SME Annual Meeting 

Feb. 25-Feb. 28, 2007, Denver, CO 

1 Copyright © 2007 by SME 

 

AN EVALUATION OF MICROSEISMIC ACTIVITY ASSOCIATED WITH MAJOR ROOF FALLS IN A LIMESTONE MINE: A CASE 

STUDY 

J. Ellenberger, NIOSH, Pittsburgh, PA 

T. Bajpayee, NIOSH, Pittsburgh, PA 

Abstract 

Microseismic monitoring and evaluation is one aspect of the 

National Institute for Occupational Safety and Health (NIOSH) 

research program. Roof falls are often preceded by a period of 

elevated microseismic activity, but not all periods of elevated activity 

result in a roof fall, nor do all roof falls occur after some amount of 

elevated activity. The objective of this study is to review periods of 

elevated microseismic activity and determine whether fracture activity 

rate can be used to anticipate the initiation of roof falls. The study was 

carried out at an underground limestone mine where major roof falls 

are associated with excessive horizontal stress. The progression of 

roof falls was detected by the microseismic signature produced by the 

rock falling from the mine roof onto the mine floor, which is termed a 

roof fall impact event. 

A total of nine elevated fracture activity periods that resulted in 

seven major roof falls were examined. It was observed that elevated 

fracture activity preceded the initial roof fall impact event in three out of 

four major roof falls. The initial impact event was not identified for the 

remaining three roof falls. 

Fracture event rates were analyzed and a roof fall alarm trigger of 

five fracture events in a ten minute time period was established for this 

test case. The fall alarm trigger was tested against six of the elevated 

activity periods. Four roof falls occurred in the six periods of elevated 

activity, and two would have triggered the alarm before the roof fall 

occurred, while two false alarms were generated. 

The results show that limited success would have been achieved 

by the microseismic system as a roof fall alarm trigger. However, the 

trigger would have been successful at warning of the onset of elevated 

activity, allowing mine employees to respond appropriately. 

The study highlighted some issues with implementing such a 

system in an operating mine, including the need for real time 

identification of fracture related microseismic signals among mining 

induced signals, and accurate location and identification of fracture 

clustering. 

Introduction 

This study was conducted under the NIOSH objective to reduce 

traumatic injuries of miners and promote safer workplaces. One of the 

goals of the mine safety program is to reduce ground fall injuries in 

underground mines. One effort focused on the use of roof deflection 

and microseismic emissions to help forecast unstable roof conditions 

(Iannacchione et al., 2004). The microseismic emissions prior to the 

initiation of major roof falls and the progression of roof fall episodes 

were examined at an underground limestone mine in Pennsylvania. If 

miners can detect an area of mine roof that is about to fall, they are 

more likely to take corrective actions and avoid injury. 

The traditional role of seismic analysis has been to locate the 

hypocenter and determine the size of earthquakes or manmade 

tremors. Mining has been recognized for over a century as a cause of 

ground vibrations (Atkinson 1903, Davison 1905). Techniques were 

developed to monitor acoustic emissions resulting from rock fractures 

in mines and laboratory (Obert and Duval 1945a, 1945b). The 

instrumentation to examine the noises was first applied by amplifying 

signals in the audible range so that rock fracture activity could be 

observed in mines. An increase in the rate of microseismic events 

have also been recognized as a precursor to failures of pillars or roof 

(Brady, 1978). More recently, the Goafwarn1

 device made by the 

Council for Scientific and Industrial Research uses light emitting diodes 

mounted on a device that will flash when a preset number of events 

are sensed (Makusha, 2005). 

A roof fall can be viewed as the culmination of deformation and 

rock fracturing events. In elevated stress situations, rock fracturing is 

likely to be a dominant mechanism causing instability. Each fracture 

event serves to create or extend a ruptured surface, thereby 

diminishing roof stability. As more events occur, the roof becomes 

progressively less stable and increases the likelihood of progression to 

a roof fall. 

The microseismic records related to roof falls are rock fracture 

and roof fall impact events. A roof fall impact event occurs when a 

rock strikes the mine floor. Impacts associated with major falls can be 

detected by the geophones located on the roof from vibrations that are 

transmitted through the mine floor and pillars (Iannacchione et al., 

2005). 

