44

ABSTRACT 

 There has been a persistent need to forecast roof falls so that 

miner’s exposure to hazardous underground environments can be 

minimized. Several monitoring techniques have been developed 

and are used today with varying levels of acceptance in the mining 

industry. This paper examines the potential for monitoring 

microseismic emissions activity as a means of forecasting roof 

falls. The use of this activity to forecast roof falls has drawn only 

limited attention, resulting in a lack of published field performance 

data. This deficiency is being partially addressed by analyzing data 

obtained during longwall mining at Moonee Colliery in 1998. The 

Moonee data base contains a wealth of information concerning roof 

fall forecast parameters and the seismic alarm criteria used to 

develop these forecasts. Four seismic alarm criteria were 

developed and used by Moonee with varying degrees of success. 

Roof falls were forecasted 73% of the time with average forecast 

times of 54 minutes. Ninety percent of the predicted roof falls had 

a warning time, i.e., the time between warning and roof fall event, 

of greater than 1 minute. The fraction of forecasted roof falls 

decayed logarithmically as a function of warning time, until only 

20% of events were predicted more than 100 minutes prior to roof 

falls. False alarms occurred in 50% of the warnings. Many of the 

false alarms were quickly followed by a cessation in mining which 

could have temporarily halted the on-going failure process. If 

mining had continued immediately after the false alarms, a roof fall 

may have occurred soon after. The microseismic activity collected 

from Moonee Colliery demonstrates that techniques to forecast roof 

rock instabilities in underground mines are possible. 

INTRODUCTION 

 Monitoring technology and techniques to provide early 

warning of hazardous roof fall conditions have been a longstanding 

goal for safety engineers and practitioners working in the mining 

sector. Roof-to-floor convergence monitors are perhaps the oldest 

and most common method of measuring roof deflection as a means 

to detect roof rock instabilities. This type of instrument consist of 

an anchor device mounted on the mine roof and floor and 

connected by a ridged bar or a metal wire. The relative movement 

of the anchor points is measured with either mechanical or electromechanical devices. 

 Multipoint extensometers installed in boreholes have been 

used to detect roof movements and have seen use in the United 

State, the United Kingdom, and Australia (Gale, et al., 1992; 

Siddall and Gale, 1992). Homemade mechanical extensometers, 

consisting of a top and bottom anchor, steel wire or rigid tubing, 

and some kind of micrometer or dial gauge, have been used for 

decades in metal mines in Michigan, Missouri, and Idaho (Parker, 

1973). In 1999, the National Institute for Occupational Safety and 

Health (NIOSH) introduced a modified mechanical extensometer 

called the RMSS which had the added capacity to be read remotely 

(Iannacchione, et al., 2000). Some common commercially 

available mechanical extensometer monitoring devices are the 

Miners Helper and the Guardian Angel (Name brand references to 

a specific product does not imply endorsement by NIOSH). 

 In addition to extensometers, coal mines sometimes use 

telltales to warn miners of strata movement. The telltale was first 

introduced in France during the early 1970’s (Bigby and DeMarco, 

2001). It consists of a rigid bar anchored into the roof. A small 

section of rod protruding from the borehole is monitored to 

determine roof deflection. Altounyan, et al., (1997) found that falls 

of ground in British coal mines were reduced from 267 to six 

between 1990 to 1995, partially due to the use of telltales. 

 All of the instruments discussed are classified as roof 

deflection monitors and are a significant part of any thorough 

ground control plan. Field evaluations have shown (Petersen and 

Shaffer, 2000; Parker, 1973; Maleki and Chaturvedi, 1999) that 

roof deflection measurements aid in monitoring mine opening 

performance and in determining where, and often when, a roof fall 

may occur. At some mines, this kind of information is routinely 

used by operations personnel to assess the stability of localized roof 

rock. Widespread industry acceptance of this technology may be 

limited by the need for extensive and costly instrument coverage. 

Each roof deflection instrument is capable of assessing the behavior 

of only localized sections of the immediate roof. These areas can 

be as small as tens-of-square meters to as great as hundreds-ofsquare meters. Since the average underground mine often 

maintains thousands of square meters of active working areas, very 

large numbers of instruments could be needed to obtain adequate 

coverage. 

