in the Binchang mining area, Shaanxi, and proposed a comprehensive warning model for rock bursts based on the MS precursor indicator system. Southwest China has seen a recent increase in the construction of hydropower stations at various locations, aiming to support national development. The hydropower industry has steadily used MS monitoring as a new approach to ensure construction safety in light of the challenging geological conditions and frequent occurrences of various engineering and geological disasters. Feng Xia-ting et al. [18,19] applied MS monitoring at the Jinping-II hydropower station to study MS events, TBM boring, and the occurrence of rock bursts, as well as to predict the occurrence of rock bursts during TBM boring in deep tunnels. Tang Chun-an et al. [20] obtained source data from an MS monitoring system and applied the loading/unloading response ratio theory to predict the slope failure during water storage at the Dagangshan hydropower station. Xu Nu-wen and his team [21,22,23,24,25,26] introduced MS monitoring for underground caverns of the Houziyan hydropower station and the Shuangjiangkou hydropower station and carried out extensive research on the identification of damages to the surrounding rock, the assessment of the stability of the surrounding rock, and risk warning and prediction during the construction period. Zhao Jin-shuai et al. [27] used microseismic monitoring technology to obtain microrupture information of the rock mass and compared borehole imaging results to clarify the mechanical behavior mechanism of the rock mass, implying that the macroscopic deformation or failure characteristics of the surrounding rock are directly related to the evolution of microfractures.
Although the microseismic characteristics of individual high geostress environments are mentioned when domestic and foreign scholars study the microseismic monitoring of high geostress underground caverns, there are few articles that systematically summarize the microseismic characteristics of high geostress underground caverns. This paper outlines our research on the underground caverns of the Shuangjiangkou hydropower station on the Dadu river. Specifically, an MS monitoring system was constructed to monitor the excavation process of the underground caverns under high geostress. Additionally, the spatial and temporal evolution characteristics of the MS events were analyzed in the rock mass of the underground caverns that are subject to high geostress. The main damage areas of the underground caverns were delineated. The intrinsic connection between the MS activity of the underground caverns and the site conditions was explored. Moreover, a 3D numerical model of the underground caverns was created to reveal the deformation characteristics of the rock mass, and the results were compared with those obtained from the MS monitoring. Finally, the evolution characteristics of underground tunnel excavations are summarized to provide reference for similar works.

2. Project Overview

2.1. Project Background

The Shuangjiangkou hydropower station is one of the key projects for hydropower cascade development in the Dadu river basin. Its rock-filled dam reaches a maximum height of 314 m. The power station has an installed capacity of 2000 MW. The diversion and power generation structure on the left bank consists of an underground powerhouse system (including the main and auxiliary powerhouses, an erection bay, a main transformer chamber, and a tailrace surge chamber), an intake, a penstock, and two tailrace tunnels. The powerhouses, main transformer chamber, and tailrace surge chamber are arranged in parallel. The underground powerhouse system is located in the mountain from 400 m to 600 m on the left bank, and the size of the main and auxiliary powerhouses measures 215.7 × 28.3 × 68.3 m (length, width, and height), with the vault reaching 2269.47 m. The size of the main transformer chamber measures 158.26 × 19.40 × 27.19 m, with the vault reaching 2266.27 m, and the distance between the main powerhouse and the main transformer chamber is 67.15 m. The size of the tailrace surge chamber measures 100.00 × 20.00 × 76.5 m, and the distance between the tailrace surge chamber and the main transformer chamber is 60.0 m. Figure 1 shows the caverns in the diversion and power generation system on the left bank of the Shuangjiangkou hydropower station [28].

2.2. Geological Structure and Geostress

Studies on the SPD9 adit indicated that the rock mass in the plant area has great integrity, with no regional faults running through the project area of the underground powerhouse. They also showed that the dykes were formed locally and that the main structural planes are secondary minor faults, joints, and fissures, as shown in Table 1.
Stress concentration occurred in fresh to slightly weathered granite rich in biotite and K-feldspars in the plant area, which was indicated by the results from eight sets of geostress measurements carried out at depths of 115 m, 205 m, 301 m, 400 m, 470 m, 540 m, 570 m, and 640 m, as shown in Figure 2 [29]. The results show that the geostress in the rock mass of the plant on the left bank exhibits a zonal distribution. In particular, in the stress-lowering zone, geostress is released at depths of 0–45 m due to unloading. In the stress-rising zone at depths of 45–400 m, the maximum principal stress has a dip, indicating the addition of pressure from the dead load, and it tends to rise as the adit depth increases, reaching 37.8 MPa at 400 m. In the stress-stationary zone, the maximum principal stress varies between 16 MPa and 30 MPa at depths greater than 400 m, where the horizontal stress predominates with a slight dip. The plant is located in an area of depths greater than 400 m, with a dry compressive strength of 50.5 MPa. According to the stress classification section in the “Code for hydropower engineering geological investigation”, the underground powerhouse area is in a high-to-very high stress state since the strength–stress ratio ranges from 1.68 to 3.16. The criteria for classifying geostress are listed in Table 2.