An example of a typical geophone trace resulting from a fracture 

event is shown in figure 1. The fracture of the rock produces a signal 

that is sharply defined, and the amplitude generally decays rapidly, 

often in a fraction of a second (Iannacchione et al., 2005). Figure 1 

also shows an example of a geophone trace resulting from a roof fall 

impact event. Impact events differ from fracture events in that they are 

emergent wave forms that are often several seconds in duration. 

Exact locations of impact events are not readily identified from P and S 

wave arrivals. This is because the irregular wave paths and the 

emergent nature of the wave distorts the P and S arrivals, but the 

geophone closest to the event is easily identified, to establish the 

location of the roof fall. Large roof fall impact events can be seen 

across the entire microseismic network. When the initial roof fall 

impact event is identified, the time of the event can be placed among 

the fracture events to show when the initial roof fall occurred relative to 

the fracture activity. 

The objective of this study is to evaluate the potential for 

anticipating major roof failures from the rate of roof fracture events. 

Roof falls are classified as major falls when they extend above the 8 ft 

(2.4m) roof bolted interval. 

Field Site and Microseismic Monitoring Network 

The study site is the Springfield Pike mine, an underground 

limestone mine located in southwestern Pennsylvania. The mine 

produces crushed stone from the Loyalhanna Limestone Formation, 

which is 70 feet (21 m) thick in some areas. The mining zone 

averages 30 feet (9 m) high during development and consists of 

horizontal beds that range from 3 to 5 feet (1-1.5 m), containing widely 

spaced vertical joints, and extensive cross bedding (Iannacchione and 

Coyle, 2002). The Loyalhanna is overlain by the Mauch Chunk 

1

 Mention of company name or product does not constitute endorsement by 

the National Institute for Occupational Safety and Health.
SME Annual Meeting 

Feb. 25-Feb. 28, 2007, Denver, CO

2 Copyright © 2007 by SME 

Formation, consisting primarily of interbedded shales and calcareous 

sandstones, and underlain by the Pocono Sandstone. The intact

strength of the Loyalhanna ranges up to 30,000 psi (200 MPa) 

unconfined strength, but geologic structures and discontinuities can

significantly reduce the overall rock mass strength. Throughout the 

mine, the roof is supported with 8 foot bolts. 

Figure 1. Example traces for a rock fracture (top) and impact (bottom) 

events. 

Roof falls in the mine display the characteristics of falls caused by

excessive levels of horizontal stress (Iannacchione et al., 2001). The 

falls are often elliptical in plan, are initiated by roof guttering similar to 

cutter roof seen in coal mines, and are aligned perpendicular to the

maximum horizontal stress. Hydrofracturing tests at the mine indicate 

the existence of very high horizontal stresses, ranging from 2,200 to

8,000 psi (15 to 55 MPa). 

The monitoring system consisted of 12 uniaxial geophones 

oriented in a North-South direction, mounted on the mine roof 

approximately 30 feet (9 m) above the mine floor. Figure 2 shows the

location of the geophones relative to the study area. The geophones 

were distributed across two active areas of the mine with average 

separations of about 300 feet (90 m). Data acquisition, filtering, and

analysis equipment was located in a trailer, and cables were

connected to the geophones. The sensors connected to the system 

were 4.5-Hz, 630 ohm, uniaxial geophones (Iannacchione et al., 2001). 

The locations and dates of the three major roof falls and the 

extension of two major falls that occurred during this study period are

shown in figure 2. It should be noted that all three major falls occurred 

in an area approximately 300 feet (90 m) wide in an E-W direction by 

500 feet (150m) in the N-S direction. The February 20 fall was 

approximately 130 feet (40 m) long and trended NW-SE. The March 7

fall was approximately 150 feet (45 m) long, trending N-S. The June 

26 fall was the extension of a previous fall, and was the only roof fall 

outside of the 300 foot (90m) by 500 foot (150m area). The October 

28 fall was approximately 170 feet (50 m) long in a N-S direction, and 

the major fall of November 14 extended the October fall approximately 

110 feet (35 m) in a NW-SE direction. 

Approach 

The microseismic records from February through November 2000

were the subject of an earlier report (Iannacchionne et al., 2001). 