 The use of monitoring microseismic emissions to warn of roof 

falls has only had limited investigations. The first evaluation of 

this technology was in the 1940’s by Obert and Duvall (1945a and 

Forecasting Roof Falls with Monitoring Technologies – A Look at the 

Moonee Colliery Experience 

Anthony T. Iannacchione, Senior Scientist

T.S. Bajpayee, Mining Engineer

NIOSH-Pittsburgh Research Laboratory 

Pittsburgh, PA 

John L. Edwards, Senior Consultant 

Collective Experience Pty Ltd 

Newcastle, NSW Australia 
45

1945b) as a means of tracking general stability conditions. Later, 

Leighton and Stebley (1975) demonstrated that increased noise 

rates, from a system capturing events in the 36 to 44 kHz range, 

preceded the failure of a coal mine roof by as much as 15 minutes. 

Unfortunately, the ultrasonic frequencies attenuate rapidly, 

requiring geophone placement very close to roof fall events. These 

kinds of system requirements have presented numerous operational 

issues. 

 Mine-wide microseismic monitoring technology has the 

capability to collect and analyze a share of the total energy released 

as localized strata fractures prior to, during, and after roof falls. 

This technology has the advantage of continuous detection and 

relatively low instrument-to-coverage area ratios. For example, 

geophone coverage areas are likely in the range of hundreds-ofsquare meters. However, microseismic monitoring systems have 

higher purchase costs and their data can be more ambiguous to 

interpret than roof deflection measurements. Perhaps an even 

greater problem is the lack of published field data which supports 

the use of this technology to warn of roof falls. Monitoring 

strategies to implement roof deflection technologies are being 

addressed by many organizations around the world. The use of 

microseismic technology in concert with other monitoring 

technology is currently being addressed in the United States by 

NIOSH. In a related effort, CSIRO is currently examining changes 

in microseismic resonance modes prior to roof falls as a possible 

forecasting tool (King, 2005). 

 It is important to note the differences between the use of 

microseismic technology to detect and warn of roof falls and its 

deployment in many countries around the world to warn of violent, 

dynamic failures of rock. Rock bursts, coal bumps, and gas 

outbursts are associated with large releases of energy, occur in most 

major mining countries, and are a major cause of traumatic injuries 

to mine workers. The literature is filled with examples of both 

successes and failures in using microseismic monitoring technology 

to warn of these intense, but relatively infrequent failures. 

Mitigating these hazards requires practitioners to forecast the areas 

of most risk and, in some circumstances, the time of their 

occurrence. 

 Dynamic failures, by their nature, are associated with a 

significant release of energy, producing large seismic events. 

Forecasting the largest magnitude events, the ones that can do the 

most damage, is the principal focus. The largest events represent a 

very small portion of the total population of microseismic activity 

occurring at any one site. For example, of the 9,580 microseismic 

events collected from the first longwall panel at the Moonee 

Colliery, only one was greater than 2.0 on the moment magnitude 

scale (Figure 1). The moment magnitude scale is roughly 

equivalent to the commonly used Richter earthquake magnitude 

scale. The vast majority of the events are less than 0. The 

difficulty in forecasting these large but relatively rare events is 

obvious. In contrast, forecasting roof falls relies on the total 

population of microseismic events to identify the on-set of the 

collapse. 

 So by analyzing microseismic emission activity and roof 

deflections associated with roof falls, forecasting methods can be 

evaluated. Improving forecasting techniques to detect roof rock 

instabilities in underground mines is seen as a positive step towards 

lowering miner exposure to hazardous environments. 

THE MOONEE COLLIERY AND ROOF FALLS

 NIOSH has embarked on an effort to collect and analyze data 

on the use of monitoring technology to forecast roof falls. One 

study was recently completed at the Springfield Pike Mine in 

Pennsylvania and a second was initiated at the Burning Springs 

Mine in West Virginia. At these underground limestone mines, 

attention is focused on the onset of intense, localized microseismic 

activity that rise-up from periods of relative quiet. These kinds of 

rock failure processes are classified as progressive, indicating that 

once failure is initiated the potential exist for accumulating failures 

that can progress towards a roof collapse (Iannacchione, et al., 

2005). Roof rock failures that are sudden and lack some 

progressive development will most likely be undetectable by 

monitoring techniques discussed in this paper. 

