Analysis of rock mass stability according to power-law attenuation characteristics of acoustic emission and microseismic activities

Tunnelling and Underground Space Technology 83 (2019) 303–312

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Analysis of rock mass stability according to power-law attenuation characteristics of acoustic emission and microseismic activities

T

⁎

Liu Jian-poa,b, , Xu Shi-daa, Li Yuan-huia a b

Key Laboratory of Ministry of Education for the Safe Mining of Deep Metal Mines, Northeastern University, Shenyang 110819, China Shandong Gold Group Co., Ltd., Jinan, Shandong 250014, China

A R T I C LE I N FO

A B S T R A C T

Keywords: Rock mass stability Acoustic Emission (AE) Microseismic (MS) Modified Omori Law (MOL) Power-law attenuation

Under the influence of many factors, including complicated geological condition, high stress environment and strong disturbance by blasting, rock mass failure, and in some cases, dynamic failures would occur. Therefore, it is important to investigate and to understand rock mass stability during mining. In this study, Modified Omori Law (MOL) was applied to analyze the acoustic emission (AE) and microseismic (MS) sequence power-law attenuation characteristics in the laboratory and in situ. The MOL parameters, during the period of constant stress at lower stress level was much different with that at higher stress level, can reflect the stress level in rock. Before failure of the two rock specimens, the MOL is not applicable, indicating that the rock was close to the critical instability state. During the mining process, rock mass would be strongly disturbed by blasting. The AE sequence monitored from a ramp near the stope, and the MS sequence monitored from the whole rock mass near the stope all exhibited distinct power-law attenuation characteristics. The changes of MOL parameters, i.e., p, c and A, are very complex and related to many factors and it should cooperative analyze the three parameters to evaluate rock mass stability during the mining process.

1. Introduction Acoustic Emission (AE) are elastic waves released (i.e., radiated energy) when micro-cracks are generated in a rock mass that is subjected to loading conditions. The AE method, when applied in situ, can continuously monitor the spatial-temporal evolution of AE events, which are linked to the nucleation and propagation of such microcracks and, thus, may reveal the deformation processes as well as the failure mechanisms in rocks under loading. A series of achievements has been realized, e.g., the AE location algorithms, the temporal-spatial evolution behaviors of micro-cracks in rock bodies and the changes of the many AE parameters (Mogi, 1962; Scholz, 1968a, 1968b; Ohtsu, 1991; Lockner, 1993; Chang and Lee, 2004; Lei and Satoh, 2007; Hirata et al., 2007; Li et al., 2010; Liu et al., 2015). Moreover, the microseismic (MS) monitoring technique, using elastic waves generated by rock fracture to evaluate the stability of rock mass, has been proven to be a useful tool for assessing rock mass stability and for forecasting dynamic hazards to better manages disastrous rock failures. With the advances in computer technology since the 1990s, the ability to perform fast processing of seismic waves has made the MS technology more applicable. Now, MS technology has become a routine technology in deep mining operations and is widely used in South Africa, Australia,

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the United States, Canada, Chile, Poland, China and other countries (Mccreary et al., 1992; Urbancic and Trifu, 2000; Milev et al., 2001; Ge, 2005; Driad-Lebeau et al., 2005; Wang and Ge, 2008; Lesniak and Lsakow, 2009; Liu et al., 2013; Yang et al., 2015). After a main earthquake, increased seismic activities, i.e., so-called aftershocks, will be observed. With the passage of time after the main earthquake, the aftershocks gradually decrease and eventually become mixed in the background earthquakes. The time of aftershock duration and attenuation speed is of great significance for earthquake research and disaster rescue and thus has attracted extensive attention by many researchers. Omori (1894) discovered scaling in earthquakes in the frequency distribution of aftershocks over one-hundred years ago, when he proposed a formula to represent the decay of aftershock activities with time as follows:

N (t ) = A·(t + c )−1

(1)

The formula represents the number of aftershocks N(t), measured at time t after the time of the main earthquake. This formula and its modified form have been widely used as one of a few established empirical laws in seismology. For most aftershock sequences, the attenuation index is often not equal to 1 and is often much smaller than expected according to Eq. (1). The Omori law was modified by Utsu

Corresponding author. E-mail address: [email protected] (L. Jian-po).

https://doi.org/10.1016/j.tust.2018.09.023 Received 17 June 2017; Received in revised form 27 June 2018; Accepted 30 September 2018 Available online 17 October 2018 0886-7798/ © 2018 Elsevier Ltd. All rights reserved.

Tunnelling and Underground Space Technology 83 (2019) 303–312

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(1958, 1961) through the use of an exponent p to describe the power law declines of aftershocks.

