Time-Lapse Tomography of A Longwall Panel:
 


A Comparison of Location Schemes
 


Kray Luxbacher, Graduate Research Assistant
 


Erik Westman, Associate Professor
 


Virginia Tech
 


Blacksburg, VA
 


Peter Swanson, Geophysicist
 


NIOSH-Spokane Research Laboratory
 


Spokane, WA
 


ABSTRACT 

Three-dimensional time-lapse velocity tomograms were 

generated to image stress redistribution around a longwall panel to 

produce a better understanding of the mechanisms that lead to 

ground failure. Mining-induced microseismic events provided 

passive sources for the three-dimensional velocity tomography. 

Surface-mounted geophones monitored microseismic activity for 

18 days. 

Most similar studies have utilized active sources including 

longwall shearers, controlled explosions, and hammer blows. 

These active sources generally require a person to initiate and 

measure the location and time of the source, and are not conducive 

to continuous monitoring. This method utilizes mining induced 

microseismic events as passive sources and lends itself well to 

continuous monitoring. 

Two event location methods were compared in order to move 

toward quantification of tomographic results in terms of ground 

conditions. Additionally, LAMODEL was utilized to determine 

the expected stress distribution around the longwall panel and 

compare these images to the velocity tomograms. Eighteen 

tomograms were generated, one per day, and high velocity regions 

in the set of tomograms generated from the initial location 

algorithm correlated with abutment stress redistribution predicted 

by numerical modeling. 

This research is significant as it has the potential to improve 

safety in underground mines and is the only example of long term 

passive velocity tomography implementation for the purpose of 

inferring stress redistribution around an area of active mining. 

Though still immature, this technology has the potential to allow 

mine personnel to image areas of active mining on a regular basis 

and detect areas with anomalous velocity distributions indicating 

potential safety hazards. 

INTRODUCTION 

As the mining industry develops ore deposits in increasingly 

challenging conditions, ground control remains one of the most 

important aspects of mine planning and operation. Three of four 

fatalities that occurred in underground coal and metal/nonmetal 

mines between January I, 2007 and May I, 2007 were the result of 

roof falls ( I). Unplanned roof falls pose a considerable risk to 

miners and can hinder production substantially. Currently, real 

time assessment of roof conditions generally includes visual 

observation, some localized measurements of movement, and, in 

some cases, monitoring of microseismic events (2). 

Seismic tomography allows for inference of stress distribution 

through a velocity image. Seismic velocity tomography is a 

noninvasive technology that can be used to determine rock mass 

response to ore removal. Velocity tomography is accomplished by 

propagating seismic waves through a rock mass to measure 

velocity distribution of the rock mass. Specifically, the P-wave 

arrival time is measured. Tomograms are created by mapping this 

velocity distribution in three dimensions. The three-dimensional 

velocity model can then be sliced in areas of interest, such as the 

active working level, resulting in a two-dimensional tomogram, 

and relative stress in the rock mass can be inferred. 

Velocity tomography is an appropriate technology for the study 

of rockbursts, events that occur in underground mines as a result of 

excessive strain energy being stored in a rock mass, and sometimes 

culminating in violent failure of the rock. Rockbursts often involve 

inundation of broken rock into open areas of the mine, which can 

result in injury, blocked travelways, and unplanned ventilation 

changes. 

This research has the potential to improve safety in underground 

mines by allowing mine personnel to image areas of active mining 

on a regular basis and detect areas where velocity distributions 

seem unusually high or atypical in location. 

BACKGROUND 

Previous Work 

While seismic tomography has been applied frequently in oil and 

gas exploration and in earthquake studies the application is far less 

prevalent in the mining industry. 

When seismic tomography is applied to mining, active sources 

are generally used. Active sources have also been implemented 

repeatedly to image individual pillars in underground mines (3-8). 

Tunnels have also been imaged to determine stress distribution 
 

 

around an excavation implementing both passive (9, 10) and active 

sources (1 1). 

The aforementioned studies are conducted on a relatively small 

scale where active sources and optimum source-receiver placement 

are fairly easy to implement. There are fewer large scale mine 

studies in the literature. Friedel and others used active sources to 

span drifts and image high velocity in working faces (12). 

Rootbolt-mounted receivers have been implemented with a 

longwall shearer as a source to image a section of a longwall panel 

(13). An earlier study was able to image velocity on a longwall 

panel and show that high velocity areas advanced with the longwall 

face (14). 

In combination with an array that surrounds the volume of 

interest, active sources allow for optimal seismic ray coverage. 

Ray coverage is an important parameter in seismic tomography. 

Poor spatial coverage will result in smeared features. Additionally, 

ray density impacts the resolution or sharpness of the image. 

Denser ray coverage provides more data for the velocity model, so 

that each voxel or pixel in the image is better constrained. A large 

seismic wavelength, relative to voxel size, can also have an adverse 

effect on resolution (15). 