3. Evolution Characteristics of MS Events during the Excavation of the Underground Powerhouse under High Geostress

3.1. Construction of the MS Monitoring System

MS events refer to rock fractures created by an overload or the growth of existing fractures. When fractures occur, the elastic waves are captured by sensors, and data, including the occurrence time, location, and strength, can be collected by sensors. The damage to the rocks can be well reflected by the MS data. The evolution of rock fractures is tracked by the MS monitoring in real time, and the technical support for assessing rock stability during the excavation of underground caverns is provided by the MS monitoring.
The studies are based on the Shuangjiangkou hydropower station. The Canadian ESG MS monitoring system was arranged in the underground powerhouse of the station, and its network topology is shown in Figure 3. Elastic waves released by MS events in the rock mass were captured by the preburied sensors and transmitted to the signal collector Paladin through a cable. The original waveform file, which includes rich fracture information, was transmitted to a computer equipped with a Hyperion system through an optical fiber. It was created and forwarded to the camp office via a wireless network. Then, the data were sent back to the data analysis center in Chengdu, where the signal was processed to locate microseismic events. The MS monitoring system was primarily intended to monitor the plant. Ten acceleration sensors (S1–S10 in Figure 3) with a single-sensor monitoring range of 150 m and a sensitivity of 30 V/g were deployed on the top floor of the drainage gallery. After the floors were excavated downward, some sensors were moved to the intermediate and bottom floors of the drainage gallery according to the construction progress. A single Paladin data acquisition substation can be connected to a maximum of six sensors. Therefore, two Paladin substations with synchronized times were used to connect the ten sensors. The positioning accuracy of the MS monitoring was closely related to the set wave velocity of the rock mass. According to the field blast and the positioning test, when the wave velocity is set at 5800 m/s, a minimum positioning error of 5.79 m may be attained. Other methods for performance and waveform analysis using the MS monitoring system can be found in some previous work, e.g., [28].

3.2. Temporal Distribution Characteristics of MS Events

The MS monitoring system was installed and formally put into operation on 19 July 2018. Figure 4 shows the temporal distribution of the MS events. In particular, 2881 valid MS events were collected as of 31 October 2020, and the incidence of the MS events was closely related to the construction conditions. From 19 July 2018 to 31 July 2019, bench I of the underground powerhouse was excavated. The natural state of the surrounding rock was destroyed, and a new free face was formed, which changed the stress state of the surrounding rock. Moreover, the surrounding rock saw a stress redistribution that resulted in the generation of MS events. Overall, the MS events occurred frequently, with an average of 9 per day and up to 19 in some localities. Specifically, the MS events were highly active during high-frequency blasting and construction from July to November 2018. In contrast, the MS events were inactive when the blasting and excavation activities of the underground powerhouse ceased from mid-January 2019 to late March 2019; however, there were still MS events, indicating that the surrounding rock experienced a long stress adjustment under high geostress. From August 2019 to 31 October 2020, bench II and part of bench III of the underground powerhouse were excavated. Due to the completion of bench I and the slow progress of blasting, construction, and excavation, the surrounding rock was less disturbed, and its internal stress was fully adjusted and released; thus, the MS event rate was low, with an average of five events per day.

3.3. Spatial Distribution Characteristics of MS Events

The spatial distribution of MS events from 19 July 2018 to 31 October 2020 is shown in Figure 5. The MS events are represented by spheres. The color and size of the spheres correspond to the moment magnitude and energy of the MS events, respectively. The MS events are mostly caused by high stress concentrations and large stress differences. The area where the MS events are concentrated usually has potential structural planes or has experienced unreasonable construction in its vicinity. According to Figure 5a, the MS events are mainly distributed in the powerhouse’s arch area and on the top of the mid-partition separating the powerhouse from the main transformer chamber. The main areas of damage are represented by zones I, II, and III in Figure 5b, where the MS events are concentrated. Zone I is located beneath the powerhouse between stakes 0 − 060.00 and 0 + 030.00. Zone II is located in the arch of the mid-partition, which separates the powerhouse from the main transformer chamber between stakes 0 + 030.00 and 0 + 070.00. Zone III is located between stakes 0 + 090.00 and 0 + 140.00. The result shows that multiple MS events are more likely to concentrate in underground caverns under high geostress, and it is noteworthy that zone II showed more MS events of high moment magnitude and significant energy. Analyses of the construction nodes indicate that the main transformer chamber was excavated for bench I while bench II of the powerhouse was being excavated. Many large blasting events occurred at this time, and the intensity of the construction and blasting was high. Therefore, the surrounding rock was disturbed and unloaded in both directions, resulting in MS events with large energy and high moment magnitude. Moreover, zone III had the greatest concentration of MS events. Analyses of the geological conditions show that this zone was near the SPD9-F1 secondary fault and lamprophyre dyke. The presence of structural planes caused more MS events to occur. The concentration zones of the MS events have a high risk of destabilization during the excavation of underground caverns. For example, on 17 May 2019, a rock collapse occurred in zone III between stakes 0 + 120.00 and 0 + 135.00 on the upstream spandrel of the main powerhouse. Site surveys revealed that a lamprophyre dyke was exposed at the site of the collapse [26].