Since this original work, improvements in analysis techniques and

software capabilities have identified an increased number of locatable

events. The recognition of roof fall impact events permitted the initial 

episode of a major roof failure to be accurately located in the

progression of fracture events. A series of roof fall impact events are

often identified during the time when the roof is failing, but the first

impact event is significant because it signals the start of the major fall.

However, it must be recognized that smaller undetected fall episodes 

may precede a major roof fall. 

Figure 2. Mine map showing the locations of geophones, three major 

roof falls, two roof fall extensions and dates. 

Because the microseismic records had been reviewed earlier 

(Iannacchione et al., 2001), and periods of elevated activity were 

already identified, the records were examined in two groups. In the

first group, all records were examined to establish normal background

fracture rate and precursor trends associated with roof falls. In the

second group, only records from elevated activity periods were

reviewed. 

The first group included all the microseismic records in a period of 

140 days from July through November 17, 2000, a total of 13,801 

microseismic records. These records were individually classified as

fracture, impact, blast, electrical, or mining induced. From this total, 

670 fracture events were identified and located. Impact events were

also identified and associated with the roof falls that occurred in this 

period. This group of events was then analyzed to establish an alarm

trigger rate for the second group of elevated activity periods. The

trigger rate is the number of events occurring in a specific time window

that may signal the beginning of a roof fall episode.

The second group of data included six periods of elevated activity

from February to July 2000. The first roof fall impact event was 

identified relative to the set of fracture events. This group of events 

was used to test the alarm trigger rate to forecast an impending major 

roof fall. Similarly to the first group, all seismic records were reviewed

in the elevated activity periods, fracture events were identified and 

located, and impact events were identified and associated with roof

falls. The first impact event associated with any roof fall was identified 

and placed in its correct position with regard to time of occurrence.

This group of events was used to test the alarm trigger rate. The 

group included two major roof falls. 
SME Annual Meeting 

Feb. 25-Feb. 28, 2007, Denver, CO 

3 Copyright © 2007 by SME 

Determination of Roof Fall Alarm Trigger 

The cumulative event plot in figure 3 shows the time relative 

occurrence of all 670 rock fracture events that were identified during 

the span of 140 days included in group one. The slope shown in the

center portion demonstrates the typical fracture event background

activity. This period includes 214 fracture events from July 10 through

October 24, a period of 106 days. The steeper slopes on either end 

represent the periods of high activity associated with roof falls in July,

October, and November. Table 1 shows the number of fracture events

that occurred per day in each of the background and elevated periods. 

Figure 3. Cumulative event count from July 2 to November 15.

Table 1. Summary of group #1 quiet and elevated activity periods 

showing the number of events per day and weighted average for 

similar periods.

Dates Activity

Classification

Duration 

(days) Outcome Events per day 

7/2-7/7 Quiet 1 3.9 3.11

7/7-7/10 Elevated 1 2.3 Roof Fall 28.73 

7/10-10/25 Quiet 2 106.0 2.03

10/25-11/2 Elevated 2 3.8 Roof Fall 75.29 

11/2-11/14 Quiet 3 11.2 4.63

11/14-11/15 Elevated 3 1.5 Roof Fall 23.32 

Weighted Average 

Quiet 2.3

Elevated Roof 

Falls 50.9 

Since event frequency is the number of events occurring in a

defined period of time, a matrix was developed including the number of

times a trigger would occur using the first group of 670 events. Time

windows of 5, 10, 15, 30, and 60 minutes were utilized to assess

fracture event rates. From the time an event occurred, it remained in

the count window for the designated time. The 670 events were time 

ordered in a spreadsheet, and the time differences between any given

event and the next six events were calculated. This effectively created

a rolling time window so that the number of events in the time window

at any point in time could be evaluated. The plot in figure 4 shows the

percentage of the time that two to seven events in a given window of

time preceded an initial roof fall impact event. This plot shows that two

or three fracture events in a time window of five to 60 minutes may 

forecast the initial roof fall impact event, but seven to ten false alarms 

would occur for each actual roof fall. When the alarm trigger is 

changed to four events in five minutes or five events in ten minutes,

the percentage of alarms that are followed by roof falls increase to over 

40 percent. Based on this assessment, an alarm trigger was selected 

as the first occurrence of five events in a period of ten minutes. 