 Roof fall Characteristics - The Moonee Colliery is a longwall 

mining operation in the Great Northern Coalbed of the Newcastle 

Coal Measure, north of Sydney, Australia. Overburden ranges 

from 90 m in the north to 170 m in the south of the mine (Hayes, 

2000). The immediate roof comprises 1.6 m of coal and claystone. 

These layers are overlain by the Teralba Conglomerate with a 

thickness of 30 to 35 m. The massive Teralba Conglomerate is the 

main reason why Moonee’s longwall strata doesn’t continuously 

cave as the longwall face advances. Instead, it can hang in place 

until extensive unsupported spans exist. When it does cave, it can 

fall as a series of impacts well behind the longwall face or as one 

continuous mass (Edwards, 1998). The non-continuous caving of 

the roof is most likely influenced by low overburden, narrow panels 

(<100 m), and strong abutment strength of the adjacent solid 

longwall panels. 

 Roof fall caving events began to occur at Moonee after the 

initial 200 m of face advance within the first longwall panel. Six 

miners were injured on January 22, 1998, from a windblast 

associated with the fifth longwall panel roof fall (Mills and Jeffrey, 

2001). This roof fall produced a fallen material geometry similar to 

half a cone with stepped surfaces (Figure 2). The top of the roof 

fall failure surface arched approximately 16o over the panel from 

the longwall face and the two gate entries, reaching a maximum 

thickness of 15 m in the center of the panel, 35 m from the longwall 

face (Figure 2). The top of the roof fall cavity was comprised of 

both horizontal and vertical planes that formed a step like surface. 

The horizontal planes were most likely associated with local 

bedding structures within the conglomerate while the vertical 

0

2000

4000

6000

<-2 >-2 to -1 >-1 to 0 > 0 to 1 > 1 to 2 >2

Moment Magnitude, M

Frequency

Figure 1. Moment magnitude distribution of microseismic events 

collected during the mining of Longwall Panel No.1 at 

the Moonee Colliery. 
46

planes were associated with the local jointing, spaced a few meters 

apart (Mills and Jeffrey, 2005). Above the fallen material, the 

conglomerate strata continued to bridge across the panel, leaving a 

2 to 3 m high air gap. The back side of the fall, facing the 

previously caved rocks, was approximately parallel to the longwall 

face but arched toward the longwall face. Mills and Jeffrey (2005) 

have indicated that the general pattern described above was typical 

of longwall panel No.1’s roof falls. 

 As a result, when these failures finally occur, they do so over a 

wide area. This type of failure can be thought of as an end member 

of the continuous failure process where the increments, or episodes, 

are very large and not tied very closely to the short-term mining 

rate. With additional mining the failure progresses until the 

overhanging rock mass becomes unstable and falls as a large mass. 

Hence, this type of rock failure is episodic or periodic in nature 

(Iannacchione, et al., 2005). 

 Microseismic Monitoring - Microseismic monitoring occurred 

at Moonee from 1998 until 2002 when a decision was made to 

close the mine, due to factors other than those related to the 

windblast issue. Many researchers worldwide are aware of the 

Figure 2. Generalized sketch of the Jan. 22 roof fall (Fall No. 5), longwall panel No.1, Moonee Colliery. 

Caved zone

Longwall panel

Conglomerate roof rock

Jan. 22 roof 

fall material

Stepped surfaces

Center line of longwall panel Mining direction

16°

15 m

45 m Gate entry pillar

A B

35 m

Caved zone

Longwall panel

Conglomerate roof rock

Jan. 22 roof 

fall material

Stepped surfaces

Center line of longwall panel Mining direction

16°

15 m

45 m Gate entry pillar

A B

35 m

KEY 

Figure 3. Cumulative frequency of microseismic events during the initial phase of monitoring. Note dashed lines symbolize nonsignificant roof falls and continuous lines symbolize significant falls. 

0

250

500

750

1000

1250

1500

1750

2000

12-Feb 16-Feb 20-Feb 24-Feb 28-Feb

Date

Cummulative Frequency .