3.4. Analysis of MS Evolutionary Responses to Construction Dynamics

The damage status of the rock mass and the changes in the stress–strain state of the surrounding rock can be characterized by the spatial distribution and temporal evolution of the MS events. Therefore, studies and analyses of the accumulation pattern and the migration and expansion trend of the MS events can not only reveal the disturbance on the surrounding rock from construction processes, such as excavation and support, but also allow qualitative assessments of the comprehensive effects of the geological structure, physico-geological functions, and geostress on the surrounding rock during the blasting, excavation, and construction processes. During the blasting and excavation of the powerhouse for bench I, the fresh state of the surrounding rock was destroyed, and the condition of the rock ahead of the tunneling was not fully investigated. Therefore, the excavation of this bench often receives more attention. This section describes the spatial and temporal concentrations and the migration characteristics of the MS events that occurred during intensive blasting from 19 July 2018 to 2 December 2018. Moreover, the response mechanism between the construction activities, the geological occurrence, and the occurrence of the MS events is provided.
The middle pilot tunnel in the main and auxiliary powerhouses of the Shuangjiangkou hydropower station was successfully excavated in June 2018. After two months of bolt-shotcrete support and other preliminary construction preparations, the rock stress was released, and the surrounding rock of the tunnel was stable after stress adjustments. Therefore, the excavation, blasting, and construction of the main and auxiliary powerhouses for bench I began on 23 August 2018. By 2 December, the upstream and downstream areas had each been dug to stakes 0 + 90 m and 0 + 130 m, respectively. The site construction is shown in Figure 6.
Figure 7 shows the spatial and temporal evolutions of the MS events from 19 July to 30 August 2018. In particular, the MS events were first concentrated near stake 0 − 50 m on the initial excavation face of the drainage gallery, as shown in Figure 7a. They appeared one after another with the advancement of the tunnel face along the powerhouse, with a small number of them distributed along the axis of the drainage gallery, as shown in Figure 7b. However, most of them showed a zonal distribution between the drainage gallery and the main and auxiliary powerhouses and an obvious shift from the drainage gallery to the area downstream of the erection bay, as shown in Figure 7c. The above law showed that the location of the MS events agreed well with that of the tunnel face of the site blasting and construction.
Figure 8 shows the spatial evolution of the MS events from 23 August to 16 November 2018. Specifically, a large number of MS events were concentrated from stakes 0 − 60 m to 0 m downstream of the erection bay. Most of them were distributed in the vault area, as shown in Figure 8a,b. The MS events that occurred from stakes 0 m to 70 m upstream and stakes 0 m to 0 + 125 m downstream of the powerhouse showed a dislocation distribution along the powerhouse axis, as shown in Figure 8c. The spatial and temporal distribution characteristics of the MS events induced by the excavation also agreed with the construction process. Analyses of the excavation show that the bench excavation was carried out for the middle pilot tunnel on both sides and that the distance between the tunnel face in the upstream area and that in the downstream area was approximately 30 m. The downstream area was excavated at the section from stakes 0 − 15 m to 0 − 5 m, and the excavation of the section from stakes 0 − 5 m to 0 + 128 m started after that from stakes 0 − 15 m to 0 − 60 m. The upstream area was excavated at the section from stakes 0 − 60 m to 0 − 50 m, and the excavation of the section from stakes 0 − 50 m to 0 + 70 m started after the tunnel face in the downstream area was advanced to stake 0 m. The excavation sequence of the sidewall is shown in Figure 9. In summary, the dislocation distribution of the MS events was closely related to the bench excavation.
When the downstream side of the plant began to expand, to accelerate the construction progress, drilling and blasting on the tunnel face were carried out twice a day, with an average daily footage of 5 m. The frequency of the blasting excavation was closely related to the damage to the surrounding rock. The higher the blasting frequency, the greater the degree of construction disturbance. Moreover, the development of microquakes inside the rock mass will be accelerated by the high blasting frequency, which worsens the fracture and damage and, ultimately, increases the risk of deformation and destabilization. In response to the early warning signals for the concentration of MS events, the constructor adjusted the construction plan in mid-September by reducing the frequency of the blasting to once a day and controlling the average daily footage within 3 m. After the adjustment of the construction plan, the number of daily MS events was maintained mainly between zero and five from 15 September to 31 October. There were a few occasions throughout the active period of MS events when the number was larger than 5, but it never reached 11. Then, the occurrence of MS events entered a quiet period, with a low risk of the surrounding rock becoming unstable. The MS events started to become active again on 1 November. On most days, there were more than ten MS events per day. The reason is that the constructor adjusted the excavation speed again by increasing the frequency of the blasting and excavation to two or three times a day and keeping the average daily footage greater than 6 m. Figure 8d indicates that the activity rate of the daily MS events was closely related to the intensity of the site blasting and construction. A stress adjustment was also performed in the surrounding rock as a result of the disturbance from the blasting excavation of the caverns, in addition to the large elastic energy that accumulated in the rock under high geostress. It is expected that a large number of MS events would be induced if the accumulated energy is greater than its capacity.
The MS events showed an irregular distribution after 17 November. As shown in Figure 10a,b, there were very few MS events in the surrounding rock in the excavation and unloading area, while many MS events were concentrated in the vault of the auxiliary powerhouse and on the downstream spandrel and even tended to nucleate. Moreover, the frequency of the MS events increased dramatically, up to 19 times a day, as shown in Figure 10c. Analysis of the unfavorable geological structures indicates that a lamprophyre dyke appeared near the powerhouse vault from stakes 0 + 125 m to 0 + 140 m, and the surrounding rock experienced a stress adjustment due to unloading relaxation when the downstream tunnel face of the main and auxiliary powerhouses advanced to stake 0 + 100 m, 25 m from the lamprophyre dyke area. The elastic strain energy of the rock mass was preferentially released in the fracture and dispersion areas of the lamprophyre dyke, which caused fractures in the rock mass to propagate, releasing elastic waves, i.e., MS signals. The information above suggests that the MS events were typically concentrated close to the structural plane under the influence of the geological structures.