Figure 4. Percent of fall alarms that proceeded roof falls vs the

number of events required to trigger the alarm. 

Assessment of Microseismic Alarm Trigger 

The second group of elevated activity periods was then used to

test the effectiveness of the alarm rate of five events in 10 minutes to

forecast the onset of roof falls. Six elevated activity periods were 

evaluated (Table 2). The elevated activity periods were identified 

during earlier analysis (Iannacchione et al., 2001). These six periods 

included three major roof falls, two periods of elevated activity that did

not result in a fall, and one fall that did not extend beyond the roof

bolts. Event records were reviewed for two to three days preceding

and during the elevated activity. Initial roof fall impact events were

identified in two of the roof falls while no impact events were found in

the two other roof falls. 

Table 2. Summary of group #2 elevated activity periods used to test

the effectiveness of the alarm trigger. 

Event 

window 

Number

of events 

Outcome 

category 

Observed 

damage 

Events/

hr

Warning Time, 

minutes 

2/20-2/21 507 1 Roof Fall 14.60 22 

3/7-3/8 66 1 Roof Fall 2.35 131 

4/21-4/22 25 4 No damage 

observed 0.61 N/A

5/27-5/28 51 3 Shallow 

failure 1.25 N/A

6/24-6/25 30 4 No damage 

observed 0.66 N/A

6/26 47 3 Fall 

Extension 2.22 N/A

It was recognized that each of the elevated fracture activity

periods would result in one of four outcomes: 

1. Elevated activity preceding a roof fall with an identifying 

impact event (forecastable falls), 

2. Initial roof fall impact event coinciding with the onset of

elevated fracture activity (roof falls with no microseismic

warning), 

3. Elevated fracture activity associated with a confirmed roof

fall, but without detection of the roof fall impact event, and 

4. Elevated fracture activity that resulted in no roof fall. 

The first category of elevated fracture activity includes roof falls 

that may be anticipated before the major fall occurs. Two of the four 

falls that occurred in group #2 were detected by microseismic activity 

before the initiation of the roof fall. Elevated fracture activity following 

the alarm trigger rate of five fracture events in the ten minute time

period is shown in figure 5 for these two roof falls. The initial roof fall

impact event associated with each fall is also shown on the graph. 

The elapsed time from the initial alarm trigger (the fifth fracture event) 
SME Annual Meeting 

Feb. 25-Feb. 28, 2007, Denver, CO

4 Copyright © 2007 by SME 

February 20-21 fall and 2 hours and 11 minutes for the March 7-8 fall. 

determines the warning time associated with the initial roof fall

episode. For these two falls, the warning time was 22 minutes for the

Figure 5. Event count plot of two major roof falls with recorded initial 

impacts. 

of 55 fracture events were identified in the elevated activity period.

The second category of elevated activity can be classified as roof

falls that are not immediately preceded by elevated microseismic

activity (roof falls with no microseismic warning). In this category 

earlier fracture events may have deformed and weakened the roof,

reducing the number of fracture events necessary to weaken the roof

to failure. Roof falls that occur in this category might also be related to 

geologic structures or discontinuities that have significantly weakened 

the roof before mining (Iannacchione et al., 2001). These falls are

associated with a high level of fracture activity after the fall develops.

The microseismic data has value to the operator in locating the fall

area, especially if it occurs in remote areas. The cumulative event 

count plot for the fall shown in Figure 6 shows an example of a roof fall 

that occurred on July 7-9, which was not preceded by elevated 

microseismic activity. The plot shows typical background activity for 

over 100 hours preceding the fall, followed by a similar trend to that of

the forecasted major falls in the previous category. However, the initial 

roof fall impact event is the third event as the activity elevates. A total 

Figure 6. Cumulative fracture event plot of a roof fall with virtually no

warning. Not

vents were masked from the microseismic system

to record the event. 

e the abrupt change from background to elevated activity. 

The third category of elevated fracture activity is one where a roof

fall is identified by on-site observation, but the microseismic records 

did not include a roof fall impact event. Figure 7 shows the cumulative 

event count of fracture events recorded on June 26, and it is very

similar to the plots seen in association with roof falls in figures 5 and 6. 