Events Alarm Roof fall

Roof fall 7

Roof fall 8

Roof fall 9

Roof fall 10

Roof fall 11

Roof fall 12

Roof fall 13

Roof fall 6

Alarms

No 

mining

No 

mining

0

250

500

750

1000

1250

1500

1750

2000

12-Feb 16-Feb 20-Feb 24-Feb 28-Feb

Date

Cummulative Frequency .

Events Alarm Roof fall

Roof fall 7

Roof fall 8

Roof fall 9

Roof fall 10

Roof fall 11

Roof fall 12

Roof fall 13

Roof fall 6

Alarms

No 

mining

No 

mining

KEY 
47

unique site conditions at Moonee and the exceptional field data that 

was collected there. After the mine closed, NIOSH purchased the 

microseismic database and began re-analyzing the data. 

 Microseismic monitoring was introduced to Moonee soon after 

the Jan. 22, 1998 roof fall as a way to predict the onset of caving 

with sufficient warning to enable miners on the longwall face to 

take shelter in a safe location prior to the associated windblast 

(Edwards, 1998). The microseismic system was manufactured by 

ISS International from South Africa and used 14-Hz 3-component 

geophones throughout the study. Four geophones were mounted in 

10 m roof boreholes surrounding the longwall face and 

continuously moved as the face advanced. During the course of 

this multi-year seismic monitoring project, tens-of-thousands of 

seismic events, including numerous roof fall caving episodes, were 

recorded and located (Brink and Newland, 2002; Hayes, 2000). 

 Initial Monitoring - An initial period of microseismic 

monitoring collected 1,903 microseismic signatures from February 

11 until February 28, 1998 (Figure 3). Many of these signatures 

were not located and some may not be associated with rock 

fracturing. Techniques were perfected during this period to 

accurately locate and classify events and to calculate an array of 

seismic parameters. As these techniques developed, the mine 

began to evaluate alarm criteria and formulated a plan for 

managing the microseismic information. 

 Eight roof falls were observed during the initial monitoring 

period (Figure 3). Three were considered significant (Nos. 7, 11, 

and 13, Figure 3). Significant roof falls were defined as those 

events that had an area greater than approximately 2,000 m2

, and 

that had, by calculation, the potential to generate dangerous 

windblast. This definition implies that the roof came down, moreor-less, as one continuous mass. Five of these roof falls (Nos. 6, 8, 

9, 10, and 12, Figure 3) were considered non-significant. In all, 27 

roof falls were classified as significant during the mining of 

longwall panel No.1. The median area of all significant roof falls is 

4,350 m2

. 

 Conversely, 14 roof falls were classified as non-significant. 

With the exception of roof falls Nos. 30 and 34, all non-significant 

roof falls were relatively small with a median area of 460 m2

. 

These two roof falls were deemed non-significant because they did 

not produce a caving event that tripped the windblast monitoring 

device in the main gate entry. However, it is possible that these 

roof falls directed their air blasts into the gob and, therefore, may 

have been significant. Most non-significant roof falls occurred 

before the face advanced 20 m from the last roof fall. 

 A geologist/microseismic operator was responsible for 

processing incoming events and continually updating trends. After 

two false alarms, the first successful alarm occurred 2 minutes prior 

to the roof fall No. 13 (Figure 3). 

MICROSEISMIC ACTIVITY AND ROOF FALL ALARMS 

 After the initial period of microseismic monitoring ended with 

the successful alarm for roof fall No. 13, a seismic alarm criterion 

was implemented to assist in producing actual warnings of roof 

falls that could potentially create windblasts. The actual warning 

alarms issued by the operator were derived from a number of 

different sources including: shield pressure, audible noise, miner 

input, and seismic information. The seismic alarm criterion was 

comprised of four individual computed or appraised criteria: 

• Frequency1 (F1) – based on the capture of 6 events or greater 

in a 10 second period. The computer automatically initiated 

an alarm to the operator. 

• Frequency2 (F2) – based on the capture of 5 multiple events in 

1 minute. Multiple events have more than one distinct 

signature per record. The operator was required to monitor 

event characteristics. 

• Magnitude (M) – based on more than one event with a moment 

magnitude greater than -1.0 in a 2 minute period. Since 68% 

of the events measured during longwall panel No. 1 were 

greater than -1.0 (Figure 1), many events could be considered 

in this criterion. The operator was required to process events 

to determine event magnitudes. 