N (t ) = A·(t + c )−p

(2)

Excavated zone R0

For a sequence of a large number of aftershock, Omori’s formula can describe the aftershock decay over time. Utsu et al. (1995) analyzed the value of parameter p for a large number of earthquakes and found that the exponent p is usually between 0.9 and 1.5. Lei et al. (2008) studied earthquakes induced by water injection and obtained p values of 0.44, 0.56 and 0.67 for Mm ≥ 3.0, Mm ≥ 4.0, and Mm ≥ 5.0, respectively. These values are smaller than the typical value of 1.0 for tectonic earthquakes worldwide. Zhao et al. (1992) conducted 32 earthquakes of M > 5 in China to analyze the p value of aftershocks activities and found that the average p value of aftershock sequences was 0.91, which is smaller than that in Japan. Omori’s law has also been used in laboratory-scale experiments in brittle rock fracture by measuring acoustic emission, and in mine-induced seismicity. Scholz (1968a,1968b) succeeded in reproducing Omori’s power law aftershock sequences of acoustic emission (AE) events of the rock specimen. In his experiment he considered that the fracture of the whole rock specimen corresponded to the main shock and AE corresponded to the aftershocks. According to the study by Hirata (1987), a time series of AE in basalt was measured under constant uniaxial compression. Some bursts of AE events considered to be the main shock and aftershock sequence were observed. Lockner and Byerlee (1977) conducted creep tests on granite and sandstone samples at 100 MPa confining pressure and stress levels from 45 to 95% of failure strength, and found a decreasing decay rate with increasing stress level. By analyzing the aftershock sequence induced by underground explosion, Li et al. (2004) indicated that the aftershocks conformed to a negative power function, and introduced the view that the aftershock sequence attenuated slightly faster within two weeks of postexplosions and attenuated to the background within one month after an explosion. By studying the MS activities at the Western Deep Levels gold mine, South Africa, Gibowicz (1997) found the MS sequence was composed in fact of four main shock-aftershocks sequences. The above mentioned results show that the aftershock rate decays with time in laboratory-scale experiments and in field monitoring. The Omori Law provides a practical useful model for mining induced seismicity. As the shallow resources gradually reduce, deep mineral resource exploitation gradually becomes the trend of future mining. The mining depth of the deepest mines in the world has reached to nearly 4 km underground (Duddu, 2013). In China, the depth of many metal mines are also gradually exceeded 1000 m below the surface, with the continued rapid development of the national economy and increased demands for mineral resources. Under the influence of many factors including complicated geological condition, high stress environment and strong disturbance by blasting, rock mass failure (in some cases, dynamic failures) occurs. Therefore, it is important to investigate and understand rock mass stability after blasting to guide the working time and areas for staff. In this paper, acoustic emission (AE) and microseismic (MS) monitoring was applied to study the rock fracture process under multilevel- uniaxial loading, as well as rock mass stability near the tunnel and stope after blasting. The power-law attenuation characteristics of the AE and the MS sequence of the three scale rock (or rock masses) were analyzed in detail.

Disturbed zone R=3 5R0 Undisturbed zone Fig. 1. Sketch map of the damage zone by excavation.

disturbed zone would gradually return to stability via self-regulation along with deformation and local fractures. If the external stress is much higher, then the stress concentration is quite easily formed in the disturbed zone. When the stress is accumulated to a certain extent, rock mass instability may be induced. In this paper, experiments of rock fracture process monitored by the AE technique under multilevel-uniaxial loading were conducted, and the power-law attenuation characteristics of the AE sequence during the period of constant stress were studied.

2.1. Experimental process Cubic specimens of granite, approximately 50 mm in both length and width and 100 mm in height, were used in this work. The PCI-2 system produced by the American Physical Acoustics Corporation (PAC) was used for the AE monitoring. Eight Nano30 type sensors were used to acquire AE signals, of which the operating frequency is 125–750 kHz. Each sensor was equipped with a 1220A-AST type preamplifier. During the experiment, the sensors were fixed on the side face of the samples with rubber bands. Vaseline was smeared between the AE sensors and the interfaces of the granite sample to ensure good coupling. Moreover, plastic sheets were placed at the top and bottom ends of the specimen to reduce friction signals between the pressure platens and the specimens. Because the laboratory environment was quiet, the number of AE hits was calculated from all eight sensors. A servo-controlled rock testing machine called Rockman207 was used for experiments in this study. The machine can record the amount of load and the degree of displacement in real time. The multileveluniaxial loading path is shown in Fig. 2. First, the axial stress was increased to 10 MPa at a rate of 0.5 MPa per second. Second, stress is kept at 10 MPa for a certain time. Then, axial stress was further increased to 20 MPa at the rate of 0.5 MPa per second and kept for a certain time again. The load steps were repeated until rock failure.