4. FLAC-Based 3D Numerical Modeling

4.1. Numerical Model

Numerical simulation is generally regarded as a simple and efficient research method that is widely used in geotechnical engineering, oil and gas, materials, and other fields [30,31,32,33,34,35,36]. A 3D geological model was established with the excavation size of the underground powerhouse and with the nearby geological conditions taken into account. Based on the three elements of faults, the upper and lower rock masses of the faults were pre-divided to achieve fault applications in the early modeling, and then the “interface” command was used in the FLAC 3D to complete the fault setting and assign the parameters. As shown in Figure 11a, the model has dimensions of 598 × 385 × 850 m, with a total of 769,304 elements. In this model, there are three important structural planes—the SPD9-F1 fault, the SPD9-F2 fault, and a lamprophyre dyke—that were taken into account. Figure 11b shows the bench excavation model of three major caverns. The underground powerhouse was excavated in nine benches, and this study focuses on the excavation of bench I. Figure 11c shows the schematic diagram of the underground powerhouse after bench I was excavated, and Figure 11d shows the support for the three major caverns with 6 m and 9 m rock bolts, which were alternatively installed. The mechanical parameters of the rock mass and structural planes were obtained from field and lab tests, as shown in Table 3 and Table 4. The displacement constraint was imposed around and at the bottom of the model, and the self-weight stress was applied to the top of the model. The Mohr–Coulomb elastic–plastic constitutive model was employed. Additionally, to minimize the residual difference between the measured and the calculated values, the geostress was fitted by using the methods of least squares and multiple linear regression. The fit results agreed well with the measured values.

4.2. Calculation Results

The powerhouse is the most important structure among the underground caverns of the diversion and power generation systems, and the deformation characteristics of the rock mass greatly affect the construction processes. Figure 12 shows the cross-sectional displacement of each turbine after the excavation of the powerhouse for bench I. The rock mass primarily deformed near the vault or spandrel, and the bottom also experienced a large displacement. The maximum cross-sectional displacement for turbines #1 and #2 was approximately 3.5 mm, and that of turbines #3 and #4 was approximately 5.1 mm and 5.6 mm, respectively. The SPD9-F1 fault appeared near turbines #3 and #4, causing significant deformation in the area. In addition, under the unfavorable influence of the steeply dipping lamprophyre dyke, the calculated maximum deformation of 7 mm in the powerhouse area was located at the downstream spandrel at stake 0 + 116.80 m, as shown in Figure 13. This indicates that the risk is the greatest in this area, and microseismic events are also concentrated near the steeply dipping lamprophyre dyke, indicating that the numerical simulation results are in good agreement with the microseismic monitoring results. Microseismic events accumulated in large numbers near the steeply dipping lamprophyre dyke, causing the rock mass near the steeply dipping lamprophyre dyke to be further fragmented and reduced in strength, which finally led to the collapse of the downstream spandrel on 17 May 2019. Fortunately, due to the early microseismic warning, there were no casualties, which means that microseismic monitoring can provide technical support for on-site construction, and the evolution characteristics of microseismic excavation of underground caverns with high geostress can provide a reference for on-site construction.

5. Conclusions

  • An MS monitoring system was built during the excavation of the underground powerhouse at the Shuangjiangkou hydropower station. The temporal distribution pattern of the MS events was obtained during the excavation of benches I and II of the underground powerhouse from 19 July 2018 to 31 October 2020. The study reveals that MS events occurred frequently during the excavation of bench I, with an average of more than nine events in a single day. Moreover, the MS events still appeared during the support period when the blasting was stopped, indicating that the surrounding rock experienced a long stress adjustment under high geostress. However, the MS events occurred less frequently overall during the excavation of bench II due to the stress release and minor disturbance from the blasting, with an average of less than five events in a single day. The spatial distribution pattern of the MS events indicates that the high ground stress environment usually had a large number of MS events. There were three concentration zones of MS events with large energy and high moment magnitude, which are closely related to the construction dynamics and planes of geological structures.
  • The intensive blasting and construction periods from 19 July 2018 to 3 December 2018 were selected to examine the dynamic relationship between the evolution of the MS events, the site construction conditions, and the geological structures. In summary, site blasting construction was the main factor inducing MS events in and around underground caverns under high geostress. The distribution of the MS events were strongly correlated with the location of the site blasting. Moreover, the frequency of the MS events was positively correlated with that of the blasting. The number of MS events was increased by the structural plane. The possibility of the surrounding rock becoming unstable was raised by the structural plane.
  • The simulated maximum cross-sectional displacement of each turbine generally appeared near the spandrel during the excavation of the underground powerhouse for bench I. The maximum displacement occurred in the vicinity of the lamprophyre dyke near the upstream spandrel. The numerical modeling results closely matched the MS monitoring data and the site failure status of the rock mass. The failure and deformation of the rock mass were greatly impacted by the geological structure of the underground powerhouse under high geostress.