• Trend (T) – based on interpreted trends in microseismic 

activity, usually focused on changes in four seismic 

parameters. One of these parameters, Apparent Volume, is a 

cumulative indicator of seismic activity based on both the 

frequency and magnitude of successive events. The Energy 

Index, Seismic Viscosity, and Seismic Schmidt Number can 

all be likely indicators for the onset of roof rock failure 

(Mendecki, van Aswegen, and Mountfort, 1999). The 

relationship between the Apparent Volume and the Energy 

Index were key indicators, along with some consideration of 

Seismic Viscosity and the Schmidt Number, to balance the 

problem of wild swings in individual parameters. These 

parameters were displayed in continuously updated system 

history windows available to the operator. 

 During the remainder of mining this longwall panel, 15 

significant roof falls were selected and analyzed (Table 1). These 

roof falls had hanging strata over the longwall gob areas greater 

than 20 m in length. The 20 m face advance was used in the mine’s 

Windblast Management Plan to determine when protective 

measures were required (McDonell, 2001). The seismic alarm 

criteria were used to determine the actual warning 73% of the time 

and produced an average forecast time of 54 minutes, 12 minutes 

better than the average for the operators warning alarm (Table 1). 

The operators alarm types consisted of seismic criteria, shield 

pressure, and audible noises. The frequency criterion (F1) was the 

dominant seismic alarm followed by the magnitude and trend 

criteria. Fifty percent or 15 of a total of 30 alarms were classified 

as false. Many of these may be due, in part, to a cessation in the 

episodic failure process when the longwall was stopped as a 

consequence of the alarm being triggered, i.e., the self-perpetuating 

threshold had not been reached. Since this paper is focused on the 

performance of the seismic activity in forecasting roof falls, the 

following analysis will focus only on the seismic alarms. 

 Plots of success rate of seismic alarms decayed logarithmically 

with increasing forecast time (Figure 4). Ideally a forecast window 

of more than 2 minutes may be needed to give the miners time to 

seek shelter in a refuge area. Refuge areas were provided for every 

second longwall support and at several places along the main gate 

entry (Hayes, 2000). Using this criterion, 80% of the roof fall 

events would have been successfully forecast. Hayes (2000) 

reported that the microseismic system was able to give sufficient 

warning of impending roof falls that could cause windblast in 

approximately 90% of the cases. The frequency and magnitude 

criteria were more important in the short forecast windows while 

the trend-criterion was more important in the longer forecast 

windows. The short forecast windows became the focus of the 

seismic alarms, thereby diminishing attention on improving the 

longer forecasts. 
48

WHAT CAN BE LEARNED ABOUT FORECASTING ROOF 

FALLS FROM THE MOONEE DATA? 

 The Moonee study is important because the episodic rock 

failure processes that were observed there are, in many ways, 

similar to the progressive rock failure that typifies many roof falls 

in underground mines with strong roof rock conditions 

(Iannacchione, et al., 2005). The extraction of longwall coal mine 

panels generally produces strata that cave continuously and lacks 

dramatic changes in microseismic activity (Heasley, et al., 2001; 

Westman, et al., 2001). At Moonee, where episodic rock failures 

are common, the majority of the microseismic activity is apparently 

associated with the initiation and development of the stepped 

failure surfaces (Figure 2). These surfaces eventually define the 

extent of large, distinct roof falls that are similar to that found at the 

Springfield Pike Mine (Iannacchione, et al., 2004). 

 What is striking about the Moonee data is that the seismic 

activity generally increases dramatically, close to the time of the 

roof falls. For example, figure 5 shows the microseismic activity 

during the period after roof fall 30 and just before roof fall 31. The 

seismic activity is maintained at a relatively constant rate, with the 

exception of the idle weekend, until a short time before the roof 

fall. Plots of event locations show a dispersed pattern over the 

most recent longwall gob areas. Most likely this represents the 

continuous development of the stepped failure surface that will 

eventually outline roof fall 31. In the 24 minute forecast period 

between the seismic alarm and the roof fall, an intense period of 

activity occurred within the gob in the area of roof fall 31 

(Figure 5). This flurry of activity probably signals the coalescence 

of many smaller fracture surfaces into larger destabilizing 

structures within the roof rock. 