until rock failure. Until rock failure Stress remains constant

2. Rock fracture process monitoring via the AE technique When rock mass was excavated, the stress near excavated zone would be redistributed caused via the unloading effect and form a disturbed zone, whose radius is approximately three-to-five times larger than that of the excavated zone, shown as Fig. 1. If one takes the excavated zone and disturbed zone as a whole, the external stress can be viewed as constant or small changes during a certain period. If the external stress is much lower than the failure strength of rock mass, the

t Fig. 2. Sketch map of multilevel-uniaxial loading path. 304

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of specimen-1 were between 0.45 and 2.41 while that were between 0.45 and 2.28 for specimen-2, with most were smaller than 1.50. At a lower stress level, i.e., under approximately 50% of the peak strength, p values were ranging from 1.16 to 0.75 for specimen-1 and from 1.80 to 0.70 for specimen-2. The average p values in this phase were 0.97 and 1.06 of the two specimens, with the c values were estimated as zero. When the stress exceeded 50% of the peak strength, there are two cases: larger p values with larger A values and c values, and another is the smaller p values with c values are zero. For specimen-1, p values are ranging 1.02 and 2.41 and its average values is 1.52 between 50% and 75% of the peak strength. During this phase, the c values were not zero and the A values were very large. When the stress exceeded 80% of the peak strength, p values suddenly dropped to that average value of 0.48 and c values returned to zero. The changes of MOL parameters for specimen-2 at a higher stress level is the other way around. The average p value was 0.47 when the stress between 57% and 69% of the peak strength, while increased to 1.73 with larger A values and c values when stress exceeded 80% of the peak strength. The discussion above mentioned indicates that the AE attenuation law at the higher stress can result in the complex changes of the MOL fitting parameters. Therefore, the three parameters, i.e., p, c and A, should be collaborative analyzed when rock under a higher stress level. In addition, it should be noted that before failure of the two rock specimens, the Modified Omori Law was not applicable, indicating that the rock was close to the critical instability state. Note that micro-cracks generated during the period of constant stress can be considered as an extension of the previous loading effect because of the existence of residual stress. These micro-cracks would reduce the residual stress, enabling the rock to return to a stable state. In the continuously cyclic loading path without stress keep stage, it is unclear if enough time exists for the internal stress and structure to adjust and achieve balance. If the adjustment of internal stress and structure is not achieved, micro-cracks may be generated before the previous maximum stress reached under continuously cyclic loading. The in situ stress measured via the Kaiser Effect is generally considered effective only when the ground stress is less than 50% of the failure stress, i.e., if the ground stress is higher than half of the failure stress, then the in situ stress measured by use of Kaiser Effect is not accurate. These results are obtained from continuous cyclic loading. The phenomenon of AE signals generated before the previous maximum stress is reached may arise from the previous loading effect mentioned above. For rock in situ or under smaller disturbances, its underground stress state can be considered as a constant. During the process of core-drilling and specimen processing, the adjustment of the internal stress and structure in rock occur. This process is much different with the adjustment of internal stress structure in rock under continuous cyclic loading. Therefore, it is quite meaningful to conduct experiments under cyclic loading, including stress keep phases for the Kaiser Effect study. Such experiments may change the understanding of effective stress level for in situ stress measurement via the Kaiser Effect.

2.2. AE attenuation law with the stress level Ogata (1983) introduced a maximum likelihood method (MLE) to estimate the Modified Omori Law (MOL) parameters (p, A, c). Vallejos (2010) and Woodward et al. (2017) evaluated the performance weighted metric for the modelling of a synthetic seismic dataset. This assessment showed that seismic responses can be quantified and delineated by the MOL, with reasonable accuracy and precision, when the modelling is optimized by evaluating the weighted MLE metric. Based on a detailed study of the MOL applied to mining-induced aftershock sequences from four different mine environments in Ontario, Canada, p values were obtained that differed from sequence to sequence, with most ranging from 0.4 to 1.6 (Vallejos and Mckinnon, 2010). The estimation procedure proposed by MLE is directly based on the time series of aftershocks rather than the number of aftershocks per unit time interval (Ogata, 1983). In the present paper, the AE hits or the MS events was recorded per unit time interval (per minutes or per day), thus the estimates of the three MOL parameters have been obtained in the following way: take the logarithm of both sides of Eq. (2) as follow:

lnN (t ) = lnA−pln(t + c )

(3)