Author Contributions

X.L. conducted the literature review and wrote the first draft of the manuscript. B.L. developed the overarching research goals and analyzed the microseismic data. P.L. edited the draft of the manuscript. Q.D. carried out the numerical simulation. M.H. processed the microseismic monitoring data. All authors have read and agreed to the published version of the manuscript.

Funding

The research is supported by the National Natural Science Foundation of China (No. 42177143, 42277461), the Science Foundation for Distinguished Young Scholars of Sichuan Province (Grant No. 2020JDJQ0011).

Institutional Review Board Statement

Not applicable.

Data Availability Statement

Not applicable.

Acknowledgments

Thanks are given to colleagues at the hydropower station for their valuable contributions to the project. Additionally, the authors would like to thank the editors and reviewers for their valuable comments and constructive suggestions.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Song, S.W.; Feng, X.M.; Xiang, B.Y.; Xing, W.B.; Zeng, Y. Research on key technologies of high and steep rock slope engineering of southwest hydropower. J. Rock Mech. Geotech. Eng. 2011, 30, 1–22. [Google Scholar]
  2. Zhu, W.H.; Li, Y.; Li, S.C.; Wang, S.G.; Zhang, Q.B. Quasi-three-dimensional physical model tests on a cavern complex under high in-situ stresses. Int. J. Rock. Mech. Min. Sci. 2011, 48, 199–209. [Google Scholar]
  3. Li, T.B.; Liu, T.Y.; Chen, G.Q.; Ma, C.C.; Zhang, H. Construction of microseismic monitoring system for highway tunnels and analysis of microseismic characteristics. Chin. J. Undergr. Space. Eng. 2019, 15, 1188–1196. [Google Scholar]
  4. Young, R.; Collins, D.; Reyes-Montes, J.; Baker, C. Quantification and interpretation of seismicity. Int. J. Rock Mech. Min. Sci. 2004, 41, 1317–1327. [Google Scholar] [CrossRef]
  5. Hassani, H.; Hloušek, F.; Alexandrakis, C.; Buske, S. Migration-based microseismic event location in the Schlema-Alberoda mining area. Int. J. Rock Mech. Min. Sci. 2018, 110, 161–167. [Google Scholar] [CrossRef]
  6. Barthwal, H.; Calixto, F.J.; van der Baan, M. 3-D attenuation tomography from microseismicity in a mine. Geophys. J. Int. 2019, 219, 1805–1817. [Google Scholar] [CrossRef]
  7. Young, R.; Collins, D. Seismic studies of rock fracture at the Underground Research Laboratory, Canada. Int. J. Rock Mech. Min. Sci. 2001, 38, 787–799. [Google Scholar] [CrossRef]
  8. Krietsch, H.; Gischig, V.; Evans, K.; Doetsch, J.; Dutler, N.O.; Valley, B.; Amann, F. Stress Measurements for an in situ stimulation experiment in crystalline rock: Integration of induced seismicity, stress relief and hydraulic methods. Rock Mech. Rock Eng. 2019, 52, 517–542. [Google Scholar] [CrossRef] [Green Version]
  9. Denlinger, R.P.; Bufe, C.G. Reservoir conditions related to induced seismicity at the Geysers steam reservoir, northern California. Bull. Seism. Soc. Am. 1982, 72, 1317–1327. [Google Scholar] [CrossRef]
  10. Rutledge, J.T.; Phillips, W.S. Hydraulic stimulation of natural fractures as revealed by induced microearthquakes, Carthage Cotton Valley gas field, east Texas. Geophysics 2003, 68, 441–452. [Google Scholar] [CrossRef]
  11. Zhao, Q.; Lisjak, A.; Mahabadi, O.; Liu, Q.; Grasselli, G. Numerical simulation of hydraulic fracturing and associated microseismicity using finite-discrete element method. J. Rock Mech. Geotech. Eng. 2014, 6, 574–581. [Google Scholar] [CrossRef] [Green Version]
  12. Akono, A.; Druhan, J.L.; Dávila, G.; Tsotsis, T.; Jessen, K.; Fuchs, S.; Crandall, D.; Shi, Z.; Dalton, L.; Tkach, M.K.; et al. A review of geochemical–mechanical impacts in geological carbon storage reservoirs. Greenh. Gases: Sci. Technol. 2019, 9, 474–504. [Google Scholar] [CrossRef]
  13. Li, S.Y.; He, X.S.; Zhang, S.Q.; Lu, Q.H.; Jiang, X.Q.; Tong, X.H.; Li, T.; Guan, E.F.; Zuo, Y.; Sun, X.H.; et al. Progress and latest achievements of mine seismic monitoring technology. Prog Geophys. 2004, 19, 853–859. [Google Scholar]
  14. Tang, L.Z.; Jian, Y.H.; Li, D.Y.; Deng, L.F.; Chen, Y. Analysis on failure mechanism of surrounding rock of mine based on microseismic moment tensor. Rock Soil Mech. 2017, 38, 1436–1444. [Google Scholar]