 This significant change in the rate of seismic activity rate at 

Moonee might be viewed as a transition from a stable to an 

unstable condition, much like what is observed in many progressive 

type roof falls. This point in time can also be considered as the 

start of the roof fall forecast window. These transitional points 

between stable and unstable conditions were observed for almost 

all of the roof falls studied (Figure 6). 

 The precise character of the forecast window starting points 

provides insight into the potential magnitude of rate changes 

expected to signal the onset of a roof fall. At Moonee, the 

background seismicity ranged from 5 to 15 events per hour 

(Figure 7). At the start of the unstable periods the seismicity rate 

at least doubled and in many cases increased by one order of 

magnitude (Figure 7). This data demonstrates the complexity of 

patterns associated with the transition from stable to unstable roof 

rock. 

Table 1. – Characteristics of fifteen selected roof falls 

Actual warning Seismic alarm criteria Roof fall number Type Minute Type Minute No. of false alarms Face advance, m

14 NA 6 F1, F2 1,1 4 67 

17 Seismic 8 F1, F2, T 8,8,8 2 48 

18 Audible 1.5 F1, F2, T 2,2,2 0 41 

19 Seismic 9 F1 9 0 20 

21 Seismic 2 F2, M, T 3, 3, 4 2 97 

23 Audible 2.5 F1, F2, M, T 159,159,159,157 0 95 

25 Seismic 13 F1, F2, M, T 36,36,36,36 4 127 

26 Seismic 1 F1, F2, T 68, 13, 13 0 28 

31 Seismic 24 F1, F2, T 24 0 38 

32 Seismic 209 F1, F2, T 206,206,209 0 30 

33 Shield pressure 139 F1, F2, M, T 158,258,158,158 1 59 

35 Seismic 119 F1, F2, M, T 98,120,98,119 0 27 

36 Seismic 90 F2, M, T 89,81,81 0 109 

39 Shield pressure 0.1 F1, F2, M T 0.1 (all) 0 69 

40 Seismic 0.5 F1, F2, M 1 (all) 2 151 

F1 – Frequency1 criterion 

F2 – Frequency2 criterion 

M –Magnitude criterion 

T – Trend criterion 

NA – not available 

0

25

50

75

100

0.1 1 10 100 1000

Forecast time, minutes

Success rate of forecasted 

roof falls, %

Figure 4. Logarithmic decline of forecast time versus the 

percentage of successfully forecasted roof falls. 
49

0

50

100

150

200

250

300

14-May 15-May 16-May 17-May 18-May 19-May 20-May

Date

Cummulative Frequency .

Events Alarm Roof fall

KEY 

Weekend, no 

mining 

Figure 5. Cumulative frequency of seismic events associated with roof fall 31. The location of events, occurring within the forecast 

window between the seismic alarm and the roof fall, is also shown. 

Figure 6. Cumulative frequency plots for 15 selected roof falls. The idle periods associated with weekends have been removed from the 

data. Roof falls are shown as squares, alarms as circles, and false alarms as triangles. 

0

100

200

300

400

500

600

700

800

900

1000

0123456

Days

Cumulative Frequency .

35

21

36

25

14

33

32

39

23

40

31

18

17

19

26

0

100

200

300

400

500

600

700

800

900

1000

0123456

Days

Cumulative Frequency .

35

21

36

25

14

33

32

39

23

40

31

18

17

19

26
50

SUMMARY AND CONCLUSIONS 

 Monitoring technology and techniques can provide a means to 

warn of hazardous roof fall conditions. Measuring roof deflection 

is the most common method of detecting roof instabilities. These 

measurements aid in monitoring mine roof performance and in 

determining where, and often when, a roof fall may occur. 

Widespread acceptance is limited by the need for extensive and 

costly instrument coverage. The use of microseismic emissions 

activity to forecast roof falls has drawn only limited attention, 

resulting in a lack of published field performance data which 

supports the use of this technology. NIOSH is interested in 

providing microseismic emissions activity and roof deflection 

performance data as a means to address this issue. 