The curve of lnN(t) versus ln(t + c) tends to a straight line with increasing t and the slope of the straight line is an estimate for p. In the present paper, the least square method (LSM) was used to fit the curve lnN(t) versus ln(t + c) and to estimate the MOL parameters (p, A, c). In addition, the value of c was set as larger than or equal to zero during the fitting process. For specimens-1, the time of constant stress was 30 min during the whole loading process. The time of constant stress for specimens-2 are changed: 15 min when the stress is less than 40 MPa, 30 min when the stress is between 40 MPa and 90 MPa, and 40 min for the stress beyond 90 MPa. The failure process of rock under uniaxial loading includes four stages, i.e., compaction stage, elastic deformation stage, unstable fracture stage and failure stage after peak strength. As stress-controlled for loading was used in this study, the specimens suffered sudden failure when the peak stress was reached, and the failure stage was not obtained. Therefore, the AE activities of the first three stages were analyzed in this study. The AE activities during the period of constant stress at a lower stress level was much different with that at a higher stress level for the two granite specimens, as shown in Figs. 3 and 4. At the initial loading stage and earlier elastic deformation stage, the AE signals were mainly generated by closure and friction of the original defects and cracks. As the stress was kept at a certain value, the AE signals declined rapidly, and the attenuation trend was quite obvious, as shown in Fig. 4(a) and (b). With increasing load, the AE signals showed obviously power attenuation characteristics from the later periods of elastic deformation stage, as shown in Fig. 4(c) and (d). From dislocation theory, when the displacements at both ends of a slip surface are not uniform because of the inhomogeneity of rock, the residual stress is generated. When the external stress is not changed, the residual stress in rock can cause self-adjustment of the internal structure, leading to micro-crack expansion or new micro-crack generation. Such microcrack expansion would reduce the residual stress, causing the rock to return to a stable state. Therefore, the AE activities are also reduced to a lower state. As the rock entered into an unstable fracture stage, the AE activities during the period of constant stress were not stable, as shown in Fig. 4(e) and (f). In this stage, although the stress has not reached the failure strength of the whole rock, the internal stress of some local regions may exceed the failure strength because of the inhomogeneity of the rock, leading to continuous generation of micro-cracks. Therefore, the AE attenuation characteristic was not notable. For example, when the stress reached 94% of the peak strength, the AE hits were not only decayed but also increased. If this stress is kept for a long enough time, the rock would fail. The MOL parameters appeared different changes at the low stress level and the high stress level, as demonstrated in Table 1. The p values

3. AE attenuation characteristics induced by blasting The Hongtoushan copper mine has been in operation since 1958; it is one of the deepest nonferrous metal mines in China. The deepest stope is 1357 m below the ground surface. With continued mining operation, high ground pressures have been causing seismic hazards, e.g., rockburst and roof collapses, which impact the safety of operators and disrupt production, hence causing financial losses. Aiming to mitigate seismic hazards and to enhance safety management, a MS monitoring system was installed around the no.27 stope at the depth of 1137 m. This stope was the largest stope, with an exposed area of 2400–3000 m2, and approximately 67,000 tons of ore were expected to be recovered. The overhead cut-and-fill stoping method was used for mining, four layers have been mined and the fifth layer is being stoped in this study. 305

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20

Stress/MPa

0.15

120

0.10

100

0.05

80

Stress AE hits

Zoom in the vertical

140

0

2

4

6

8

10

16

12 2.0

Zoom in the vertical

0.00 12

60

1.5

8

1.0

40

0.5

20 0

3

0.20

12

0

4

8

14

12

16

3

18

20

16

20

22

AE hits (10 /60s)

(a)

160

4

0.0

24

28

0

Time /10 s

120

10

0.20

100

8

0.16

80 0.12

6

0.08

4

60

3

Stress AE hits

AE hits (10 /60s)

12

140

Stress/MPa

14

(b)

160

40

Zoom in the vertical

20

0.04

2

0.00

0

0

5

10

15

20

25

30

0

3

Time /10 s Fig. 3. AE activities of granite specimens under multilevel-uniaxial loading: (a) is specimen-1 and (b) is specimen-2.

3.1. Mining process and monitoring program

3.2. AE attenuation characteristics by mining disturbed

The mining of the fifth layer at the no.27 stope was conducted from January 11 to January 19, 2011, except for January 16, 2011. The thickness of ore body was approximately 3–4 m, and the total area was approximately 1600 m2. The blasting design parameters of timing, position, sequence, amount of explosives and excavated volume are shown in Table 2 and Fig. 5. Before this mining work, two areas, Regions A and B, were mined. Regions C and D will be mined at a later stage. The mining in Regions 1–8 was completed on January 19, 2011. Nine AE sensors, divided into three groups, were installed along the ramp near the no.27 stope, as shown in Fig. 5. The Sensor Highway-II (SH-II) system produced by the American Physical Acoustics Corporation (PAC), was used for the AE monitoring. This system uses an 18-bit A/D switching technology that allows for instant time waveform recording. For the no.27 stope, the AE data was collected from January 12 to January 19. The blasting time was approximately 16:00 PM; hence, workers left after 15:30 and did not re-enter until the blasting fumes were cleared. During this period, the mining machines also stopped working. Therefore, the period was one with the least interference signals. Fig. 6 shows the Typical AE signal according to filed monitoring.