Source Location 

Active source tomography is not a realistic option for long-term 

mine monitoring because it is generally labor intensive. The 

method presented here utilizes mining-induced microseismic 

events as passive sources, lending itself well to continuous 

monitoring. However, disadvantages of passive sources are the 

inability to constrain the spatial distribution of sources, and event 

locations depend upon the unknown velocity structure that is 

sought in the model. These disadvantages result in error in source 

location. This error is difficult to quantify and can significantly 

influence the velocity distribution in the tomogram. It is 

imperative that various location schemes be examined to determine 

their effects on velocity tomograms. 

Case Study 

The rock mass under investigation in this research is the strata 

surrounding an underground coal mine in the western United States, 

utilizing longwall mining. Eighteen days of microseismic data 

were collected by NIOSH in 1997. Instrumentation consisted of 

sixteen receivers mounted on the surface approximately 365 meters 

above the longwall panel of interest. The system recorded and 

located the microseismic events. 

The active coal seam is 2.6 to 3.0 meters thick and is underlain 

and overlain by massive sandstone units. The longwall panel was 

250 meters wide and retreated about 431 meters over the course of 

the 18-day study. 

Original Event Location Method 

Initially, event locations were calculated using an iterative 

solution technique with a spatial-gradient basis function (16). A 

minimum of ten P-wave arrival times were used in each solution. 

An initial isotropic layered velocity model was constructed using 

nearby available sonic logs as a starting point. Average velocity 

values and the positions of five model layer boundaries were 

chosen to best approximate the sonic logs. Calculations using this 

initial model located a majority of the events below the seam and 

not in the known layers of sandstone caving directly above the 

seam. With a surface array that is essentially flat, and the use of 

only P-wave arrival times, there is little constraint on the vertical 

position of calculated event locations approximately 365 meters 

below the surface. Therefore, velocity values were subsequently 

adjusted to constrain the median depth of the activity to just above 

the mining horizon. Constraints for these adjustments were 

provided by array-based velocity calibration measurements in nearidentical geologic strata above the same seam in other parts of the 

mine several kilometers away. The resulting model is shown in 

Figure 1. 

2070 

1970 

1870 

1770 

1670 

1570 

1470 

13 70 

2 25 3 35 4 45 

Figure 1. Initial isotropic layered velocity model. 

Double-Difference Event Locations 

Double-difference location (17) refers to the difference between 

calculated and observed seismic travel times for a pair of 

microseismic events. If two microseismic events have very similar 

travel times at all stations then they are defined as a pair, because it 

is assumed that they will also have very similar raypaths. Next, the 

distance between the two events, which, presumably, is much 

smaller than the distance from the event to the receiver, is 

iteratively adjusted to reach a solution which accounts for the 

difference in travel times for the pair while minimizing the 

difference between the calculated and observed travel times. 

There are several examples of double difference relocation in the 

literature (18-19). However, all of these examples are related to 

volcanic and earthquake activity with no specific application to 

mining. 
 

Inversion 

The inversion procedure used to generate the velocity 

tomograms, can only occur once the passive sources, microseismic 

events, have been located. Velocity tomography is based on the 

relationship between time, distance, and velocity of a ray traveling 

through a medium. The mass is discretized and the velocity is 

determined for each discrete unit of the mass, a voxel, in the threedimensional case. 

The principal equation is (20): 

Where T is a matrix of travel times per ray, D is a matrix of 

distances per ray per voxel, and P is a matrix of slowness (inverse 

velocity) in each grid cell. Inversion of the matrix D should allow 

for a relatively simple solution. 

Most tomography problems are ill-posed they have no unique 

solution. This usually results in a singular distance matrix, for 

which there is no inverse, so iterative solutions are often employed. 

Consideration of a priori information allows for the better 

solutions to be chosen. This information often includes an initial 

velocity model determined through exploration of the rock mass. 

This initial model can then be iteratively perturbed until a solution 

is found that fits the data. 

A commercial package was utilized for the inversion of the data. 

The data were inverted using both the initial microseismic event 

locations and the double-difference microseismic event locations. 

GeoTOM implements the Simultaneous Iterative Reconstruction 

Technique, SIRT, to accomplish the inversion (21). SIRT (22) can 

require a large number of iterations, but is generally more stable 

than some of the other iterative techniques. 

The Velocity-Stress Relationship 

In laboratory testing of rocks P-wave velocity increases slightly 

with initial axial stress. Prior to the peak stress the elastic wave 

velocity begins to decrease rapidly as microcracks propagate (23), 

so that an increase in velocity would be indicative of an increase in 

stress, but a decrease in velocity is not necessarily indicative of 

failure - it may be a pre-failure indicator. Thill indicates changes 

in P-wave velocity are largely due to changes in cracks and 

porosity (24). Other factors also affect the P-wave velocity, 

including fluid saturation which can increase the wave speed (25) 

and preferred orientation of cracks which can give rise to velocity 

anisotropy. It is vital that the velocity-stress relationship is 

carefully considered when using velocity tomograms to make 

inferences about relative stress in a mine. 