Nearly 50 fracture events were recorded between 7 and 11 hours on

the plot. The review of the seismic records showed that the events 

were readily identified as being nearest geophones 3 or 4. A roof fall 

that was observed to have extended to a greater depth on June 26 is 

also near geophones 3 and 4. Since the material that fell from the roof

to extend the fall probably fell on existing rubble, it is reasonable to 

assume the impact e

Figure 7. Cumulative fracture event activity with no identified roof fall 

impact. 

ibute

to those falls described earlier that occur with little or no warning. 

The fourth category, elevated fracture activity that results in no

roof fall, may best be classified as false alarms. In these situations,

fracture events occur, and the frequency may reach that of an alarm,

but the roof reaches equilibrium without having a failure. Figure 8 

shows two elevated cumulative event count periods that were not

associated with significant roof damage. These plots include a small 

number of fracture events following the 5 events in 10 minutes that

classified them as triggered alarms, while the roof falls of February 20-

21 and October 28-29 included 507 and 244 events, respectively. It 

should be noted that the elevated activity seen on June 24-25

preceded the fall extension that occurred on June 26 (category two).

These episodes of elevated activity do represent the development of 

fractures and the continued weakening of the roof, and may contr

Figure 8. Cumulative fracture count of two elevated activity periods 

with no identified impact e

ctivity 

periods rea

Discussi

vents. 

To summarize, the alarm trigger would have provided pre-warning

of the two roof falls in which the initial impact event was known. It is 

not known if the alarm would have triggered prior to the initial impact in

the two remaining roof falls, because these impact events were not

detected by the microseismic system. The final two elevated a

ched the trigger alarm rate and caused false alarms. 

on of Issues Related to Microseismicity and Roof Falls
SME Annual Meeting 

Feb. 25-Feb. 28, 2007, Denver, CO 

5 Copyright © 2007 by SME 

re difficult 

to di

he initial large rock fall 

even

he use of 

a un

roof failure. In this ted 

activity pe

analysis 

show

sing a range of 

time

ods that did not result in roof falls. The other two roof 

falls 

wledge of the location of the elevated 

fractu

ts, b) identification of small roof falls 

prior

tion on the onset and location of elevated fracture 

activity, indicating poten remedial 

actions 

cchione, Ph.D., Principal 

Research Engineer, Rock Sa ing Branch, for constructive 

the f ata. 

Davi

Iannacchione, A Chapman (2005), 

. 

Iannacchione, P.R. Coyle (2002), “An Examination of the 

Iannacchione, A. E., and L. J. Prosser (2001), “Failure 

. 

V, Aug. 

Obert

ines, Report of Investigations 3797. 

Obert, L and W. I. Duval (1945b), “The Microseismic Method of 

Predicting Rock Failure in Underground Mining, Part 2, 

Laboratory Experiments,” Bureau of Mines, Report of 

Investigations 3803. 

Clearly, several issues still need to be addressed to further 

enhance the capability of microseismic systems as roof fall warning 

devices. These issues are discussed below. 

A warning system would have to operate in real time. Less than 

10% of the events that the system recorded were determined to be 

fracture events. Some events generated by mining activity a

stinguish from fracture events and typically occur at the workface. 

A reliable filtering system to automatically exclude these events and 

only consider rock fracture events is required. 

Although roof fall impacts were detected with the microseismic 

system, it is possible that smaller rock falls occurred prior to the initial 

identified impact. The focus was to detect t

t. Since almost any size rock can result in a fatal accident in 

mines where the roof is usually 25 feet or higher, the need to further 

refine the initial failure is a significant problem. 

When a roof fall has occurred, the roof fall may become an 

impediment to the ability to recognize activity that will result in an 

extension of the roof fall. First, the roof in the fall extension area has 

been weakened by fractures that developed at the time of the initial 

roof fall. The preexistence of these fractures weaken the roof to a near 

critical state. Then the critical nature of the roof may render t

iversal alarm trigger impossible. A review of the fracture event 

plots presented in this study shows that the fracture rates during 

recognized periods of elevated activity vary considerably. 

A roof fall warning system needs to address areal clustering of 

events in addition to event frequency rate. Events occurring frequently 

but dispersed over a large area are not necessarily related and do not 

indicate an accumulation of damage in a local area. Conversely, if the 

same events do occur in close proximity, it can indicate an impending

 study it was observed that four of the eleva

riods were clustered around major roof fall locations while 

two were not clustered nor were they associated with a major roof fall. 