Fig. 7 shows the AE hits distribution after each blasting to 18:00, from January 12 to January19, and the number of AE hits was calculated every minute. It can be seen that the AE activities were suddenly increased to a much higher level after blasting, and then gradually declined over time. Because that no blasting mining operations occurred on January 16, as shown in Fig. 7(e), AE hits were mainly generated less than twenty every minute. These AE hits can be seen as the AE background and were used to study the AE attenuation characteristics by mining disturbed on other days. Based on the background AE activity on January 16, the time for the AE activities returned to a stable state on January 12, 13, 14, 15, 17, 18 and 19 at 16:25, after 18:00, 16:55, 17:12, 17:16, 17:11 and 17:21, respectively. The periods from blasting were 29 min, two and a half hours, 60 min, 71 min, 81 min, 73 min and 74 min, which indicated that the rock mass in the monitoring area can return to the stable state within 90 min after blasting, except on January 13. The mining area on January 13 was closest to the monitoring area, leading to the number of AE hits being tens of times greater than at other days, suggesting that the disturbance for monitoring area was largest on this day and that it requires a longer time for stress redistribution in the rock mass. Note that the number of AE hits only reflected the disturbance near the monitoring area by blasting, rather than disturbance of the whole stope. Because the frequency of AE signals is much higher and attenuation is much faster for 306

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150

Stress: 30.57MPa σA/ σmax= 0.19

120

A=6.92E3 p= 1.23 c= 0

90 60 30 0

300

600

900

Time/s

1200

1500

(c)

1000

Stress: 81.52MPa σA/ σmax= 0.50

800

A=1.03E6 p= 1.27 c= 147.29

600 400 200 0

300

600

900

Time/s

1200

1500

AE hits (each minute)

5000

Stress: 142.66MPa σA/ σmax= 0.87

4000

A=1.85E4 p= 0.51 c=0

3000

2000

1000

0

300

600

900

Time/s

1200

1500

Stress: 50.94MPa σA/ σmax= 0.31

80

A=0.92E3 p= 0.92 c= 0

60 40 20

300

600

900

Time/s

1200

1500

Stress: 122.28MPa σA/ σmax= 0.75

600

A=5.60E9 p= 2.41 c= 684.58

400

200

0

300

600

900

Time/s

1200

1500

15000

12000

1800

(f) Stress: 152.86MPa σ A/ σmax= 0.94

9000

6000

3000

0

1800

1800

(d)

800

1800

(e)

(b)

100

0

1800

AE hits (each minute)

AE hits (each minute)

1200

120

AE hits (each minute)

(a)

AE hits (each minute)

AE hits (each minute)

180

300

600

900

Time/s

1200

1500

1800

Fig. 4. Attenuation law of the AE sequence of typical stages during the period of constant stress.

18:00 for the days of January 12 to January 19. Clearly, the number of AE hits on January 13 was far higher than that of the other days, and a relatively low number of AE hits were generated on January 16. From analysis of the distance between the blasting area and the monitoring area and the time required for the rock mass to return to the stable state, a linear relationship was found, as shown in Fig. 9. Although the wide-range of failure of the ramp did not easily occur, generation of small-scale fractures was still possible, such as stripping and loosening of joint fissures. The monitoring result of the time for rock mass to return to the stable state from AE data provides useful information to evaluate the time at which workers can re-enter the ramp.

transmission in rock mass, only the signals from a distance of several meters can be received. During the mining process of no.27 stope, the AE activities showed quite obvious power-law attenuation characteristics after blasting. The power attenuation index, p value, on January 12, 13, 14, 15, 17, 18 and 19 was 1.00, 0.94, 0.47, 1.05, 0.42, 0.91 and 0.72, respectively, and its average value is 0.79. The c values varies from 0.12 to 1.73. The Aparameter is proportional to the productivity of a seismic response (Woodward et al., 2017). Although it is commonly arbitrary, there is a positive correlation between the A values and the AE activities that just following the blasting. In most case, the higher of the AE activities after the blasting, the larger of the A values. For example, the A value on January 13 is very large because the ramp was disturbed much more than on other days because of the smaller blasting distance. Fig. 8 shows the total AE hits between the time of each blasting to 307

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Table 1 MOL parameters’ values of estimated from the two specimens. Specimen-1

Specimen-2

σa/σmax

A

c

p

0.06 0.12 0.19 0.25 0.31 0.37 0.44 0.50 0.56 0.62 0.69 0.75 0.81 0.87 0.94

– 2991.08 6916.19 1157.92 916.58 529.83 524.07 1.03E+06 2.04E+05 6.11E+05 5.38E+06 5.60E+09 4626.8 18542.3 –

– 0.00 0.00 0.00 0.00 0.00 0.00 147.29 59.95 53.29 135.90 684.58 0.00 0.00 –

– 1.16 1.23 0.97 0.92 0.79 0.75 1.27 1.02 1.30 1.62 2.41 0.45 0.51 –

Average p

0.97

1.52

0.48

σa/σmax

A

c

p

0.06 0.13 0.19 0.25 0.31 0.38 0.44 0.50 0.57 0.63 0.69 0.75 0.82 0.88 0.94

– 20589.78 1672.27 15283.67 3936.43 944.32 300.31 419.41 41.9 49.94 80.37 – 7.84E+05 5.36E+09 –

– 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 – 382.33 1182.08 –

– 1.80 1.12 1.20 0.99 0.84 0.70 0.78 0.49 0.47 0.45 – 1.18 2.28 –

Average p

1.06

0.47

1.73

Note: The AE activities as the stress level of 6% and 94% of the two specimens and the stress level of 75% of specimen-2 are not conform to MOL.