 Two roof fall failure processes were identified that lend 

themselves to early roof fall detection: 

• Progressive failure – periods of quiet are interrupted by the 

onset and progression of microseismic activity and marked by 

significant changes in roof deflection. Both of these 

measurements signal the progress of rock failures that can 

eventually lead to a total roof collapse (Iannacchione, et al., 

2005). 

• Episodic failure – microseismic activity is associated with the 

initiation and development of the stepped-shaped failure 

surface that outlines the eventual roof fall material. The final 

surge in activity is associated with the completion of this 

surface and the collapse of the roof. 

 Roof falls in conjunction with longwall mining at the Moonee 

Colliery were classified as episodic and produced a fallen material 

geometry similar to half a cone with a stepped failure surface. 

Microseismic emissions from 15 roof falls were analyzed during 

the mining of the first longwall panel at Moonee. These emissions 

are apparently associated with the initiation and development of the 

stepped failure surface associated with each roof fall. 

 Four seismic alarm criteria were developed at Moonee. 

Geologists responsible for operating the microseismic system had 

varying levels of input in the generation of these alarms, ranging 

from computer initiated auto alarms to trend analysis requiring 

substantial data interpretation. The seismic alarm criteria were 

used to successfully determine the actual roof fall warning 73% of 

the time and produced an average forecast time of 54 minutes. 

False alarms occurred in 50% of the warnings. Many of the false 

alarms were quickly followed by a cessation in mining which 

temporarily halted the on-going failure process. In many cases, a 

roof fall would probably have occurred if mining had continued 

after the alarm. The seismic alarm forecast times displayed a 

logarithmic decay versus the percentage of forecasted roof falls. 

Frequency based seismic criteria were most important in the short 

forecast windows while the trend based criterion were more 

important in the longer forecast windows. 

 The microseismic activity displayed a rapid increase prior to 

15 roof falls with longwall panel No.1, probably signaling the 

completion of the stepped failure surface associated with each 

individual collapse. This rapid increase in microseismic activity is 

thought of as the transitional point between stable and unstable 

conditions. Background seismicity associated with normal 

longwall advance ranged from 5 to 15 events per hour. At the start 

of the unstable periods, the seismicity rate increased from 2 to 10 

times over the background rate. If these kinds of rate changes can 

be observed in the episodic failure modes at Moonee Colliery, there 

should be a more than reasonable chance for observing similar 

significant rate changes associated with the progressive type roof 

falls that plague many underground mines. 

0

10

20

30

40

50

0:00 1:00

Hours

Cumulative Frequency

23

26

14

33

21

18

35

32

26

17 25

39

31

36

19

40

0

10

20

30

40

50

0:00 1:00

Hours

Cumulative Frequency

23

26

14

33

21

18

35

32

26

17 25

39

31

36

19

40

Figure 7. Cumulative frequency plots for 15 roof falls covering a two hour window. The zero hour indicates the beginning of the 

forecast window where the strata is transitioning from stable to unstable. 
51

ACKNOWLEDGEMENT 

 The authors wish to thank Coal Operations Australia Limited 

for their cooperation and for providing a wealth of information, 

including the Microseismic Monitoring Operators Manual. It 

should be mentioned that the level of effort by mine personnel to 

install and maintain the microseismic system and the care in 

collection and analysis of this data are viewed by the authors with 

respect and admiration. 

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(1997). Instrumentation and Procedures for Routine Monitoring of 

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Proceedings, 27th Intern. Conf. of Safety in Mines Research Inst., 

1997, New Delhi, India, pp. 759-766. 

Bigby, D. and DeMarco, M. (2001). Development of a Remote 

Reading Dual-Height Telltale System for Monitoring Mine Roof 

Deformation. In Proceedings, 20th International Conference on 

Ground Control in Mining, Morgantown, WV, Aug. 7-9, pp. 163-

170. 

Brink, V.Z. and Newland, A.R. (2002). Automatic Real Time 

Assessment of Windblast Risk. ACARP End of Grant Report No. 

C8026. 

Edwards, J.L. (1998). Seismic Monitoring for Windblast 

Prediction, Seminar on Mine Seismicity and Rockburst 

Management in Underground Mines. Australian Centre of 

Geomechanics, Sept. 2-4, Sec. 14, pp. 1-4. 

Gale, W.J., Fabjanczyk, M.W., Tarrant, G.C. and Guy, R.J. (1992). 

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