Summary and Conclusions 

Elevated microseismic activity was found to be correlated to major 

roof falls at an underground limestone mine where roof falls are 

attributed to high horizontal stress. A total of nine elevated activity 

periods were associated with seven roof falls. A detailed 

ed that elevated microseismic activity preceded three out of four 

of the falls. An evaluation was carried out to determine if the preceding 

microseismicity could be used as a roof fall warning system. 

An alarm trigger was developed using three of the elevated 

activity periods. The background activity rate was also considered to 

limit false alarms. A variety of event rates were tested u

 windows from five to sixty minutes duration. It was found that a 

rate of 5 fracture events in a 10 minute window provided the best 

chance to warn the onset of roof falls at the mine site. 

The developed alarm trigger was tested against the remaining six 

periods of elevated activity, which included four roof falls and two 

periods that did not result in roof falls. It was found that the trigger 

correctly warned of two falls, but two false alarms were generated by 

the elevated peri

triggered alarms, but the time of the roof fall was undetermined; it 

is therefore not known if the alarms would have proceeded the roof 

falls. 

While the alarm trigger showed limited success as a roof fall 

warning system, it would have been successful in warning of the onset 

of elevated fracture activity. Kno

re activities would allow mine employees to take appropriate 

action, such as inspections to determine if the roof has already fallen 

or avoidance of the area. 

The study has highlighted some of the issues related to the use of 

a microseismic system as a roof fall warning device. These issues 

include: a) real time determination of fracture events among large 

numbers of mining induced even

 to the larger impact event recorded by the microseismic system, 

c) identification of the extension of existing falls, and d) quantification 

of areal clustering of events. 

The potential for false alarms and the reality of roof falls that are 

not preceded by microseismic activity are further issues that would 

impede the acceptability of such a roof fall warning system. 

Notwithstanding the above, microseismic systems can provide 

valuable informa

tially unstable roof so that appropriate 

can be planned. In addition, the location of roof fall impact 

events is useful information, especially if they occur in disused areas of 

a mine. 

Acknowledgements 

The authors are indebted to A. T. Ianna

fety Engineer

guidance and direction in conducting this analysis, and T. E. Marshall, 

Engineering Technician (retired) for his dedicated work in maintaining 

ield network and collecting the field d

References 

Atkinson, W.N. (1903), “Report of H.M. Inspector of Mines for the 

Stafford District for the Year 1903.” 

Brady, B.T. (1978), “Prediction of Failures in Mines-An Overview,” 

Bureau of Mines, Report of Investigations No. 8285. 

son, C. (1905), “Earthshakes in Mining Districts,” Geol. Mag, 

Decade V, 2:219-223. 

. T., L. M. Burke and M. C.

“Characterising Roof Fall Signatures from Underground Mines,” in 

The Proceedings, Sixth International Symposium on Rockburst 

and Seismicity in Mines, Controlling Seismic Risk, Australia, 

March 9-11, pp. 619-629

Iannacchione, A.T., P.R. Coyle, L. J. Prosser, T.E. Marshall and J. 

Litsenberger, (2004), “Relationship of Roof Movement and 

Strata-Induced Microseismic Emissions to Roof Falls,” Mining 

Engineering, pp. 53-60. 

 A.T. and

Loyalhanna Limestone’s Structural Features and Their Impact on 

Mining and Ground Control Practices,” in The 21st International 

Conference on Ground Control in Mining, Morgantown, WV, Aug. 

6-8, pp. 218-227. 

 T., Marshall, T. 

Characteristics of Roof Falls at an Underground Stone Mine in 

Southwestern Pennsylvania,” in The 20th International 

Conference on Ground Control in Mining, Morgantown, WV, Aug. 

7-9, pp. 119-125

Makusha, G and D. Minney (2005), “A System to Provide Early 

Warning on Impending Goaf,” in The 24th International 

Conference on Ground Control in Mining, Morgantown, W

2-4, pp. 61-65. 

, L and W. I. Duval (1945a), “The Microseismic Method of 

Predicting Rock Failure in Underground Mining, Part 1, General 

Method,” Bureau of M