4. Analysis of the rock mass stability near the stope after blasting

Table 2 Blasting parameters of mining work in no.27 stope. Number

Data

1 2 3 4 5 6 7 8

Explosive/box

2011.01.11 2011.01.12 2011.01.13 2011.01.14 2011.01.15 2011.01.17 2011.01.18 2011.01.19

25 26 30 30 30 30 30 6

Weight of explosive/ kg

Numbers of millisecond blasting

Ore volume/ m3

600 624 720 720 720 720 720 144

5 5 6 6 6 6 6 6

660 686 792 792 792 792 792 158

6

The no.21 stope, formed using sublevel rock drilling and the stage room mining method, is located at an elevation of −707 m (approximately 1100 m below the surface). The width and thickness of the orebody in this stope are approximately 30 m and 18 m, respectively. The height of the no.21 stope is 60 m (from −647 m level to −707 m level), with approximately 35 m of height remaining after excluding the top pillar and the bottom structure. After the cutting groove was stopped, five blasts were conducted to exploit the ore. The blasting design regarding the timing, position, sequence, amount of explosives are shown in Table 3 and Fig. 10.

Ore Pillar

7

4.2. MS system and sensor arrangement

5

8

4

For the no.21 stope, as shown in Fig. 10, three drilling tunnels are located between the −647 m level and the −707 m level. If the MS sensors were installed in these three tunnels, then the signal cable would be easily destroyed by the drastic explosive shock wave. Therefore, twenty-four 14-Hz uniaxial geophones, each with a performance range of 7–2000 Hz and sensitivity of 80 V/m s−1, were installed in the transportation roadways at the −647 m level and the −707 m level, with each level contains half the number of sensors. MS sensors were temporarily installed to allow their reuse for other stopes. The whole orebody to be mined and its surrounding rock mass of the no.21 stope are covered by the MS sensors to ensure the calculation accuracy of the position and source parameters of MS events. During the monitoring process, MS wave signals are detected by the sensors, which converted them into electrical analog signals that are received by the GS data acquisition units, where the signals are further converted to digital signals. A DSL-technology based communication system synchronizes the system and transmits the digital data through a telephone line from the GS units to a central server at an underground center at the −707 m level. The digital seismic data can be processed at the server, and results can be downloaded by the central office of the mine and by a remote research center at Northeast University (NEU) via the Internet. As the mining process is quite complex, there are many varieties of interference signals caused by blasting, ore drawing, mechanical vibration, etc. Although there are many methods to process MS signals, such as wavelet analysis and the time-frequency analysis technique, the useful MS signals are still easily mixed with the interference signals. In this study, the MS signals from rock mass fractures were mainly

D

2 A

4.1. Introduction of the no.21 stope and its mining process

C

3 1

Earlier excavation

Later excavation

B

AE sensors (3 sensors of each group) Fig. 5. Sequence and position of blasting in the no.27 stope.

Amplitude / V

0.08 0.04 0.00 -0.04 0

1

2

3

4

5

6

7

8

t / ms Fig. 6. Typical AE signal from field monitoring.

308

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Accumulated AE hits

60

40

Fitting curve

January 14 Blast time 15:55 A=115.37 p= 0.47 c= 0.89

1.0x103 5.0x102

16:00

16:30

17:00

17:30

Time

25

AE hits rate (each minute)

1.5x103

20

Accumulated AE hits

AE hits rate

20

0.0 18:00

(e)

No blast on January 16

6.0x102

4.0x102

10

2.0x102

5

0 16:00

16:30

17:00

17:30

Time

600 500

Accumulated AE hits

400

January 18 Blast time 15:58 A=604.87 p= 0.91 c= 0.12

300 200

Fitting curve

100

16:00

16:30

17:00

1.8x103

9.0x102

AE hits rate

Time

2.7x103

17:30

2x104 1x104

16:30

17:00

0 18:00

17:30

Time

(d)

300

3.5x103 3.0x103

250

Accumulated AE hits

2.5x103

January 15 Blast time 16:01 A=773.16 p= 1.05 c= 1.32

200 150 100

Fitting curve

2.0x103 1.5x103 1.0x103

AE hits rate

50

16:30

5.0x102

17:00

17:30

Time

0.0 18:00

(f)