  15. Dou, L.M.; Feng, L.F.; Cai, W.; Wang, H.; He, H.H.; Jiao, B.; Zhang, M. Study on acoustic earthquake precursor recognition and comprehensive early warning model in coal and rock disaster damage process. J. Min. Saf. Eng. 2020, 37, 10. [Google Scholar]
  16. Zhu, Q.J.; Jiang, F.X.; Wei, Q.D.; Wang, B.; Liu, J.H.; Liu, X.H. Automatic pickup method of P-wave first break of microseismic signal of coal seam hydraulic fracturing. J. Rock Mech. Geotech. Eng. 2018, 37, 2319–2333. [Google Scholar]
  17. Jiang, L.; Kong, P.; Zhang, P.; Shu, J.; Wang, Q.; Chen, L.; Wu, Q. Dynamic Analysis of the Rock Burst Potential of a Longwall Panel Intersecting with a Fault. Rock Mech. Rock Eng. 2020, 53, 1737–1754. [Google Scholar] [CrossRef]
  18. Chen, B.R.; Feng, X.T.; Zeng, X.H.; Xiao, Y.X.; Zhang, Z.T.; Ming, H.J.; Feng, G.L. Real time monitoring and characteristic analysis of microseisms in TBM tunneling of deep tunnels. J. Rock Mech. Geotech. Eng. 2011, 30, 275–283. [Google Scholar]
  19. Feng, G.-L.; Feng, X.-T.; Chen, B.-R.; Xiao, Y.-X.; Zhao, Z.-N. Effects of structural planes on the microseismicity associated with rockburst development processes in deep tunnels of the Jinping-II Hydropower Station, China. Tunn. Undergr. Space Technol. 2019, 84, 273–280. [Google Scholar] [CrossRef]
  20. Liu, X.; Tang, C.; Li, L.; Lv, P.; Sun, R. Microseismic monitoring and stability analysis of the right bank slope at Dagangshan hydropower station after the initial impoundment. Int. J. Rock Mech. Min. Sci. 2018, 108, 128–141. [Google Scholar] [CrossRef]
  21. Liang, Z.; Xue, R.; Xu, N.; Dong, L.; Zhang, Y. Analysis on microseismic characteristics and stability of the access tunnel in the main powerhouse, Shuangjiangkou hydropower station, under high in situ stress. Bull. Eng. Geol. Environ. 2020, 79, 3231–3244. [Google Scholar] [CrossRef]
  22. Xue, R.; Liang, Z.; Xu, N.; Dong, L. Rockburst prediction and stability analysis of the access tunnel in the main powerhouse of a hydropower station based on microseismic monitoring. Int. J. Rock Mech. Min. Sci. 2020, 0126, 104174. [Google Scholar] [CrossRef]
  23. Dai, F.; Li, B.; Xu, N.; Fan, Y.; Zhang, C. Deformation forecasting and stability analysis of large-scale underground powerhouse caverns from microseismic monitoring. Int. J. Rock Mech. Min. Sci. 2016, 86, 269–281. [Google Scholar] [CrossRef]
  24. Dai, F.; Li, B.; Xu, N.; Meng, G.; Wu, J.; Fan, Y. Microseismic Monitoring of the Left Bank Slope at the Baihetan Hydropower Station, China. Rock Mech. Rock Eng. 2017, 50, 225–232. [Google Scholar] [CrossRef]
  25. Li, B.; Xu, N.; Dai, F.; Zhang, G.; Xiao, P. Dynamic analysis of rock mass deformation in large underground caverns considering microseismic data. Int. J. Rock Mech. Min. Sci. 2019, 122, 104078. [Google Scholar] [CrossRef]
  26. Li, B.; Ding, Q.-F.; Xu, N.-W.; Dai, F.; Xu, Y.; Qu, H.-L. Characteristics of microseismic b-value associated with rock mass large deformation in underground powerhouse caverns at different stress levels. J. Central South Univ. 2022, 29, 693–711. [Google Scholar] [CrossRef]
  27. Zhao, J.-S.; Jiang, Q.; Lu, J.-F.; Chen, B.-R.; Pei, S.-F.; Wang, Z.-L. Rock fracturing observation based on microseismic monitoring and borehole imaging: In situ investigation in a large underground cavern under high geostress. Tunn. Undergr. Space Technol. 2022, 126. [Google Scholar] [CrossRef]
  28. Li, B.; Ding, Q.-F.; Xu, N.-W.; Lei, Y.-F.; Xu, Y.; Zhu, Z.-P.; Liu, J.-F. Mechanical response and stability analysis of rock mass in high geostress underground powerhouse caverns subjected to excavation. J. Central South Univ. 2020, 27, 2971–2984. [Google Scholar] [CrossRef]
  29. Ding, Q.; Li, B.; Su, H.; Xu, N.; Li, X.; Deng, X. Damage mechanism and stability analysis of rock mass in the high geo-stress tunnel subjected to excavation. Geomatics Nat. Hazards Risk 2022, 13, 75–93. [Google Scholar] [CrossRef]
  30. Ka, M.; Liu, G.Y. Three-dimensional discontinuous deformation analysis of failure mechanisms and movement characteristics of slope rockfalls. Rock Mech. Rock Eng. 2022, 55, 275–296. [Google Scholar]
  31. Song, R.; Liu, J.; Yang, C.; Sun, S. Study on the multiphase heat and mass transfer mechanism in the dissociation of methane hydrate in reconstructed real-shape porous sediments. Energy 2002, 254. [Google Scholar] [CrossRef]