EXPERIMENTAL PROCEDURE 

The original data set provided microseismic event locations, 

receiver locations and measured arrival times for each sourcereceiver pair. For each event, the first arrival time was set to zero, 

so that the subsequent arrivals were timed relative to the first 

arrival. Travel times through the layered velocity model were then 

calculated for each event-receiver pair. These travel times were 

calculated using TTBOX (26), an algorithm that computes seismic 

ray paths and travel times for a one-dimensional spherical velocity 

model. 

 

For double difference microseismic event locations, the 

calculated travel time data is read into HypoDD (27), a double 

difference event location program developed by Waldhauser, and 

the events are relocated. The original event locations and 

subsequent HypoDD locations are displayed in Figure 2 relative to 

the longwall panel geometry. 

The HypoDD event locations and calculated travel times were 

inverted using a commercial package that utilizes SIRT and 

produces a three-dimensional velocity model. A smoothing 

constant of 0.02 was applied in all directions and 12 curved ray 

iterations were performed for each day. Travel time residuals were 

deemed to be suffiently stable after 12 iterations. The smoothing 

constant constrains the velocity in each voxel in relation to the 

neighboring voxels in order to avoid high or low velocity artifacts 

in areas with poor seismic ray coverage. 

Finally, the three-dimensional model was input into a 

commercial three-dimensional visualization program. In this phase, 

any voxels bisected by less than five rays were removed from 

display. The program interpolates between well constrained voxels 

to determine velocity over the entire model. This also minimizes 

high velocity artifacts in the model which can be misleading. 

The initial set of tomograms, using the first location method. 

were processed in the same way with two exceptions. First, the 

travel times were calculated for straight ray paths, so they are 

probably less realistic than the TTBOX travel times because they 

do not take into account raybending due to velocity change. Also. 

the initial event locations were used for this set. 

RESULTS AND DISCUSSION 

Event Locations 

The initial event locations are shown in gray with the double 

difference locations in black in relation to the pillar geometry and 

longwall face locations in Figure 2. Events are scaled by relative 

magnitude. Mining is retreating from the northeast to the 

southwest. The tailgate is the northern gateroad, while the 

headgate is the southern gateroad. The panel adjacent to the 

tailgate was previously mined. 

The initial event locations are consistently in front of the mining 

face with a few events in the gob and along the tailgate. In days 2, 

5, and 7 the double difference microseismic event locations are 

fairly similar to the initial locations, although they may be more 

tightly clustered. However, the double difference microseismic 

event locations differ significantly from the initial locations on 

days 12, IS, and 18. The microseismic events located by the 

double difference algorithm migrate east into the gob, and on day 

12 they also migrate south over the headgate. The double 

difference microseismic event relocations seem improbable in 

comparison with the initial locations. A previous study of 

microseismic events at a longwall mine in the western United 

States determined that most microseismic events occurred in the 

forward stress abutment zone (28). Although there is significant 

activity in the gob as the roof collapses behind the longwall shields 

these failures are often in tension, and produce far less energy than 

the compressional failures occurring in front of the face. The 

samestudy suggested that these high energy compressional failures 

were more likely to be picked up by the microseismic system (28). 

( I ) 

 

 

Figure 2 does not display the vertical change between the two 

location schemes, but the double difference microseismic location 

algorithm shifted the events toward the surface in all six cases. 

This may account for the lateral shift of events, because the 

distance had to be increased to satisfy the theoretical arrival time. 

Since all of the receivers were surface-mounted this vertical 

location is poorly constrained. 

Seismic Velocity Tomograms 

The velocity tomograms generated from the initial locations and 

from the double difference locations are displayed in Figures 3 and 

4, respectively. These tomograms are plan views, sliced at 

approximately seam level, with the longwall excavation geometry 

overlain. In Figure 3, tomograms generated from the initial 

microseismic event locations, a high velocity zone, represented by 

darker colors, is distinguishable just in front of the longwall face 

and along the tailgate, and is observed to advance with the face. 