100

Accumulated AE hits AE hits rate

60 40

4.0x103

3.2x103

January 17 Blast time 15:55 A=139.47 p= 0.42 c= 0.94

80

Accumulated AE hits

3x104

1x103

2.4x103

1.6x103

Fitting curve

20

8.0x102

0 16:00

16:30

17:00

Time

17:30

300

0.0 18:00

(h)

250 200 150 100

AE hits rate

January 19 Blast time 16:07 A=439.25 p= 0.72 c= 0.85 Fitting curve

50

16:30

17:00

Time

4.5x103

3.6x103

Accumulated AE hits

0 16:00

0.0 18:00

4x104

Fitting curve

120

4.5x103

3.6x103

January 13 Blast time 16:02 A=10685.36 p= 0.94 c= 0.25

2x103

0.0 18:00

(g)

5x104

AE hits rate

3x103

0 16:00

1.0x103

8.0x102

15

0

3

6x104

Accumulated AE hits

4x103

0 16:00

2.5x103 2.0x10

AE hits rate

5x103

0.0 18:00

(c)

80

6x103

7x104

Accumulated AE hits

17:30

AE hits rate (each minute)

17:00

Time

AE hits rate (each minute)

16:30

AE hits rate (each minute)

16:00

5.0x10

2

(b)

7x103

17:30

2.7x103

1.8x103

9.0x102

Accumulated AE hits

Fitting curve

20

0

AE hits rate (each minute)

1.0x103

Accumulated AE hits

AE hits rate

40

1.5x10

AE hits rate (each minute)

January 12 Blast time 15:56 A=414.69 p=1.00 c=1.73

3

Accumulated AE hits

2.0x103

Accumulated AE hits

60

2.5x103

Accumulated AE hits

80

0

AE hits rate (each minute)

(a)

Accumulated AE hits

AE hits rate (each minute)

100

Accumulated AE hits

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0.0 18:00

Fig. 7. AE activities after blasting and its power-law attenuation characteristics.

4.3. Temporal and spatial evolution laws of mining-induced seismicity

analyzed manually according to the waveform, frequency, and energy, etc. Fig. 11 shows the typical MS signal obtained from filed monitoring. We also performed a location accuracy test of the MS events; the location accuracy was determined to be approximately three meters, which meets the requirement for studying MS activities in the field.

During the entire mining process of the no.21 stope, each blast would strongly disturb the surrounding rock mass and generate a large number of MS events, as shown in Fig. 12. From the spatial distribution of the MS events, the rock mass damage was mainly distributed near the

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1.4x10

-647m level el

4

1.2x10 1.0x10

Total AE hits

MS sensors C t shaft h Cut Cut groove

Not show all The total AE hits is 6.3E+4

4

3

8.0x10

3

6.0x10

Drilling Tunnel

3

4.0x10

No blast

3

2.0x10

0.0

1/12

1/13

1/14

1/15

1/16

1/17

1/18

Bottom Structure

1/19

-707m level Fig. 8. The total AE hits between the time of each blasting to 18:00 (2011.01.12–2011.01.19).

Fig. 10. Layout of the tunnels, arrangement of the MS sensors and mining work sequence: ①, ②, ③, ④ and ⑤ represent the mining sequence.

160

Jan 13

After each blasting, the surrounding rock required a certain time to recover to a relatively stable state, and stress adjustment and redistribution occurred. Before preforming this study, we monitored other stopes by using the MS technique and obtained the MS background, which is approximately five events per day. According to this background MS activity, the time required for the surrounding rock mass to recover to a relatively stable state was approximately twenty days. The MOL fitting results indicated that the MS sequences corresponded to power-law decay characteristics except the first blasting, as shown in Fig. 12. The values of p of the MS sequence of the last four blasting were 0.52, 0.42, 0.55 and 0.41; these values were much smaller than those in earthquakes (Utsu et al., 1995) and in mining-induced Seismicity (Vallejos and Mckinnon, 2010). The much smaller monitoring area (one stope) in this study, compared to the above mentioned studies, may cause the rock mass to return to a stable condition in a short time after mining, resulting in a smaller p value. In addition, the c values of the four fittings varies from 0.27 to 1.21 and have no obviously correlation with parameter p. For MS monitoring in mines, the values of MOL parameters are related to many factors, such as geological conditions, stress state of rock mass and blasting energy. If the values of the three MOL parameters under different mining conditions can be obtained, then the time for the rock mass to recover to a stable state after mining may be determined, thus providing theoretical support for evaluating the rock mass state.