  32. Song, R.; Wang, Y.; Tang, Y.; Peng, J.; Liu, J.; Yang, C. 3D Printing of natural sandstone at pore scale and comparative analysis on micro-structure and single/two-phase flow properties. Energy 2022, 261. [Google Scholar] [CrossRef]
  33. Salari, A.; Kazemian, A.; Ma, T.; Hakkaki-Fard, A.; Peng, J. Nanofluid based photovoltaic thermal systems integrated with phase change materials: Numerical simulation and thermodynamic analysis. Energy Convers. Manag. 2022, 205, 112384. [Google Scholar] [CrossRef]
  34. Quarteroni, A.; Luca, F. Mathematical modelling and numerical simulation of the cardiovascular system. Handb. Numer. Anal. 2004, 12, 3–127. [Google Scholar]
  35. Hasheminezhad, A.; Bahadori, H. Seismic response of shallow foundations over liquefiable soils improved by deep soil mixing columns. Comput. Geotech. 2019, 110, 251–273. [Google Scholar] [CrossRef]
  36. Zhao, J.-S.; Chen, B.-R.; Jiang, Q.; Lu, J.-F.; Hao, X.-J.; Pei, S.-F.; Wang, F. Microseismic Monitoring of Rock Mass Fracture Response to Blasting Excavation of Large Underground Caverns Under High Geostress. Rock Mech. Rock Eng. 2022, 55, 733–750. [Google Scholar] [CrossRef]
Applsci 12 12145 g001 550
Figure 1. Layout of the caverns in the diversion and power generation system on the left bank of the Shuangjiangkou hydropower station [26].
Figure 1. Layout of the caverns in the diversion and power generation system on the left bank of the Shuangjiangkou hydropower station [26].
Applsci 12 12145 g001
Applsci 12 12145 g002 550
Figure 2. Geological horizon slice map of the plant area at a height of 2268 m [29].
Figure 2. Geological horizon slice map of the plant area at a height of 2268 m [29].
Applsci 12 12145 g002
Applsci 12 12145 g003 550
Figure 3. Network topology of the MS monitoring system for the underground powerhouse.
Figure 3. Network topology of the MS monitoring system for the underground powerhouse.
Applsci 12 12145 g003
Applsci 12 12145 g004 550
Figure 4. Temporal distribution of MS events from 19 July 2018 to 31 October 2020.
Figure 4. Temporal distribution of MS events from 19 July 2018 to 31 October 2020.
Applsci 12 12145 g004
Applsci 12 12145 g005 550
Figure 5. Spatial distribution of MS events. (a), Side view of MS event distribution; (b), Top view of MS event distribution.
Figure 5. Spatial distribution of MS events. (a), Side view of MS event distribution; (b), Top view of MS event distribution.
Applsci 12 12145 g005
Applsci 12 12145 g006 550
Figure 6. Construction site of the sidewall excavation.
Figure 6. Construction site of the sidewall excavation.
Applsci 12 12145 g006
Applsci 12 12145 g007 550
Figure 7. Spatial and temporal evolutions of the MS events from 19 July to 30 August 2018. (a), Spatial and temporal evolutions of the MS events from 19 July to 3 August 2018; (b), Spatial and temporal evolutions of the MS events from 19 July to 16 August 2018; (c), Spatial and temporal evolutions of the MS events from 19 July to 30 August 2018.
Figure 7. Spatial and temporal evolutions of the MS events from 19 July to 30 August 2018. (a), Spatial and temporal evolutions of the MS events from 19 July to 3 August 2018; (b), Spatial and temporal evolutions of the MS events from 19 July to 16 August 2018; (c), Spatial and temporal evolutions of the MS events from 19 July to 30 August 2018.
Applsci 12 12145 g007
Applsci 12 12145 g008 550
Figure 8. Spatial and temporal evolutions of the MS events from 23 August to 16 November 2018. (a), Spatial and temporal evolutions of the MS events from 23 August to 3 September 2018; (b), Spatial and temporal evolutions of the MS events from 23 August to 3 October 2018; (c), Spatial and temporal evolutions of the MS events from 23 August to 16 November 2018; (d), The activity rate of the daily MS events.
Figure 8. Spatial and temporal evolutions of the MS events from 23 August to 16 November 2018. (a), Spatial and temporal evolutions of the MS events from 23 August to 3 September 2018; (b), Spatial and temporal evolutions of the MS events from 23 August to 3 October 2018; (c), Spatial and temporal evolutions of the MS events from 23 August to 16 November 2018; (d), The activity rate of the daily MS events.
Applsci 12 12145 g008