The tomograms generated from the events that were located with 

the double difference algorithm display a large area of low velocity 

at the face and tailgate, with a high velocity area visible well in 

front of the face on days 2 and 5, near the left edge of the 

tomograms. These tomograms seem unlikely to represent the true 

state of the rock mass for several reasons. First, days 2 and 5 are 

the only days that seem to exhibit any redistribution of high 

velocity features with face retreat. Additionally, the presence of 

these features on days 2 and 5 is uncertain because there is very 

poor ray coverage in that area of the model, so those voxels are not 

well constrained. Also, because the double difference algorithm 

forced the event locations toward the surface the voxels at seam 

level in Figure 4 are less well-constrained than the same voxels in 

Figure 3. Finally, the double difference microseismic event 

location scheme eliminates events that are relocated above the 

surface and events that are not paired with other events (27). The 

ray coverage for the tomograms in Figure 3 is denser than for the 

tomograms in Figure 4. The number of events used for each set of 

tomograms is displayed below in Table I. 

Table 1. Occurrence of events and number of events 

remaining after the final relocation iteration. 

Day No. of Events 

used in initial 

location 

No. of Events 

used in HypoDD 

location 

2 430 395 

5 591 514 

7 739 589 

12 819 671 

15 1450 1157 

18 666 578 

Also, it is evident in Table1 that ray coverage is substantially 

denser on some days due to the number of microseismic events that 

were recorded. 

There are some substantial limitations in both methods. First, 

the initial isotropic, layered, model is a gross simplification of 

actual ground conditions and does not reflect the low-velocity 

region association with caving and gob areas that advance through 

the rock mass in a time-dependent fashion. Next, calculation of 

event locations and travel times based on this simplified model 

results in systematic errors and eventually leads to distortion in the 

velocity images. 

Numerical Modeling 

Two LAMODEL plots, from days 5 and 12, are displayed in 

Figure 5 to compare the expected stress pattern with the observed 

velocity patterns. The highest stresses are displayed in light colors 

in the forward abutment zone and in the gateroad pillars, especially 

on the tailgate. The LAMODEL plots show the expected forward 

abutment stress, and some tailgate abutment stress. These plots 

appear to correlate more closely with the initial location velocity 

tomograms. 

CONCLUSIONS 

The initial location scheme seems to correlate most closely with 

the LAMODEL plots, and also illustrates velocity redistribution 

with face retreat. The tomograms displayed in Figure 3 are 

probably a more realistic estimate of the state of the rock mass than 

the tomograms displayed in Figure 4. The presence of high 

velocities in the abutment zones, and their subsequent redistribution 

indicates that this technology is promising as a tool for inferring the 

stress state in a mine. 

Additionally, the comparison of the initial microseismic event 

location scheme and the double difference microseismic event 

location scheme indicates that event locations significantly affect 

velocity tomograms. Although the double difference location 

scheme did not generate reasonable event locations this is probably 

a function of the oversimplified initial velocity model than 

evidence of an inappropriate algorithm. Further study of these 

schemes to determine the most appropriate algorithm or algorithms 

for locating microseismic events is vital for creating a viable realtime velocity imaging system in a mine. 

These tomograms do not exhibit the smooth and continuous 

redistribution of stress that might be expected. There are several 

reasons for first, the distribution and number of microseismic 

events significantly affect the images. Since passive sources are 

employed this is not a parameter that can be controlled. Some 

images are generated from more data with better coverage than 

others. Also, a representative sample of the 18 days of data are 

shown here to illustrate the velocity change over the course of the 

study, so tomograms are not displayed for consecutive days. It is 

significant that with the original location scheme high velocity 

features were imaged that can be observed to redistribute with 

longwall face retreat. 


 

 

Figure 5. Plan view LAMODEL stress plots of the longwall 

panel at seam level for days 5 and 12 of the study. The highest 

stresses are represented by the light color in the forward 

abutment zone, and in the gateroad pillars. 

Future Research 

Future research will involve use of TomoDD (29), a program 

that combines the HypoDD location algorithm with an inversion, 

optimizing both the location and the inversion. TomoDD 

simultaneously inverts for the event locations and the velocity 

structure, which mitigates some of the error that occurs as a result 

of using an oversimplified initial velocity model to calculate travel 

times. 

Synthetic tomography of the LAMODEL plots could also yield 

information about the validity of the velocity tomograms exhibited 

here. A synthetic velocity tomogram of the theoretical stress 

distribution displayed in a LAMODEL plot would provide 

information about how stress features might be misrepresented or 

smeared due to inadequate ray coverage. In order to generate 

synthetic tomograms a theoretical velocity-stress relationship must 

be established, and then travel times will be calculated based on the 

actual event locations. Finally, the same inversion process will be 

used to detennine how closely the velocity tomogram models the 

LAMODEL stress plot. 

Successful velocity imaging of stress distribution in underground 

mines could lead to routine imaging of velocity distribution in mine 

roof, providing miners and mine operators with additional 

infonnation about the stress state of the mine and enhancing safety 

and production. 

ACKNOWLEDGEMENTS 

The authors are grateful to NIOSH for providing the data for this 

study. This research is funded by a National Science Foundation 

CAREER Grant (CMS-0134034). 

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