140

T/min

120

T= -3.66D+205.56

100 80

Jan 19

60

Jan 17 Jan 15 Jan 18

Jan 14

40

Jan 12

20 15

20

25

30

35

40

45

50

D/m Fig. 9. Relationship between the blasting distance and the time for rock mass to return to the stable state. Table 3 Blasting date and the usage amount of explosive in no.21 stope. Date

Blasting

Explosive/kg

2013.11.29 2013.12.31 2014.01.28 2014.04.26 2014.06.10

1 2 3 4 5

1780 1900 1880 2520 1820

5. Conclusion In this paper, acoustic emission (AE) and microseismic (MS) monitoring was applied to study the rock fracture process under multileveluniaxial loading, rock mass stability near tunnel and stope after blasting. Omori’s formula from seismology theory was applied to analyze the power-law attenuation characteristics of the AE and the MS sequence of the three-scale rock or rock masses in detail. The AE attenuation law, during the period of constant stress at lower stress level was much different with that at higher stress level. The average p values of AE hits power-law attenuation with the c values were estimated as zero when rock with a lower stress level. When the stress exceeded 50% of the peak strength, the changes of MOL parameters are very complex and there are two cases: larger p values with larger A values and c values, and another is the smaller p values with c values are zero. Before failure of the two rock specimens, the MOL is not applicable, indicating that the rock is close to critical instability state. During the period of constant stress, the generated micro-cracks can be seen as an extension of the previous loading effect and resulted in

mining areas and was especially concentrated at the roof and the two sides of the goaf. On the day of the first blast, a sharp increase in MS events was found, with twenty events generated. Within approximately twenty days after this blasting, the MS activities remained at a higher level, with more than ten MS events every day. Although the MS activities were also remarkable on the day of later blasts, the number of MS events was much less than that of the first blast. For a stope, the rock mass was in a relatively stable state before mining. When the mining process started, the rapid unloading effect caused by a strong disturbance would result in stress redistribution and migration. During the early phase of the mining process, stress was intense redistributed and continued for a long time, accelerating cracks generation and propagation. The disturbance to the surrounding rock mass caused by mining in this phase is larger than that of the later phase. The later phase of the mining process would enhance the range and the extent of stress re-distribution. 310

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1 0

0

-1 -2 4

Channel-13 0.2

0.4

0.6

0.8

1.0

-2

15:41:05.808293 1.2

Amplitude/10-4V

0.2

0.4

0.2

0.4

0.6

0.8

15:41:05.809793

1.0

1.2

0.5

2 0

0.0

-2

-0.5

Channel-15

-4

0.2

2

0.4

15:41:05.814293

0.6

Channel-6

-1.0 0.8 2

0.6

0.8

15:41:05.814804

1.0

1.2

1

1

0

0

-1

-1 -2

Channel-14

1.0

1.4

Channel-4 0.2

0.4

0.6

0.8

15:41:05.817470

Channel-10

-2

1.0

0.2

1.2

0.4

0.6

15:41:05.819554 0.8

1

1 0

0

-1

-1

Channel-2 0.2

0.4

0.6

0.8

15:41:05.819970

1.0

Channel-3 0.2

1.2

0.4

0.6

0.8

1.0

15:41:05.820137 1.2

Time/s

Fig. 11. Typical MS signal obtained from filed monitoring.

Amount of MS events each day

30

1st blast 2013.11.29

4th blast 2014.04.26

2nd blast 3rd blast 2013.12.31 2014.01.28

5th blast 2014.06.10

25

20

15 A=22.51 p=0.52 c=0.96

10

A=18.23 p=0.42 c=1.19

A=17.15 p=0.41 c=0.27

A=19.56 p=0.55 c=1.21

5

0 11/25 12/9

12/24

1/8

1/23

2/7

2/22

3/9

3/24

4/8

4/23

5/8

5/23

6/7

6/22

7/7

7/22

8/6

8/21

9/5

Date (2013-2014, month/day) Fig. 12. Temporal-spatial evolution laws of MS events and its power-law decay characteristics.

Foundation funded project (2017M612302) and the Postdoctoral Creative Funding of Shangdong Province.

internal structure and stress self-adjustment in rock. Therefore, conducting experiments under cyclic loading, including stress keep phases for the Kaiser Effect study, which may change the understanding of effective stress level for in situ stress measurement via the Kaiser Effect. For a local rock mass in a ramp near stope, AE activities showed obvious power-law attenuation characteristics after blasting. The time that the rock mass returned to the stable state has a linear relationship with distance between the blasting area and the monitoring area. The time that the worker re-enters the ramp should be delayed if the work area is close to the blasting area. For the whole rock mass near the stope, the MS sequences corresponded to the Omori’s power-law decay characteristics, and the time of rock mass recovery to a relatively stable state is approximately twenty days. The MOL parameters, i.e., p, c and A, should be comprehensive analyzed for evaluating the rock mass state during mining process.

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Acknowledgements This work was financially supported by the National Key Research and Development Program of China (2017YFC0602904, 2016YFC0801605), The Project supported by National Natural Science Foundation of China (51704056), the Fundamental Research Funds for the Central Universities (N150104004), the China Postdoctoral Science 311

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