Applsci 12 12145 g009 550
Figure 9. Excavation sequence of the sidewall.
Figure 9. Excavation sequence of the sidewall.
Applsci 12 12145 g009
Applsci 12 12145 g010 550
Figure 10. Spatial and temporal evolutions of the MS events from 17 November to 3 December 2018. (a), Top view of MS event distribution; (b), Side view of MS event distribution; (c), The activity rate of the daily MS events.
Figure 10. Spatial and temporal evolutions of the MS events from 17 November to 3 December 2018. (a), Top view of MS event distribution; (b), Side view of MS event distribution; (c), The activity rate of the daily MS events.
Applsci 12 12145 g010
Applsci 12 12145 g011 550
Figure 11. Three-dimensional numerical model: (a) 3D numerical model; (b) numerical model of three major caverns; (c) completion of bench I; (d) schematic diagram of the support.
Figure 11. Three-dimensional numerical model: (a) 3D numerical model; (b) numerical model of three major caverns; (c) completion of bench I; (d) schematic diagram of the support.
Applsci 12 12145 g011
Applsci 12 12145 g012 550
Figure 12. Cross-sectional displacement of each turbine after excavation and support of bench I: (a) turbine #1; (b) turbine #2; (c) turbine #3; (d) turbine #4.
Figure 12. Cross-sectional displacement of each turbine after excavation and support of bench I: (a) turbine #1; (b) turbine #2; (c) turbine #3; (d) turbine #4.
Applsci 12 12145 g012
Applsci 12 12145 g013 550
Figure 13. Displacement at the exposure of the lamprophyre dyke.
Figure 13. Displacement at the exposure of the lamprophyre dyke.
Applsci 12 12145 g013
Table
Table 1. List of the main structural planes.
Table 1. List of the main structural planes.
Fault/JointLocation Depth in the SPD9 AditAttitudeFracture Zone WidthAngle of Intersection with the Plant Axis
SPD9-F1504–505.5 mN79°W/SW∠48°50–60 cm69°
SPD9-f2625 mN33°W/NE∠88°80–140 cm23°
Lamprophyre dyke380–395 mN35°–50°W/SW∠72°–75°80–110 cm25°–40°
J1 N20°–50°E/SE∠25°–42° 30°–60°
J2 N5°–26°E/NW∠10°–30° 15°–36°
J3 N50°–75°W/SW∠58°–75° 60°–85°
J4 N60°–80°E/NW∠5°–15° 50°–80°
J5 N50°–60°E/SE∠45°–65° 40°–50°
Table
Table 2. Geostress classification.
Table 2. Geostress classification.
Stress ClassificationMaximum Principal Stress Level σm (MPa)Rock Strength–Stress Ratio Rb/σm
Very highσm ≥ 40<2
High20 ≤ σm < 402–4
Moderate10 ≤ σm < 204–7
Lowσm < 10>7
Note: Rb in the table is the saturated uniaxial compressive strength of the rock (MPa), and σm is the maximum principal stress (MPa).
Table
Table 3. Mechanical parameters of the rock mass.
Table 3. Mechanical parameters of the rock mass.
Parameter CategoryDensity
(g/cm3)		Bulk Modulus
(GPa)		Shear Modulus
(GPa)		Poisson’s RatioCohesion
(MPa)		Internal Friction Angle
(°)		Tensile Strength
(MPa)
IIIa2.5529.213.50.251.5456.5
Table
Table 4. Mechanical parameters of the structural planes.
Table 4. Mechanical parameters of the structural planes.
Structural PlaneNormal Stiffness
(GPa/m)		Shear Stiffness
(GPa/m)		Cohesion
(MPa)		Internal Friction Angle
(°)		Tensile Strength
(MPa)
SPD9-F1630.05200.05
SPD9-F2630.05200.05
Lamprophyre dyke1050.1250.1
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Lin, X.; Li, B.; Li, P.; Ding, Q.; Huang, M. Study of the Evolution Characteristics of Microseismic Events during the Excavation of Underground Caverns under High Geostress. Appl. Sci. 2022, 12, 12145. https://doi.org/10.3390/app122312145

AMA Style

Lin X, Li B, Li P, Ding Q, Huang M. Study of the Evolution Characteristics of Microseismic Events during the Excavation of Underground Caverns under High Geostress. Applied Sciences. 2022; 12(23):12145. https://doi.org/10.3390/app122312145

Chicago/Turabian Style

Lin, Xin, Biao Li, Peng Li, Quanfu Ding, and Mengting Huang. 2022. "Study of the Evolution Characteristics of Microseismic Events during the Excavation of Underground Caverns under High Geostress" Applied Sciences 12, no. 23: 12145. https://doi.org/10.3390/app122312145

APA Style

Lin, X., Li, B., Li, P., Ding, Q., & Huang, M. (2022). Study of the Evolution Characteristics of Microseismic Events during the Excavation of Underground Caverns under High Geostress. Applied Sciences, 12(23), 12145. https://doi.org/10.3390/app122312145

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop