Research ArticleArtificial Seismic Source Field Research on the Impact of theNumber and Layout of Stations on the Microseismic LocationError of Mines

Bao-xin Jia 12 Lin-li Zhou 1 Yi-shan Pan3 and Hao Chen1

1School of Civil Engineering Liaoning Technical University Fuxin 123000 China2Institute of Geology China Earthquake Administration Beijing 100000 China3Liaoning University Shenyang 110036 China

Correspondence should be addressed to Bao-xin Jia 13941855200126com

Received 2 September 2018 Accepted 6 December 2018 Published 22 January 2019

Academic Editor Abdul Aziz bin Abdul Samad

Copyright copy 2019 Bao-xin Jia et al -is is an open access article distributed under the Creative Commons Attribution Licensewhich permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited

A site experiment is performed herein within a 100m range using a high-frequency structure activity monitor to explore theimpact of different factors on the microseismic source location and analyze the range of influence of the velocity model number ofstations and array surface on the seismic source location Moreover the impact of wave velocity velocity-free location algorithmand position of the seismic source on the microseismic location error of mines is discussed by establishing the ideal theoreticalmodel of the wave velocity location and with particle swarm optimization -e impact of the number of stations and tables on thelocation precision is also explored by using the microseismic signals produced by the artificial seismic source -e results showthat for the location model containing the velocity the velocity error would greatly affect the location precision and the velocity-free algorithm receives good location results-e location result is more satisfactory when the seismic source point falls in betweenarray envelope lines -e seismic source location precision is in direct proportion to the number of stations According to theexperiment within a 100m range when the number of stations is over 12 the effect does not significantly grow with the increaseof stations the number of tables affects the location precision and the multitable location effect is significantly superior to thesingle-table effect -e research shows that the optimal station density is 00192 and the appropriate sensor layout to form amultitable monitoring network may effectively enhance the microseismic source precision of mines through the selection of avelocity-free location model On the contrary the number of stations can be reduced on the premise of the allowable error of theseismic source location which may effectively reduce the monitoring cost

1 Introduction

-e shallow coal resource in China has already beenexhausted in recent years hence the shift to deep coalmining is inevitable -e average mining depth of mines inChina has already reached 700m and the number of deepshafts would increase year by year However a morecomplicated and dangerous stress environment would leadto more dynamic disasters in coal mines Mine earthquakeis one of these primary disasters which usually give rise toa series of secondary disasters and result in a tremendousloss of personnel and property -erefore mine earth-quake has become a challenge for both Chinese and foreign

scholars and institutions [1 2] -e microseismic moni-toring system is widely applied in all coal mines [3ndash7] Todate the microseismic monitoring technology has madegreat progress in research and application in the world forexample in analyzing focal mechanisms [8] simulatingthree-dimensional (3D) geological structures [9 10] es-timating rock shear-wave velocity [11] and developingmicroseismic data processing software packages [12]However a prominent unresolved problem in the seismicmonitoring is the large location error Consequentlystudies on improving the microseismic location precisionwould be of great theoretical significance and practicalvalue

HindawiAdvances in Civil EngineeringVolume 2019 Article ID 1487486 11 pageshttpsdoiorg10115520191487486

Most of the current methods of microseismic locationhave been developed from earthquake locations Accord-ingly many scholars conducted studies on the location al-gorithm and how to improve the location precision Severalresearch directions on the decrease of the location errorsuch as the location algorithm [13] velocity model stationlayout [14] and the accuracy of a seismic instrument[15 16] have been presented -urber used the nonlinearNewton iterationmethod for location for the first time Zhaoand Zeng [17] then introduced the simplex method by re-lying on the rapid development of the computer Howeverthe simplex method has defects for instance it may easilyfall in local error Sabbione et al [18] proposed an adaptivefiltering method using the apex-shifted parabolic Radontransform to denoise downhole microseismic data Dong[19] and Li et al [20] proposed the velocity-free locationmethod after considering the impact of the velocity error onthe location precision Afterward Dong et al [21] proposedthe comprehensive location method based on a three-dimensional analysis of the acoustic emission and micro-seismic source in an unknown velocity system Zhou et al[22] proposed the microseismic source location methodbased on the small-region signal pickup Increasing thenumber of stations is considered an effective method ofimproving the location precision hence Gong et al [23]established the principle of determining the optimal numberof channels by aiming at how to determine a proper numberof stations Gong et al [24] believed that six channels couldguarantee the location precision of the seismic source andproposed the anisotropic location method caused by theconsideration of the anisotropic error Lurka and Swanson[25] constructed a model according to the inversion prin-ciple and evolutionary algorithm for a deep coal mine inWestern United States -is author then modified andimproved the seismic location precision with a new targetfunction model and as a result the seismic location pre-cision was evidently enhanced compared with the constantvelocity model -e station layout would affect the locationprecision Kovaleva et al [26] developed a comprehensiveworkflow to optimize the microseismic acquisition designand obtain optimum depth and location for deploying theborehole geophone arrays Chen [27] studied the impact of asubstation network on the location precision After de-termining the optimal number of channels Feng and Lan[28] conducted the optimal channel combiner fixed-pointtest to enhance the microseismic location precision Jia andLi [29] proposed the reduction of the location error byoptimizing the station layout Ruigrok et al [30] designedand applied a temporary array of 38 seismic stations ISanina et al [31] designed and applied a two-dimensionalsmall-aperture seismic array Meanwhile Hu and Li [32]reduced the location error by accurately picking up thevelocity of the P wave Chen et al [33] applied the ranking ofthe P wave to estimate the location error

In conclusion substantial research results have alreadybeen achieved for the microseismic source locationHowever the abovementioned research mainly aims at thealgorithm of a limited number of stations and stationlayout and few comprehensive studies focused on the

impact of comprehensive factors in a high-density stationlayout on the location error In this study an in situ mi-croseismic monitoring experiment is conducted within a100m range for the first time with the high-frequencystructure activity monitor to improve the microseismiclocation precision Moreover the impact of the locationtarget function velocity error seismic source positionnumber of stations and number of tables on the locationprecision is analyzed and studied by applying the theo-retical analysis and field experimentation

2 Microseismic Monitoring Experiment of anArtificial Seismic Source Site

Microseismic monitoring has become one of the effectivemethods of dynamic disaster control for all kinds of minesacross the country but location precision has always been adifficult problem to resolve High-density station monitor-ing is considered an effective solution but research on thistopic is seldom performed in mines Small-range micro-seismic monitoring is performed in this research Moreovera microseismic experiment site is built for the high-densitystation microseismic monitoring experiment which canprovide a theoretical basis for mine earthquake research

21 Introduction to the Experimental Region A gold mine inFuxin was selected for the small-range microseismic mon-itoring experiment -e geographic coordinates of the mineare as follows east longitude 121deg43prime04Primendash121deg43prime06Prime andnorth latitude 41deg53prime03Primendash41deg53prime04Prime -e surface soil of thecoal mine is mild clay and rocks in the mine mainly includebiotite plagioclase mylonite and felsic mylonite which aresolid and of good integrity -e mines are explored throughvertical and inclined shafts in a single cage with a balancedweight Coal mining currently has four midlevels namelymid-223m mid-180m mid-140m and mid-100m Amongwhich the first (mid-223m) has already been emptied andabandoned -e top-down horizontal sublevel miningmethod is adopted according to the status of mine pro-duction and the hoisting condition of the ore body Un-derground mining is being adopted at the present andvertical shaft-blind inclined shaft is employed for codevel-opment based on the full utilization of the original devel-opment system A vertical shaft is employed fortransportation from the surface to 180m below the groundwhile an inclined shaft is adopted from 180m to 140m and180m to 100m plane -e experiment section is the plane of140m 180m and 100m

22 Monitoring Instrument Experiment monitoring in-cludes sensors cables a 12-channel data hub and a 48-channel data recorder for constructing the physical de-formation site (Figure 1)-e sensors used in the experimentadopt a direction-free setting Sensors feature high sensi-tivity hence the data acquisition frequency can be set as100000Hz at the maximum While recording the micro-blasting signal in the experiment the sampling frequency isset to 25 kHz

2 Advances in Civil Engineering

23 Array Layout Sensors were mainly laid out in threeplanes and two inclined shafts -e vertical size of thedistribution region was 80m while the horizontal size wasbetween 100m and 200m -e array mainly consisted of 33sensors Table 1 shows their location informationFigures 2ndash4 depict the planar layout of the sensor Figure 5shows the space layout of the sensors

24 Microblasting Seismic Source -ree microblasting ex-periments were performed and the blasting location was setin three operation planes A monitoring station was set nearthe artificial seismic source to precisely collect the seismicmoment -e arrival time difference of this station and theother monitoring stations was calculated and became thetravel time of the seismic signal spent in reaching the de-tection station Table 2 presents the artificial seismic sourcecoordinates amount of explosive and the signal waveformrecorded Figure 5 illustrates the spatial arrangement of theartificial microseismic source

-e monitoring result showed that only the No 2blasting at the 140m plane and the No 3 blasting at the100m plane were well received -e No 1 seismic signal atthe 180m plane and the effective acceptance amount ofstations were quite dissatisfactory and thus abandoned -eanalysis implied that this finding may be caused by theremote seismic location the small amount of explosive andthe dense transportation channels which affected the signaltransmission from the artificial seismic source to all thesensors Figure 6 shows the signal received by all stationsafter the second and third blasting -e picked up signalswere filtered Subsequently onset time picking was thenconducted which was not elaborated here because of thelength limit

3 Seismic Source Location Algorithm

31Modeling Suppose the microseismic monitoring regionis a cubic area of which the side length is 1000m-e sensorsare distributed at the eight vertexes whose coordinates (unitm) are A (0 0 0) B (1000 0 0) C (1000 1000 0) D (0 10000) E (0 0 1000) F (1000 0 1000) G (1000 1000 1000) andH (0 1000 1000) -e equivalent velocity of the wave

transmission in the medium in the theoretical model issimplified as V 5600ms to make it convenient to explorethe impact of different factors on the location error -ecentral point O of the monitoring region is (500 500 500)-e location effect worked out for the seismic source withinand without the region is studied After the artificial seismicsource coordinates and the velocity are given the arrivaltime from the artificial seismic source to the sensors isworked out by supposing that the artificial seismic source isstirred at 0 moment and taken as the true value -e locationcalculation is then performed with the arrival time -ecoordinates of seismic source points 1 to 11 are (500 500500) (400 400 400) (minus500 minus500 minus500) Artificialseismic source points 1ndash6 are within the envelope line of themonitoring region (ie AG line) while points 7ndash11 arebeyond the envelope line (ie extending line of AG) -earrival time from the artificial seismic source points to allsensors is 01ms as the minimum unit in the round-offmethod to simulate the error caused by the onset timepicking Figure 7 shows the model

32 Location Algorithm Particle swarm optimization is anemerging evolutionary algorithm which constantly collectsthe direction and speed of search according to the flightcourse and information transfer between swamps -esearch process is mainly accomplished by relying on theinteractions and the mutual influence of particles featuringeasy implementation fast convergence and high precision-e free flight of ldquoparticle swarmrdquo in the solution space canperfectly resolve the problem of the final solution being thelocal optimal solution -e updated versions of the speedand the location of particle i are shown in the followingequations

Vid wVid + c1r1 Pid minusXid( 1113857 + c2r2 Pgd minusXid1113872 1113873

Xid Xid + Vid(1)

where w is the inertia weight c1 and c2 are the integralsranging between [2 4] known as the learning or acceleratedfactor r1 and r2 are the random numbers between [0 1]known as the maximum inertia weight and minimum inertiaweight respectively d 1 2 3 D where D stands for

(a) (b)

Figure 1 Site monitoring equipment layout (a) Data recorder (b) Data hub

Advances in Civil Engineering 3

the dimension of the solution vector Vid Xid Pid and Pgd

are the flight speed of particle i in the dth dimension spacelocation optimal solution searched and optimal solutionsearched by the swamp

-e location was worked out through the MATLABPSO toolbox with the following PSO parameter settingslearning factor c1 c2 2 inertia weight r1 09 r2 04number of particles 20 w 1 and end condition maxi-mum number of iterations 20000 or ε 1e minus 25 Whenthe velocity is known V 5600ms and D 3 MeanwhileD 4 when the location is worked out with the unknownvelocity

321 Impacts of the Location Methods on the Location-is study located the two target functions of the knownwave velocity and the unknown wave velocity through theion swarm algorithm to explore the effects of different lo-cation methods on the location error Equation (2) is thetarget function for solving the known wave velocity local-ization and equation (3) is the target function for solving the

unknown wave velocity localization Figure 8 shows thelocation result error

f min1113944n

i1Δ1113954tij minusΔtij1113872 1113873

2 min1113944

n

i1ti minus tj minus

li minus lj

v1113888 1113889

2

(2)

f min ti minus tj1113872 1113873vminus li minus lj1113872 1113873

(3)

Figure 8(a) illustrates that with the known wave ve-locity the errors in the x y and z directions tended toincrease with the source point away from the center of themonitoring station envelope -e error presented a jumpchange when the unknown wave velocity was used for thelocation with the location error of each source pointgetting farther and farther away from the center point ofthe monitoring station -e location error was smaller inthe area -e error outside the area also increased whenthe distance increased and became greater than the lo-cation error of the known wave velocity Figure 8(b)depicts a large difference of the location error between

Table 1 Sensor location information

Plane NumberData hub andinterface serial

number

Sensornumber

Coordinates (m)

X Y Z

180m plane 6 1

3 180103 8835730 6146960 1808164 180104 8832982 6121473 1807605 180105 8851786 6124607 1807406 180106 8854521 6108712 1806757 180107 8879863 6114670 1809688 180108 8834896 6103363 180469

Short inclined shaft 3 19 110101 8883636 6197365 15035510 110102 8878167 6185213 15628511 110103 8867835 6160976 169305

140m plane 12 2

1 140201 8860325 6241630 1413532 140202 8879256 6235671 1396503 140203 8902053 6225357 1395904 140204 8924206 6221107 1395505 140205 8924527 6201975 1396086 140206 8918945 6182133 1397237 140207 8908220 6174085 1397168 140208 8919876 6314837 1399259 140209 8927746 6244410 13958010 140210 8932245 6261876 13961911 140211 8932629 6279137 13962812 140212 8922516 6308026 139820

100m plane 6 3

1 100301 8851300 6321265 1000702 100302 8858368 6321290 1017963 100303 8868516 6315367 1003984 100304 8882840 6324850 1010105 100305 8925043 6335871 1005216 100306 8894740 6323830 100150

Long inclined shaft 6 3

7 111301 8838087 6170980 1711568 111302 8840036 6193240 1603059 111303 8841736 6212716 15079310 111304 8845730 6264803 12588011 111305 8847221 6284368 11583012 111306 8848507 6308935 103820

4 Advances in Civil Engineering

the known and unknown wave velocities which cannotreect the actual geologic wave velocity e inuences ofthe two location methods on the location error were notobvious when the wave velocity error was not consideredHowever the variation trend of the location error wasdierent

322 Inuences of the Wave Velocity Error on the Locatione P-wave velocity of the rock samples in the experimentalarea was rst required to be determined by an ultrasonicvelocity meter based on the known wave velocity model forthe location Dierences between the given wave velocity andthe actual wave velocity were observed erefore the errorsthat are plusmn2 plusmn5 plusmn10 and plusmn15 are applied to disturb the

original wave velocity V 5600ms and take it as the truevalue of wave velocity A disturbance error greater than 0implied that the actual wave velocity was less than V oth-erwise the actual wave velocity was greater thanVe arrivaltime was calculated and taken as the initial value of the lo-cation calculation together with V 5600ms to verify theinuences of the wave velocity error on the location Figure 9shows the location distance error of each articial seismicsource under dierent wave velocity error disturbances

Figure 9 also depicts that the wave velocity error has agreat inuence on the location performance when the knownwave velocity was used for the location e location error ofeach source point increased in line with the increase of thewave velocity error when the actual wave velocity was less thanthat used for the location Meanwhile the location error of

180107180108

Verticalsha 180106

180m plane

180105110103

Short inclinedsha

110102110101

140m plane

140202

140201140m plane

111304

111305

111306

100301100m plane

111303

111302

111301

180103

180104180m plane

Long inclinedsha

Figure 2 180m plane and inclined shaft sensor layout

140206 140205 140204 140209 140210 140211140212

140208

140207Short inclined shaft

110101

Long inclined shaft

111303111304

140201

140202

140203140m plane

Figure 3 140m plane sensor layout

Advances in Civil Engineering 5

each source point inside the area increased in line with theincrease of the wave velocity error when the actual wavevelocity was greater than that used for the location e lo-cation error of each source point outside the area was greaterthan that inside the area that approximately showed an ex-ponential increase with the increase of the wave velocity errore error brought by a lower location wave velocity wasgenerally larger with a greater inuence on the location

323 Inuences of the Source Position on the LocationFigure 10 clearly shows that the location error of each sourcepoint inside and outside the monitoring area was

signicantly dierent e location error increased in astraight line with the enlarged distance from the centralpoint inside the area when the actual wave velocity wasgreater than location wave velocity and the disturbed valuewas less than minus5 e change rate of the error suddenlybecame higher from source point 6 (ie the demarcationpoint between the inside and the outside) and then becamelower Its position of becoming smaller became farther andfarther away with the decrease of the disturbed value Inaddition the change rate of the error eventually tended to bestable e disturbed value was greater than 5 when theactual wave velocity was less than the location wave velocitye location error rst increased and then decreased withthe enlarged distance from the central point inside the areaand gradually increased again with a more enlarged distancefrom the demarcation point e location error was verysmall when the disturbed value was plusmn2 is error slowlyincreased in a straight line inside the area but remainedstable outside the area e inuences of the source positionon the location are suggested to be interfered by the wavevelocity error With the great error in the wave velocity thelocation error changes could be divided into the three fol-lowing areas from the central point of the area (Figure 10)near enlarged mutation and far enlarged areas e changetrend of the location error changed within themutation areaFurthermore the range and the changing characteristics ofthe mutation area depended on the wave velocity error

4 Analysis on the Influences of the Quantity ofStation Planes and Stations on theLocation Error

e particle swarm algorithm was applied to undertake thesource location to the microexplosion performed on the sitee location parameters are as follows location area co-ordinates X [8800 9000] Y [6100 6400] and Z [95185] e eective arrival time was adopted for the locatione ultrasonic testing indoor showed that the P-wave ve-locity of the rock samples of the experimental diggings was6357ms e unknown wave velocity was adopted for themicroexplosion source location to avoid the inuences of thewave velocity error on the location performance

41 Inuences of the Quantity of Station Planes on theLocation Dierent station sensors including 180m plane140m plane 100m plane inclined shaft (long and shortinclined shafts) and some plane sensors were successivelyapplied for the location to analyze the high-density array forthe location performance of microseismic monitoring eunknown wave velocity location was adopted for a betterlocation performance (Figure 11) When the single stationplane was used for the location the source location was moreaccurately realized only when the source was located on ornearby the monitoring plane e single location of themonitoring plane far away from the source would have anextremely great error especially the vertical location errorWhen the sensor of the 140m plane was adopted for thelocation of the 100m plane its vertical error unexpectedly

100305

100306

100304

100m plane

100302

100301111306

Long inclined shaft

100303

Watertank

Figure 4 100m plane sensor layout

190

180

170

160

150

140

130

120

110

1006400

6300 62006100 8950 8900 8850 8800

Artificial source180m planeShort inclined shaft

140m plane100m planeLong inclined shaft

Figure 5 Sensor and articial source space layout

6 Advances in Civil Engineering

reached 51m and the vertical distance between the two planeswas only 40m e location performance was obviouslygreater than that of the single plane when two monitoringplanes were applied for the location However this value wasstill less than that in the location with all the sensors usedisnding illustrates that the increase of the sensor ldquoarray planerdquocould largely reduce the location error with a positive andstimulating inuence on the microseismic location

42 Inuences of the Station Quantity on the LocationFour sensors were selected from all the sensors in the arrayto verify the impact of the monitoring array density on the

location performance and avoid locating in a single planee sensors at the other positions were successivelysuperimposed to select dierent sensor quantities andperform an unknown wave velocity location for themicroblasting on the 140m plane ree sets of data wereselected to take the mean value for the location Figure 12shows the resulting location errore left gure depicts thatthe sensor quantity plays a positive role in improving thelocation accuracy of the source e location errors becameincreasingly smaller as the sensor quantity increased ederivation was taken for the location error to obtain thevariation trend curve of the error As shown in the right sideof Figure 12 the location error decreased with the increase ofthe sensor quantity when the sensor quantity was between 4and 14 e value change of the derivative then became slowbut was still less than 0 thereby indicating that the increaseof the sensor quantity can improve the location perfor-mance which proves that the high-density array is benecialto control the microseismicmonitoring accuracye sourcelocation error of the whole array was approximately 26me mathematical relationship between the location errorΔL and the sensor quantity n was obtained as shown inequation (4) based on the tting of the location error data inthe guree correction determination coecient Adj R2 098972 which shows that the tting result is very close tothe real situation rough this equation an exponentialrelationship can be found between both

ΔL 251999 times eminus(n2343) + 3166 (4)

In the above calculation the P-wave velocities of the140m plane and the 100m plane obtained from the

Table 2 Microblasting source

Seismic source no Location Number Explosive amountCoordinates (m)

Example of the signal waveformX Y Z

1 180mplane 1 300 g 8882635 6127475 181028

2 140mplane 1 300 g 8917753 6171168 139620

3 100mplane 1 400 g 8870609 6316663 100096

2000 800060004000

3

1

ndash3

0

ndash1

t (ms)

v (m

ms

)

(a)

2000 800060004000

3

1

ndash3

0

ndash1

t (ms)

v (m

ms

)

(b)

Figure 6 Microblasting signal (a) No 2 seismic source signal at the 100m plane (b) No 3 seismic signal at the 140m plane

C

YDA

B

X

GF

E H

Z

Figure 7 Model of the monitoring region

Advances in Civil Engineering 7

inversion of the whole array were 5898ms and 5903msrespectively which were rather dierent from the results ofthe indoor experiment In addition compared with themodel analysis results the location error of the actualmonitoring was larger and related to the complexity of ageological structure e location size and direction ofvarious discontinuity surfaces such as fractures joints andfaults in the rock mass all inuence the wave propagation inthe medium Inevitably errors were found in the arrival timerequired for the location because the time was acquired fromthe waveform recorded in the noise environment throughphase identication On the one hand the high-density arraymicroseismic monitoring can extend the quantity of thearrival time data to reduce the signicant impact of thearrival time error On the other hand the high-density

station especially when being three-dimensionally laiddecreases the travel time distance from the source to thevarious sensors and reduces the dierence between spaceand time and the theoretical calculation of the travel timedata caused by the inhomogeneity of the rock mass Insummary benetting from the two abovementioned pointsthe high-density station can eectively improve the locationperformance of the microseismic source of the mine

5 Conclusions

e following conclusions are obtained from this study

(1) eoretical modeling was used herein to analyze thetarget function with the wave velocity nonwavevelocity and source location performance Conse-quently the wave velocity error had a great inuence

100806040200

ndash02ndash04ndash06ndash08

Loca

tion

erro

r (m

)

0 2 4 6 8 10 12Source point

Error in z directionError in y direction

Error in x directionDistance error

(a)

Error in z directionError in y directionError in x direction

Velocity errorDistance error

1 2 3 4 5 6 7 8 9 10 11

0806040200

ndash02ndash04ndash06

1816141210

Loca

tion

erro

r (m

)

6040200ndash20ndash40ndash60ndash80ndash100ndash120

Vel

ocity

erro

r (m

s)

Source point

(b)

Figure 8 (a) Location error distribution under the known wave velocity (b) Location error distribution under the unknown wave velocity

900

800

700

600

500

400

300

200

100

ndash100

0

Loca

tion

erro

r (m

)

ndash15 ndash10 ndash5 0 5 10 15Wave velocity error ()

Seismic source 6

Seismic source 1Seismic source 2Seismic source 3Seismic source 4Seismic source 5

Seismic source 7Seismic source 8Seismic source 9Seismic source 10Seismic source 11

Figure 9 Location distance error distribution of dierent wavevelocity errors

1 2 3 4 5 6 7 8 9 10 11 12

Loca

tion

erro

r (m

)900850800750700650600550500450400350300250200150100

500

ndash50ndash100 Source point

ndash15ndash10ndash5

02

ndash2 51015

Figure 10 Location distance error distribution of dierentpositions

8 Advances in Civil Engineering

on the location result in the target function with thewave velocity and such inuence exponentially in-creased e positioning error was small when thesource point was at the envelope center of themonitoring array e error was larger when thesource point was outside the envelope

(2) e inuence of the station density on the locationerror was analyzed by a eld experiment e ex-perimental results indicated that the inuence of thestation density can be divided into two parts station

quantity and station plane quantity e locationaccuracy signicantly increased with the increase ofthe station quantity when the station plane quantitywas certain When station quantity was more than12 such an increase was no longer obvious Whenthe station quantity is certain the increase of thestation plane quantity can signicantly improve thelocation accuracy e accuracy of the multistationplane was higher than that of the single-station planee best station density was 00192

Loca

tion

erro

r (m

)160

140

120

100

80

60

40

20

0Wholestations

180mplane

140mplane

100mplane

180mplane

+ 140mplane

Shortinclined

sha

Longinclined

sha

(a)

0

5

Loca

tion

erro

r (m

)

35

30

25

20

15

10

Wholestations

180mplane

140mplane

100mplane

180mplane

+ 140mplane

Shortinclined

shaft

Longinclined

shaft

(b)

Figure 11 Relationship between the location error and the sensor position (a) 100m plane seismic source location error (b) 140m planeseismic source location error

2 4 6 8 10 12 14 16 18 20 22 24 26 28 30

50

40

30

20

10

0

Loca

tion

erro

r (m

)

Number of stations

Location errorFitted location errorWhole array location error

(a)

40

ndash2

ndash4

ndash6

ndash8

ndash10

ndash12

6 8 10 12 14 16 18 20 22 24 26 28 30

Derivative

(b)

Figure 12 Relationship between the location error and the number of stations

Advances in Civil Engineering 9

Data Availability

-e data used to support the findings of this study areavailable from the corresponding author upon request

Conflicts of Interest

-e authors declare that there are no conflicts of interestregarding the publication of this paper

Acknowledgments

-e authors would like to express their gratitude to all thosewho helped them during the writing of this thesis First of allthe author is grateful for the site and technical support of themanager and technical staff of the Fuxin Xinmin gold mineSecond the authors are thankful to the postgraduates ofLiaoning Technical University for their help in the experi-ments Lastly the authors would like to thank Editage(httpwwweditagecn) for the English language editing-is work was supported by the National Natural ScienceFoundation of China grant no 51774173 the NaturalScience Foundation of Liaoning Province China grant no201602351 and the Open Fund for the State Key Laboratoryof Seismological Dynamics grant no LED2015B01

References

[1] S J Gibowicz and A Kijko An Introduction to MiningSeismology Academic Press Inc New York NY USA 1994

[2] Y M Yin F X Jiang G X Xie et al ldquoRelation between coal-rock failure andmethane emission based onmicroseismic anddynamic stress monitoringrdquo Journal of Mining and SafetyEngineering vol 32 no 2 pp 325ndash330 2015

[3] A-y Cao L-m Dou G-x Chen S-y Gong Y-g Wang andZ-h Li ldquoFocal mechanism caused by fracture or burst of acoal pillarrdquo Journal of China University of Mining andTechnology vol 18 no 2 pp 153ndash158 2008

[4] Y S Pan Y F Zhao F H Guan et al ldquoStudy on rockburstmonitoring and orientation system and its applicationrdquoChinese Journal of Rock Mechanics and Engineering vol 26no 5 pp 1002ndash1011 2007

[5] L M Dou J He S Y Gong et al ldquoA case study of micro-seismic monitoring goaf water-inrush dynamic hazardsrdquoJournal of China University of Mining and Technology vol 41no 1 pp 20ndash25 2012

[6] X F Xu L M Dou A Y Cao et al ldquoEffect of overlying stratastructures on rock burst and micro-seismic monitoringanalysisrdquo Journal of Mining and Safety Engineering vol 28no 1 pp 11ndash15 2011

[7] S Y Gong L M Dou A Y Cao et al ldquoStudy on optimalconfiguration of seismological observation network for coalminerdquo Chinese Journal of Geophysics vol 53 no 2pp 457ndash465 2010

[8] L Fojtıkova V Vavrycuk A Cipciar and J Madaras ldquoFocalmechanisms of micro-earthquakes in the dobra voda seis-moactive area in the male karpaty mts (little carpathians)Slovakiardquo Tectonophysics vol 492 no 1ndash4 pp 213ndash229 2010

[9] J Rhie and D Dreger ldquoA simple method for simulatingmicroseismic HV spectral ratio in 3D structurerdquo GeosciencesJournal vol 13 no 4 pp 401ndash406 2010

[10] K B Danilov and B Konstantin ldquo-e structure of the onegadownthrown block and adjacent geological objects accordingto the microseismic sounding methodrdquo Pure and AppliedGeophysics vol 174 no 7 pp 2663ndash2676 2017

[11] A V Gorbatikov A V Kalinina V A Volkov J ArnosoR Vieira and E Velez ldquoResults of analysis of the data ofmicroseismic survey at lanzarote island canary Spainrdquo Pureand Applied Geophysics vol 161 no 7 pp 1561ndash1578 2004

[12] D V Popov K B Danilov R A Zhostkov Z I Dudarov andE V Ivanova ldquoProcessing the digital microseismic recordingsusing the data analysis kit (DAK) software packagerdquo SeismicInstruments vol 50 no 1 pp 75ndash83 2014

[13] A Auger and N Hansen ldquoPerformance evaluation of anadvanced local search evolutionary algorithmrdquo in Proceedingsof the 2005 IEEE Congress on Evolutionary Computation no2 pp 1777ndash17842 Edinburgh Scotland September 2005

[14] Y Sato and D Skoko ldquoOptimum distribution of seismicobservationpoints IIIrdquo Bulletin of the Earthquake ResearchInstitute University of Tokyo vol 43 no 1 pp 451ndash457 1965

[15] A T Ringler T Storm L S Gee C R Hutt and D WilsonldquoUncertainty estimates in broadband seismometer sensitiv-ities usingmicroseismicsrdquo Journal of Seismology vol 19 no 2pp 317ndash327 2014

[16] A T Ringler R Sleeman C R Hutt et al Seismometer Self-Noise and Measuring Methods Springer Berlin Heidelberg2015

[17] Z Zhao and R S Zeng ldquoA method for improving the de-termination of earthquake hypocentersrdquo Chinese Journal ofGeophysics vol 30 no 4 pp 379ndash388 1987

[18] J I Sabbione M D Sacchi and D R Velis ldquoRadontransform-based microseismic event detection and signal-to-noise ratio enhancementrdquo Journal of Applied Geophysicsvol 113 pp 51ndash63 2015

[19] L J Dong ldquoMathematical functions and parameters formicroseismic source location without pre-measuring speedrdquoChinese Journal of Rock Mechanics and Engineering vol 30no 10 pp 2057ndash2067 2011

[20] J Li Y T Gao Y L Xie et al ldquoImprovement of microseismiclocating based on simplex method without velocity measur-ingrdquo Chinese Journal of Rock Mechanics and Engineeringvol 33 no 7 pp 1336ndash1346 2014

[21] L J Dong X B Li J Ma et al ldquo-ree-dimensional analyticalcomprehensive solutions for acoustic emissionmicroseismicsources of unknown velocity systemrdquo Chinese Journal of RockMechanics and Engineering vol 36 no 1 pp 186ndash197 2017

[22] M B Zhou J X Wu and W Zhang ldquoMicroseismic sourcelocation method based on small area signal pickuprdquo Safetyand Environmental Engineering vol 22 no 5 pp 154ndash1572015 in Chinese

[23] S Y Gong L M Dou X P Ma et al ldquo-e method to identifythe optimal channel numbers for increasing the locationaccuracy of microseismic events in coal minerdquo Journal ofChina Coal Society vol 35 no 12 pp 2017ndash2021 2012

[24] S Y Gong L M Dou X P Ma et al ldquoStudy on the con-struction and solution technique of anisotropic velocity modelin the location of coal mine tremorrdquo Chinese Journal ofGeophysics-Chinese Edition vol 55 no 5 pp 1757ndash17632012

[25] A Lurka and P Swanson ldquoImprovements in seismic eventlocations in a deep western US coal mine using tomographicvelocity models and an evolutionary search algorithmrdquoMining Science and Technology (China) vol 19 no 5pp 599ndash603 2009

10 Advances in Civil Engineering

23 Array Layout Sensors were mainly laid out in threeplanes and two inclined shafts -e vertical size of thedistribution region was 80m while the horizontal size wasbetween 100m and 200m -e array mainly consisted of 33sensors Table 1 shows their location informationFigures 2ndash4 depict the planar layout of the sensor Figure 5shows the space layout of the sensors

24 Microblasting Seismic Source -ree microblasting ex-periments were performed and the blasting location was setin three operation planes A monitoring station was set nearthe artificial seismic source to precisely collect the seismicmoment -e arrival time difference of this station and theother monitoring stations was calculated and became thetravel time of the seismic signal spent in reaching the de-tection station Table 2 presents the artificial seismic sourcecoordinates amount of explosive and the signal waveformrecorded Figure 5 illustrates the spatial arrangement of theartificial microseismic source

-e monitoring result showed that only the No 2blasting at the 140m plane and the No 3 blasting at the100m plane were well received -e No 1 seismic signal atthe 180m plane and the effective acceptance amount ofstations were quite dissatisfactory and thus abandoned -eanalysis implied that this finding may be caused by theremote seismic location the small amount of explosive andthe dense transportation channels which affected the signaltransmission from the artificial seismic source to all thesensors Figure 6 shows the signal received by all stationsafter the second and third blasting -e picked up signalswere filtered Subsequently onset time picking was thenconducted which was not elaborated here because of thelength limit

3 Seismic Source Location Algorithm

31Modeling Suppose the microseismic monitoring regionis a cubic area of which the side length is 1000m-e sensorsare distributed at the eight vertexes whose coordinates (unitm) are A (0 0 0) B (1000 0 0) C (1000 1000 0) D (0 10000) E (0 0 1000) F (1000 0 1000) G (1000 1000 1000) andH (0 1000 1000) -e equivalent velocity of the wave

transmission in the medium in the theoretical model issimplified as V 5600ms to make it convenient to explorethe impact of different factors on the location error -ecentral point O of the monitoring region is (500 500 500)-e location effect worked out for the seismic source withinand without the region is studied After the artificial seismicsource coordinates and the velocity are given the arrivaltime from the artificial seismic source to the sensors isworked out by supposing that the artificial seismic source isstirred at 0 moment and taken as the true value -e locationcalculation is then performed with the arrival time -ecoordinates of seismic source points 1 to 11 are (500 500500) (400 400 400) (minus500 minus500 minus500) Artificialseismic source points 1ndash6 are within the envelope line of themonitoring region (ie AG line) while points 7ndash11 arebeyond the envelope line (ie extending line of AG) -earrival time from the artificial seismic source points to allsensors is 01ms as the minimum unit in the round-offmethod to simulate the error caused by the onset timepicking Figure 7 shows the model

32 Location Algorithm Particle swarm optimization is anemerging evolutionary algorithm which constantly collectsthe direction and speed of search according to the flightcourse and information transfer between swamps -esearch process is mainly accomplished by relying on theinteractions and the mutual influence of particles featuringeasy implementation fast convergence and high precision-e free flight of ldquoparticle swarmrdquo in the solution space canperfectly resolve the problem of the final solution being thelocal optimal solution -e updated versions of the speedand the location of particle i are shown in the followingequations

Vid wVid + c1r1 Pid minusXid( 1113857 + c2r2 Pgd minusXid1113872 1113873

Xid Xid + Vid(1)

where w is the inertia weight c1 and c2 are the integralsranging between [2 4] known as the learning or acceleratedfactor r1 and r2 are the random numbers between [0 1]known as the maximum inertia weight and minimum inertiaweight respectively d 1 2 3 D where D stands for

(a) (b)

Figure 1 Site monitoring equipment layout (a) Data recorder (b) Data hub

Advances in Civil Engineering 3

the dimension of the solution vector Vid Xid Pid and Pgd

are the flight speed of particle i in the dth dimension spacelocation optimal solution searched and optimal solutionsearched by the swamp

-e location was worked out through the MATLABPSO toolbox with the following PSO parameter settingslearning factor c1 c2 2 inertia weight r1 09 r2 04number of particles 20 w 1 and end condition maxi-mum number of iterations 20000 or ε 1e minus 25 Whenthe velocity is known V 5600ms and D 3 MeanwhileD 4 when the location is worked out with the unknownvelocity

321 Impacts of the Location Methods on the Location-is study located the two target functions of the knownwave velocity and the unknown wave velocity through theion swarm algorithm to explore the effects of different lo-cation methods on the location error Equation (2) is thetarget function for solving the known wave velocity local-ization and equation (3) is the target function for solving the

unknown wave velocity localization Figure 8 shows thelocation result error

f min1113944n

i1Δ1113954tij minusΔtij1113872 1113873

2 min1113944

n

i1ti minus tj minus

li minus lj

v1113888 1113889

2

(2)

f min ti minus tj1113872 1113873vminus li minus lj1113872 1113873

(3)

Figure 8(a) illustrates that with the known wave ve-locity the errors in the x y and z directions tended toincrease with the source point away from the center of themonitoring station envelope -e error presented a jumpchange when the unknown wave velocity was used for thelocation with the location error of each source pointgetting farther and farther away from the center point ofthe monitoring station -e location error was smaller inthe area -e error outside the area also increased whenthe distance increased and became greater than the lo-cation error of the known wave velocity Figure 8(b)depicts a large difference of the location error between

Table 1 Sensor location information

Plane NumberData hub andinterface serial

number

Sensornumber

Coordinates (m)

X Y Z

180m plane 6 1

3 180103 8835730 6146960 1808164 180104 8832982 6121473 1807605 180105 8851786 6124607 1807406 180106 8854521 6108712 1806757 180107 8879863 6114670 1809688 180108 8834896 6103363 180469

Short inclined shaft 3 19 110101 8883636 6197365 15035510 110102 8878167 6185213 15628511 110103 8867835 6160976 169305

140m plane 12 2

1 140201 8860325 6241630 1413532 140202 8879256 6235671 1396503 140203 8902053 6225357 1395904 140204 8924206 6221107 1395505 140205 8924527 6201975 1396086 140206 8918945 6182133 1397237 140207 8908220 6174085 1397168 140208 8919876 6314837 1399259 140209 8927746 6244410 13958010 140210 8932245 6261876 13961911 140211 8932629 6279137 13962812 140212 8922516 6308026 139820

100m plane 6 3

1 100301 8851300 6321265 1000702 100302 8858368 6321290 1017963 100303 8868516 6315367 1003984 100304 8882840 6324850 1010105 100305 8925043 6335871 1005216 100306 8894740 6323830 100150

Long inclined shaft 6 3

7 111301 8838087 6170980 1711568 111302 8840036 6193240 1603059 111303 8841736 6212716 15079310 111304 8845730 6264803 12588011 111305 8847221 6284368 11583012 111306 8848507 6308935 103820

4 Advances in Civil Engineering

the known and unknown wave velocities which cannotreect the actual geologic wave velocity e inuences ofthe two location methods on the location error were notobvious when the wave velocity error was not consideredHowever the variation trend of the location error wasdierent

322 Inuences of the Wave Velocity Error on the Locatione P-wave velocity of the rock samples in the experimentalarea was rst required to be determined by an ultrasonicvelocity meter based on the known wave velocity model forthe location Dierences between the given wave velocity andthe actual wave velocity were observed erefore the errorsthat are plusmn2 plusmn5 plusmn10 and plusmn15 are applied to disturb the

original wave velocity V 5600ms and take it as the truevalue of wave velocity A disturbance error greater than 0implied that the actual wave velocity was less than V oth-erwise the actual wave velocity was greater thanVe arrivaltime was calculated and taken as the initial value of the lo-cation calculation together with V 5600ms to verify theinuences of the wave velocity error on the location Figure 9shows the location distance error of each articial seismicsource under dierent wave velocity error disturbances

Figure 9 also depicts that the wave velocity error has agreat inuence on the location performance when the knownwave velocity was used for the location e location error ofeach source point increased in line with the increase of thewave velocity error when the actual wave velocity was less thanthat used for the location Meanwhile the location error of

180107180108

Verticalsha 180106

180m plane

180105110103

Short inclinedsha

110102110101

140m plane

140202

140201140m plane

111304

111305

111306

100301100m plane

111303

111302

111301

180103

180104180m plane

Long inclinedsha

Figure 2 180m plane and inclined shaft sensor layout

140206 140205 140204 140209 140210 140211140212

140208

140207Short inclined shaft

110101

Long inclined shaft

111303111304

140201

140202

140203140m plane

Figure 3 140m plane sensor layout

Advances in Civil Engineering 5

each source point inside the area increased in line with theincrease of the wave velocity error when the actual wavevelocity was greater than that used for the location e lo-cation error of each source point outside the area was greaterthan that inside the area that approximately showed an ex-ponential increase with the increase of the wave velocity errore error brought by a lower location wave velocity wasgenerally larger with a greater inuence on the location

323 Inuences of the Source Position on the LocationFigure 10 clearly shows that the location error of each sourcepoint inside and outside the monitoring area was

signicantly dierent e location error increased in astraight line with the enlarged distance from the centralpoint inside the area when the actual wave velocity wasgreater than location wave velocity and the disturbed valuewas less than minus5 e change rate of the error suddenlybecame higher from source point 6 (ie the demarcationpoint between the inside and the outside) and then becamelower Its position of becoming smaller became farther andfarther away with the decrease of the disturbed value Inaddition the change rate of the error eventually tended to bestable e disturbed value was greater than 5 when theactual wave velocity was less than the location wave velocitye location error rst increased and then decreased withthe enlarged distance from the central point inside the areaand gradually increased again with a more enlarged distancefrom the demarcation point e location error was verysmall when the disturbed value was plusmn2 is error slowlyincreased in a straight line inside the area but remainedstable outside the area e inuences of the source positionon the location are suggested to be interfered by the wavevelocity error With the great error in the wave velocity thelocation error changes could be divided into the three fol-lowing areas from the central point of the area (Figure 10)near enlarged mutation and far enlarged areas e changetrend of the location error changed within themutation areaFurthermore the range and the changing characteristics ofthe mutation area depended on the wave velocity error

4 Analysis on the Influences of the Quantity ofStation Planes and Stations on theLocation Error

e particle swarm algorithm was applied to undertake thesource location to the microexplosion performed on the sitee location parameters are as follows location area co-ordinates X [8800 9000] Y [6100 6400] and Z [95185] e eective arrival time was adopted for the locatione ultrasonic testing indoor showed that the P-wave ve-locity of the rock samples of the experimental diggings was6357ms e unknown wave velocity was adopted for themicroexplosion source location to avoid the inuences of thewave velocity error on the location performance

41 Inuences of the Quantity of Station Planes on theLocation Dierent station sensors including 180m plane140m plane 100m plane inclined shaft (long and shortinclined shafts) and some plane sensors were successivelyapplied for the location to analyze the high-density array forthe location performance of microseismic monitoring eunknown wave velocity location was adopted for a betterlocation performance (Figure 11) When the single stationplane was used for the location the source location was moreaccurately realized only when the source was located on ornearby the monitoring plane e single location of themonitoring plane far away from the source would have anextremely great error especially the vertical location errorWhen the sensor of the 140m plane was adopted for thelocation of the 100m plane its vertical error unexpectedly

100305

100306

100304

100m plane

100302

100301111306

Long inclined shaft

100303

Watertank

Figure 4 100m plane sensor layout

190

180

170

160

150

140

130

120

110

1006400

6300 62006100 8950 8900 8850 8800

Artificial source180m planeShort inclined shaft

140m plane100m planeLong inclined shaft

Figure 5 Sensor and articial source space layout

6 Advances in Civil Engineering

reached 51m and the vertical distance between the two planeswas only 40m e location performance was obviouslygreater than that of the single plane when two monitoringplanes were applied for the location However this value wasstill less than that in the location with all the sensors usedisnding illustrates that the increase of the sensor ldquoarray planerdquocould largely reduce the location error with a positive andstimulating inuence on the microseismic location

42 Inuences of the Station Quantity on the LocationFour sensors were selected from all the sensors in the arrayto verify the impact of the monitoring array density on the

location performance and avoid locating in a single planee sensors at the other positions were successivelysuperimposed to select dierent sensor quantities andperform an unknown wave velocity location for themicroblasting on the 140m plane ree sets of data wereselected to take the mean value for the location Figure 12shows the resulting location errore left gure depicts thatthe sensor quantity plays a positive role in improving thelocation accuracy of the source e location errors becameincreasingly smaller as the sensor quantity increased ederivation was taken for the location error to obtain thevariation trend curve of the error As shown in the right sideof Figure 12 the location error decreased with the increase ofthe sensor quantity when the sensor quantity was between 4and 14 e value change of the derivative then became slowbut was still less than 0 thereby indicating that the increaseof the sensor quantity can improve the location perfor-mance which proves that the high-density array is benecialto control the microseismicmonitoring accuracye sourcelocation error of the whole array was approximately 26me mathematical relationship between the location errorΔL and the sensor quantity n was obtained as shown inequation (4) based on the tting of the location error data inthe guree correction determination coecient Adj R2 098972 which shows that the tting result is very close tothe real situation rough this equation an exponentialrelationship can be found between both

ΔL 251999 times eminus(n2343) + 3166 (4)

In the above calculation the P-wave velocities of the140m plane and the 100m plane obtained from the

Table 2 Microblasting source

Seismic source no Location Number Explosive amountCoordinates (m)

Example of the signal waveformX Y Z

1 180mplane 1 300 g 8882635 6127475 181028

2 140mplane 1 300 g 8917753 6171168 139620

3 100mplane 1 400 g 8870609 6316663 100096

2000 800060004000

3

1

ndash3

0

ndash1

t (ms)

v (m

ms

)

(a)

2000 800060004000

3

1

ndash3

0

ndash1

t (ms)

v (m

ms

)

(b)

Figure 6 Microblasting signal (a) No 2 seismic source signal at the 100m plane (b) No 3 seismic signal at the 140m plane

C

YDA

B

X

GF

E H

Z

Figure 7 Model of the monitoring region

Advances in Civil Engineering 7

inversion of the whole array were 5898ms and 5903msrespectively which were rather dierent from the results ofthe indoor experiment In addition compared with themodel analysis results the location error of the actualmonitoring was larger and related to the complexity of ageological structure e location size and direction ofvarious discontinuity surfaces such as fractures joints andfaults in the rock mass all inuence the wave propagation inthe medium Inevitably errors were found in the arrival timerequired for the location because the time was acquired fromthe waveform recorded in the noise environment throughphase identication On the one hand the high-density arraymicroseismic monitoring can extend the quantity of thearrival time data to reduce the signicant impact of thearrival time error On the other hand the high-density

station especially when being three-dimensionally laiddecreases the travel time distance from the source to thevarious sensors and reduces the dierence between spaceand time and the theoretical calculation of the travel timedata caused by the inhomogeneity of the rock mass Insummary benetting from the two abovementioned pointsthe high-density station can eectively improve the locationperformance of the microseismic source of the mine

5 Conclusions

e following conclusions are obtained from this study

(1) eoretical modeling was used herein to analyze thetarget function with the wave velocity nonwavevelocity and source location performance Conse-quently the wave velocity error had a great inuence

100806040200

ndash02ndash04ndash06ndash08

Loca

tion

erro

r (m

)

0 2 4 6 8 10 12Source point

Error in z directionError in y direction

Error in x directionDistance error

(a)

Error in z directionError in y directionError in x direction

Velocity errorDistance error

1 2 3 4 5 6 7 8 9 10 11

0806040200

ndash02ndash04ndash06

1816141210

Loca

tion

erro

r (m

)

6040200ndash20ndash40ndash60ndash80ndash100ndash120

Vel

ocity

erro

r (m

s)

Source point

(b)

Figure 8 (a) Location error distribution under the known wave velocity (b) Location error distribution under the unknown wave velocity

900

800

700

600

500

400

300

200

100

ndash100

0

Loca

tion

erro

r (m

)

ndash15 ndash10 ndash5 0 5 10 15Wave velocity error ()

Seismic source 6

Seismic source 1Seismic source 2Seismic source 3Seismic source 4Seismic source 5

Seismic source 7Seismic source 8Seismic source 9Seismic source 10Seismic source 11

Figure 9 Location distance error distribution of dierent wavevelocity errors

1 2 3 4 5 6 7 8 9 10 11 12

Loca

tion

erro

r (m

)900850800750700650600550500450400350300250200150100

500

ndash50ndash100 Source point

ndash15ndash10ndash5

02

ndash2 51015

Figure 10 Location distance error distribution of dierentpositions

8 Advances in Civil Engineering

on the location result in the target function with thewave velocity and such inuence exponentially in-creased e positioning error was small when thesource point was at the envelope center of themonitoring array e error was larger when thesource point was outside the envelope

(2) e inuence of the station density on the locationerror was analyzed by a eld experiment e ex-perimental results indicated that the inuence of thestation density can be divided into two parts station

quantity and station plane quantity e locationaccuracy signicantly increased with the increase ofthe station quantity when the station plane quantitywas certain When station quantity was more than12 such an increase was no longer obvious Whenthe station quantity is certain the increase of thestation plane quantity can signicantly improve thelocation accuracy e accuracy of the multistationplane was higher than that of the single-station planee best station density was 00192

Loca

tion

erro

r (m

)160

140

120

100

80

60

40

20

0Wholestations

180mplane

140mplane

100mplane

180mplane

+ 140mplane

Shortinclined

sha

Longinclined

sha

(a)

0

5

Loca

tion

erro

r (m

)

35

30

25

20

15

10

Wholestations

180mplane

140mplane

100mplane

180mplane

+ 140mplane

Shortinclined

shaft

Longinclined

shaft

(b)

Figure 11 Relationship between the location error and the sensor position (a) 100m plane seismic source location error (b) 140m planeseismic source location error

2 4 6 8 10 12 14 16 18 20 22 24 26 28 30

50

40

30

20

10

0

Loca

tion

erro

r (m

)

Number of stations

Location errorFitted location errorWhole array location error

(a)

40

ndash2

ndash4

ndash6

ndash8

ndash10

ndash12

6 8 10 12 14 16 18 20 22 24 26 28 30

Derivative

(b)

Figure 12 Relationship between the location error and the number of stations

Advances in Civil Engineering 9

Data Availability

-e data used to support the findings of this study areavailable from the corresponding author upon request

Conflicts of Interest

-e authors declare that there are no conflicts of interestregarding the publication of this paper

Acknowledgments

-e authors would like to express their gratitude to all thosewho helped them during the writing of this thesis First of allthe author is grateful for the site and technical support of themanager and technical staff of the Fuxin Xinmin gold mineSecond the authors are thankful to the postgraduates ofLiaoning Technical University for their help in the experi-ments Lastly the authors would like to thank Editage(httpwwweditagecn) for the English language editing-is work was supported by the National Natural ScienceFoundation of China grant no 51774173 the NaturalScience Foundation of Liaoning Province China grant no201602351 and the Open Fund for the State Key Laboratoryof Seismological Dynamics grant no LED2015B01

References

[1] S J Gibowicz and A Kijko An Introduction to MiningSeismology Academic Press Inc New York NY USA 1994

[2] Y M Yin F X Jiang G X Xie et al ldquoRelation between coal-rock failure andmethane emission based onmicroseismic anddynamic stress monitoringrdquo Journal of Mining and SafetyEngineering vol 32 no 2 pp 325ndash330 2015

[3] A-y Cao L-m Dou G-x Chen S-y Gong Y-g Wang andZ-h Li ldquoFocal mechanism caused by fracture or burst of acoal pillarrdquo Journal of China University of Mining andTechnology vol 18 no 2 pp 153ndash158 2008

[4] Y S Pan Y F Zhao F H Guan et al ldquoStudy on rockburstmonitoring and orientation system and its applicationrdquoChinese Journal of Rock Mechanics and Engineering vol 26no 5 pp 1002ndash1011 2007

[5] L M Dou J He S Y Gong et al ldquoA case study of micro-seismic monitoring goaf water-inrush dynamic hazardsrdquoJournal of China University of Mining and Technology vol 41no 1 pp 20ndash25 2012

[6] X F Xu L M Dou A Y Cao et al ldquoEffect of overlying stratastructures on rock burst and micro-seismic monitoringanalysisrdquo Journal of Mining and Safety Engineering vol 28no 1 pp 11ndash15 2011

[7] S Y Gong L M Dou A Y Cao et al ldquoStudy on optimalconfiguration of seismological observation network for coalminerdquo Chinese Journal of Geophysics vol 53 no 2pp 457ndash465 2010

[8] L Fojtıkova V Vavrycuk A Cipciar and J Madaras ldquoFocalmechanisms of micro-earthquakes in the dobra voda seis-moactive area in the male karpaty mts (little carpathians)Slovakiardquo Tectonophysics vol 492 no 1ndash4 pp 213ndash229 2010

[9] J Rhie and D Dreger ldquoA simple method for simulatingmicroseismic HV spectral ratio in 3D structurerdquo GeosciencesJournal vol 13 no 4 pp 401ndash406 2010

[10] K B Danilov and B Konstantin ldquo-e structure of the onegadownthrown block and adjacent geological objects accordingto the microseismic sounding methodrdquo Pure and AppliedGeophysics vol 174 no 7 pp 2663ndash2676 2017

[11] A V Gorbatikov A V Kalinina V A Volkov J ArnosoR Vieira and E Velez ldquoResults of analysis of the data ofmicroseismic survey at lanzarote island canary Spainrdquo Pureand Applied Geophysics vol 161 no 7 pp 1561ndash1578 2004

[12] D V Popov K B Danilov R A Zhostkov Z I Dudarov andE V Ivanova ldquoProcessing the digital microseismic recordingsusing the data analysis kit (DAK) software packagerdquo SeismicInstruments vol 50 no 1 pp 75ndash83 2014

[13] A Auger and N Hansen ldquoPerformance evaluation of anadvanced local search evolutionary algorithmrdquo in Proceedingsof the 2005 IEEE Congress on Evolutionary Computation no2 pp 1777ndash17842 Edinburgh Scotland September 2005

[14] Y Sato and D Skoko ldquoOptimum distribution of seismicobservationpoints IIIrdquo Bulletin of the Earthquake ResearchInstitute University of Tokyo vol 43 no 1 pp 451ndash457 1965

[15] A T Ringler T Storm L S Gee C R Hutt and D WilsonldquoUncertainty estimates in broadband seismometer sensitiv-ities usingmicroseismicsrdquo Journal of Seismology vol 19 no 2pp 317ndash327 2014

[16] A T Ringler R Sleeman C R Hutt et al Seismometer Self-Noise and Measuring Methods Springer Berlin Heidelberg2015

[17] Z Zhao and R S Zeng ldquoA method for improving the de-termination of earthquake hypocentersrdquo Chinese Journal ofGeophysics vol 30 no 4 pp 379ndash388 1987

[18] J I Sabbione M D Sacchi and D R Velis ldquoRadontransform-based microseismic event detection and signal-to-noise ratio enhancementrdquo Journal of Applied Geophysicsvol 113 pp 51ndash63 2015

[19] L J Dong ldquoMathematical functions and parameters formicroseismic source location without pre-measuring speedrdquoChinese Journal of Rock Mechanics and Engineering vol 30no 10 pp 2057ndash2067 2011

[20] J Li Y T Gao Y L Xie et al ldquoImprovement of microseismiclocating based on simplex method without velocity measur-ingrdquo Chinese Journal of Rock Mechanics and Engineeringvol 33 no 7 pp 1336ndash1346 2014

[21] L J Dong X B Li J Ma et al ldquo-ree-dimensional analyticalcomprehensive solutions for acoustic emissionmicroseismicsources of unknown velocity systemrdquo Chinese Journal of RockMechanics and Engineering vol 36 no 1 pp 186ndash197 2017

[22] M B Zhou J X Wu and W Zhang ldquoMicroseismic sourcelocation method based on small area signal pickuprdquo Safetyand Environmental Engineering vol 22 no 5 pp 154ndash1572015 in Chinese

[23] S Y Gong L M Dou X P Ma et al ldquo-e method to identifythe optimal channel numbers for increasing the locationaccuracy of microseismic events in coal minerdquo Journal ofChina Coal Society vol 35 no 12 pp 2017ndash2021 2012

[24] S Y Gong L M Dou X P Ma et al ldquoStudy on the con-struction and solution technique of anisotropic velocity modelin the location of coal mine tremorrdquo Chinese Journal ofGeophysics-Chinese Edition vol 55 no 5 pp 1757ndash17632012

[25] A Lurka and P Swanson ldquoImprovements in seismic eventlocations in a deep western US coal mine using tomographicvelocity models and an evolutionary search algorithmrdquoMining Science and Technology (China) vol 19 no 5pp 599ndash603 2009

10 Advances in Civil Engineering

the dimension of the solution vector Vid Xid Pid and Pgd

are the flight speed of particle i in the dth dimension spacelocation optimal solution searched and optimal solutionsearched by the swamp

-e location was worked out through the MATLABPSO toolbox with the following PSO parameter settingslearning factor c1 c2 2 inertia weight r1 09 r2 04number of particles 20 w 1 and end condition maxi-mum number of iterations 20000 or ε 1e minus 25 Whenthe velocity is known V 5600ms and D 3 MeanwhileD 4 when the location is worked out with the unknownvelocity

321 Impacts of the Location Methods on the Location-is study located the two target functions of the knownwave velocity and the unknown wave velocity through theion swarm algorithm to explore the effects of different lo-cation methods on the location error Equation (2) is thetarget function for solving the known wave velocity local-ization and equation (3) is the target function for solving the

unknown wave velocity localization Figure 8 shows thelocation result error

f min1113944n

i1Δ1113954tij minusΔtij1113872 1113873

2 min1113944

n

i1ti minus tj minus

li minus lj

v1113888 1113889

2

(2)

f min ti minus tj1113872 1113873vminus li minus lj1113872 1113873

(3)

Figure 8(a) illustrates that with the known wave ve-locity the errors in the x y and z directions tended toincrease with the source point away from the center of themonitoring station envelope -e error presented a jumpchange when the unknown wave velocity was used for thelocation with the location error of each source pointgetting farther and farther away from the center point ofthe monitoring station -e location error was smaller inthe area -e error outside the area also increased whenthe distance increased and became greater than the lo-cation error of the known wave velocity Figure 8(b)depicts a large difference of the location error between

Table 1 Sensor location information

Plane NumberData hub andinterface serial

number

Sensornumber

Coordinates (m)

X Y Z

180m plane 6 1

3 180103 8835730 6146960 1808164 180104 8832982 6121473 1807605 180105 8851786 6124607 1807406 180106 8854521 6108712 1806757 180107 8879863 6114670 1809688 180108 8834896 6103363 180469

Short inclined shaft 3 19 110101 8883636 6197365 15035510 110102 8878167 6185213 15628511 110103 8867835 6160976 169305

140m plane 12 2

1 140201 8860325 6241630 1413532 140202 8879256 6235671 1396503 140203 8902053 6225357 1395904 140204 8924206 6221107 1395505 140205 8924527 6201975 1396086 140206 8918945 6182133 1397237 140207 8908220 6174085 1397168 140208 8919876 6314837 1399259 140209 8927746 6244410 13958010 140210 8932245 6261876 13961911 140211 8932629 6279137 13962812 140212 8922516 6308026 139820

100m plane 6 3

1 100301 8851300 6321265 1000702 100302 8858368 6321290 1017963 100303 8868516 6315367 1003984 100304 8882840 6324850 1010105 100305 8925043 6335871 1005216 100306 8894740 6323830 100150

Long inclined shaft 6 3

7 111301 8838087 6170980 1711568 111302 8840036 6193240 1603059 111303 8841736 6212716 15079310 111304 8845730 6264803 12588011 111305 8847221 6284368 11583012 111306 8848507 6308935 103820

4 Advances in Civil Engineering

the known and unknown wave velocities which cannotreect the actual geologic wave velocity e inuences ofthe two location methods on the location error were notobvious when the wave velocity error was not consideredHowever the variation trend of the location error wasdierent

322 Inuences of the Wave Velocity Error on the Locatione P-wave velocity of the rock samples in the experimentalarea was rst required to be determined by an ultrasonicvelocity meter based on the known wave velocity model forthe location Dierences between the given wave velocity andthe actual wave velocity were observed erefore the errorsthat are plusmn2 plusmn5 plusmn10 and plusmn15 are applied to disturb the

original wave velocity V 5600ms and take it as the truevalue of wave velocity A disturbance error greater than 0implied that the actual wave velocity was less than V oth-erwise the actual wave velocity was greater thanVe arrivaltime was calculated and taken as the initial value of the lo-cation calculation together with V 5600ms to verify theinuences of the wave velocity error on the location Figure 9shows the location distance error of each articial seismicsource under dierent wave velocity error disturbances

Figure 9 also depicts that the wave velocity error has agreat inuence on the location performance when the knownwave velocity was used for the location e location error ofeach source point increased in line with the increase of thewave velocity error when the actual wave velocity was less thanthat used for the location Meanwhile the location error of

180107180108

Verticalsha 180106

180m plane

180105110103

Short inclinedsha

110102110101

140m plane

140202

140201140m plane

111304

111305

111306

100301100m plane

111303

111302

111301

180103

180104180m plane

Long inclinedsha

Figure 2 180m plane and inclined shaft sensor layout

140206 140205 140204 140209 140210 140211140212

140208

140207Short inclined shaft

110101

Long inclined shaft

111303111304

140201

140202

140203140m plane

Figure 3 140m plane sensor layout

Advances in Civil Engineering 5

each source point inside the area increased in line with theincrease of the wave velocity error when the actual wavevelocity was greater than that used for the location e lo-cation error of each source point outside the area was greaterthan that inside the area that approximately showed an ex-ponential increase with the increase of the wave velocity errore error brought by a lower location wave velocity wasgenerally larger with a greater inuence on the location

323 Inuences of the Source Position on the LocationFigure 10 clearly shows that the location error of each sourcepoint inside and outside the monitoring area was

signicantly dierent e location error increased in astraight line with the enlarged distance from the centralpoint inside the area when the actual wave velocity wasgreater than location wave velocity and the disturbed valuewas less than minus5 e change rate of the error suddenlybecame higher from source point 6 (ie the demarcationpoint between the inside and the outside) and then becamelower Its position of becoming smaller became farther andfarther away with the decrease of the disturbed value Inaddition the change rate of the error eventually tended to bestable e disturbed value was greater than 5 when theactual wave velocity was less than the location wave velocitye location error rst increased and then decreased withthe enlarged distance from the central point inside the areaand gradually increased again with a more enlarged distancefrom the demarcation point e location error was verysmall when the disturbed value was plusmn2 is error slowlyincreased in a straight line inside the area but remainedstable outside the area e inuences of the source positionon the location are suggested to be interfered by the wavevelocity error With the great error in the wave velocity thelocation error changes could be divided into the three fol-lowing areas from the central point of the area (Figure 10)near enlarged mutation and far enlarged areas e changetrend of the location error changed within themutation areaFurthermore the range and the changing characteristics ofthe mutation area depended on the wave velocity error

4 Analysis on the Influences of the Quantity ofStation Planes and Stations on theLocation Error

e particle swarm algorithm was applied to undertake thesource location to the microexplosion performed on the sitee location parameters are as follows location area co-ordinates X [8800 9000] Y [6100 6400] and Z [95185] e eective arrival time was adopted for the locatione ultrasonic testing indoor showed that the P-wave ve-locity of the rock samples of the experimental diggings was6357ms e unknown wave velocity was adopted for themicroexplosion source location to avoid the inuences of thewave velocity error on the location performance

41 Inuences of the Quantity of Station Planes on theLocation Dierent station sensors including 180m plane140m plane 100m plane inclined shaft (long and shortinclined shafts) and some plane sensors were successivelyapplied for the location to analyze the high-density array forthe location performance of microseismic monitoring eunknown wave velocity location was adopted for a betterlocation performance (Figure 11) When the single stationplane was used for the location the source location was moreaccurately realized only when the source was located on ornearby the monitoring plane e single location of themonitoring plane far away from the source would have anextremely great error especially the vertical location errorWhen the sensor of the 140m plane was adopted for thelocation of the 100m plane its vertical error unexpectedly

100305

100306

100304

100m plane

100302

100301111306

Long inclined shaft

100303

Watertank

Figure 4 100m plane sensor layout

190

180

170

160

150

140

130

120

110

1006400

6300 62006100 8950 8900 8850 8800

Artificial source180m planeShort inclined shaft

140m plane100m planeLong inclined shaft

Figure 5 Sensor and articial source space layout

6 Advances in Civil Engineering

reached 51m and the vertical distance between the two planeswas only 40m e location performance was obviouslygreater than that of the single plane when two monitoringplanes were applied for the location However this value wasstill less than that in the location with all the sensors usedisnding illustrates that the increase of the sensor ldquoarray planerdquocould largely reduce the location error with a positive andstimulating inuence on the microseismic location

42 Inuences of the Station Quantity on the LocationFour sensors were selected from all the sensors in the arrayto verify the impact of the monitoring array density on the

location performance and avoid locating in a single planee sensors at the other positions were successivelysuperimposed to select dierent sensor quantities andperform an unknown wave velocity location for themicroblasting on the 140m plane ree sets of data wereselected to take the mean value for the location Figure 12shows the resulting location errore left gure depicts thatthe sensor quantity plays a positive role in improving thelocation accuracy of the source e location errors becameincreasingly smaller as the sensor quantity increased ederivation was taken for the location error to obtain thevariation trend curve of the error As shown in the right sideof Figure 12 the location error decreased with the increase ofthe sensor quantity when the sensor quantity was between 4and 14 e value change of the derivative then became slowbut was still less than 0 thereby indicating that the increaseof the sensor quantity can improve the location perfor-mance which proves that the high-density array is benecialto control the microseismicmonitoring accuracye sourcelocation error of the whole array was approximately 26me mathematical relationship between the location errorΔL and the sensor quantity n was obtained as shown inequation (4) based on the tting of the location error data inthe guree correction determination coecient Adj R2 098972 which shows that the tting result is very close tothe real situation rough this equation an exponentialrelationship can be found between both

ΔL 251999 times eminus(n2343) + 3166 (4)

In the above calculation the P-wave velocities of the140m plane and the 100m plane obtained from the

Table 2 Microblasting source

Seismic source no Location Number Explosive amountCoordinates (m)

Example of the signal waveformX Y Z

1 180mplane 1 300 g 8882635 6127475 181028

2 140mplane 1 300 g 8917753 6171168 139620

3 100mplane 1 400 g 8870609 6316663 100096

2000 800060004000

3

1

ndash3

0

ndash1

t (ms)

v (m

ms

)

(a)

2000 800060004000

3

1

ndash3

0

ndash1

t (ms)

v (m

ms

)

(b)

Figure 6 Microblasting signal (a) No 2 seismic source signal at the 100m plane (b) No 3 seismic signal at the 140m plane

C

YDA

B

X

GF

E H

Z

Figure 7 Model of the monitoring region

Advances in Civil Engineering 7

inversion of the whole array were 5898ms and 5903msrespectively which were rather dierent from the results ofthe indoor experiment In addition compared with themodel analysis results the location error of the actualmonitoring was larger and related to the complexity of ageological structure e location size and direction ofvarious discontinuity surfaces such as fractures joints andfaults in the rock mass all inuence the wave propagation inthe medium Inevitably errors were found in the arrival timerequired for the location because the time was acquired fromthe waveform recorded in the noise environment throughphase identication On the one hand the high-density arraymicroseismic monitoring can extend the quantity of thearrival time data to reduce the signicant impact of thearrival time error On the other hand the high-density

station especially when being three-dimensionally laiddecreases the travel time distance from the source to thevarious sensors and reduces the dierence between spaceand time and the theoretical calculation of the travel timedata caused by the inhomogeneity of the rock mass Insummary benetting from the two abovementioned pointsthe high-density station can eectively improve the locationperformance of the microseismic source of the mine

5 Conclusions

e following conclusions are obtained from this study

(1) eoretical modeling was used herein to analyze thetarget function with the wave velocity nonwavevelocity and source location performance Conse-quently the wave velocity error had a great inuence

100806040200

ndash02ndash04ndash06ndash08

Loca

tion

erro

r (m

)

0 2 4 6 8 10 12Source point

Error in z directionError in y direction

Error in x directionDistance error

(a)

Error in z directionError in y directionError in x direction

Velocity errorDistance error

1 2 3 4 5 6 7 8 9 10 11

0806040200

ndash02ndash04ndash06

1816141210

Loca

tion

erro

r (m

)

6040200ndash20ndash40ndash60ndash80ndash100ndash120

Vel

ocity

erro

r (m

s)

Source point

(b)

Figure 8 (a) Location error distribution under the known wave velocity (b) Location error distribution under the unknown wave velocity

900

800

700

600

500

400

300

200

100

ndash100

0

Loca

tion

erro

r (m

)

ndash15 ndash10 ndash5 0 5 10 15Wave velocity error ()

Seismic source 6

Seismic source 1Seismic source 2Seismic source 3Seismic source 4Seismic source 5

Seismic source 7Seismic source 8Seismic source 9Seismic source 10Seismic source 11

Figure 9 Location distance error distribution of dierent wavevelocity errors

1 2 3 4 5 6 7 8 9 10 11 12

Loca

tion

erro

r (m

)900850800750700650600550500450400350300250200150100

500

ndash50ndash100 Source point

ndash15ndash10ndash5

02

ndash2 51015

Figure 10 Location distance error distribution of dierentpositions

8 Advances in Civil Engineering

on the location result in the target function with thewave velocity and such inuence exponentially in-creased e positioning error was small when thesource point was at the envelope center of themonitoring array e error was larger when thesource point was outside the envelope

(2) e inuence of the station density on the locationerror was analyzed by a eld experiment e ex-perimental results indicated that the inuence of thestation density can be divided into two parts station

quantity and station plane quantity e locationaccuracy signicantly increased with the increase ofthe station quantity when the station plane quantitywas certain When station quantity was more than12 such an increase was no longer obvious Whenthe station quantity is certain the increase of thestation plane quantity can signicantly improve thelocation accuracy e accuracy of the multistationplane was higher than that of the single-station planee best station density was 00192

Loca

tion

erro

r (m

)160

140

120

100

80

60

40

20

0Wholestations

180mplane

140mplane

100mplane

180mplane

+ 140mplane

Shortinclined

sha

Longinclined

sha

(a)

0

5

Loca

tion

erro

r (m

)

35

30

25

20

15

10

Wholestations

180mplane

140mplane

100mplane

180mplane

+ 140mplane

Shortinclined

shaft

Longinclined

shaft

(b)

Figure 11 Relationship between the location error and the sensor position (a) 100m plane seismic source location error (b) 140m planeseismic source location error

2 4 6 8 10 12 14 16 18 20 22 24 26 28 30

50

40

30

20

10

0

Loca

tion

erro

r (m

)

Number of stations

Location errorFitted location errorWhole array location error

(a)

40

ndash2

ndash4

ndash6

ndash8

ndash10

ndash12

6 8 10 12 14 16 18 20 22 24 26 28 30

Derivative

(b)

Figure 12 Relationship between the location error and the number of stations

Advances in Civil Engineering 9

Data Availability

-e data used to support the findings of this study areavailable from the corresponding author upon request

Conflicts of Interest

-e authors declare that there are no conflicts of interestregarding the publication of this paper

Acknowledgments

-e authors would like to express their gratitude to all thosewho helped them during the writing of this thesis First of allthe author is grateful for the site and technical support of themanager and technical staff of the Fuxin Xinmin gold mineSecond the authors are thankful to the postgraduates ofLiaoning Technical University for their help in the experi-ments Lastly the authors would like to thank Editage(httpwwweditagecn) for the English language editing-is work was supported by the National Natural ScienceFoundation of China grant no 51774173 the NaturalScience Foundation of Liaoning Province China grant no201602351 and the Open Fund for the State Key Laboratoryof Seismological Dynamics grant no LED2015B01

References

[1] S J Gibowicz and A Kijko An Introduction to MiningSeismology Academic Press Inc New York NY USA 1994

[2] Y M Yin F X Jiang G X Xie et al ldquoRelation between coal-rock failure andmethane emission based onmicroseismic anddynamic stress monitoringrdquo Journal of Mining and SafetyEngineering vol 32 no 2 pp 325ndash330 2015

[3] A-y Cao L-m Dou G-x Chen S-y Gong Y-g Wang andZ-h Li ldquoFocal mechanism caused by fracture or burst of acoal pillarrdquo Journal of China University of Mining andTechnology vol 18 no 2 pp 153ndash158 2008

[4] Y S Pan Y F Zhao F H Guan et al ldquoStudy on rockburstmonitoring and orientation system and its applicationrdquoChinese Journal of Rock Mechanics and Engineering vol 26no 5 pp 1002ndash1011 2007

[5] L M Dou J He S Y Gong et al ldquoA case study of micro-seismic monitoring goaf water-inrush dynamic hazardsrdquoJournal of China University of Mining and Technology vol 41no 1 pp 20ndash25 2012

[6] X F Xu L M Dou A Y Cao et al ldquoEffect of overlying stratastructures on rock burst and micro-seismic monitoringanalysisrdquo Journal of Mining and Safety Engineering vol 28no 1 pp 11ndash15 2011

[7] S Y Gong L M Dou A Y Cao et al ldquoStudy on optimalconfiguration of seismological observation network for coalminerdquo Chinese Journal of Geophysics vol 53 no 2pp 457ndash465 2010

[8] L Fojtıkova V Vavrycuk A Cipciar and J Madaras ldquoFocalmechanisms of micro-earthquakes in the dobra voda seis-moactive area in the male karpaty mts (little carpathians)Slovakiardquo Tectonophysics vol 492 no 1ndash4 pp 213ndash229 2010

[9] J Rhie and D Dreger ldquoA simple method for simulatingmicroseismic HV spectral ratio in 3D structurerdquo GeosciencesJournal vol 13 no 4 pp 401ndash406 2010

[10] K B Danilov and B Konstantin ldquo-e structure of the onegadownthrown block and adjacent geological objects accordingto the microseismic sounding methodrdquo Pure and AppliedGeophysics vol 174 no 7 pp 2663ndash2676 2017

[11] A V Gorbatikov A V Kalinina V A Volkov J ArnosoR Vieira and E Velez ldquoResults of analysis of the data ofmicroseismic survey at lanzarote island canary Spainrdquo Pureand Applied Geophysics vol 161 no 7 pp 1561ndash1578 2004

[12] D V Popov K B Danilov R A Zhostkov Z I Dudarov andE V Ivanova ldquoProcessing the digital microseismic recordingsusing the data analysis kit (DAK) software packagerdquo SeismicInstruments vol 50 no 1 pp 75ndash83 2014

[13] A Auger and N Hansen ldquoPerformance evaluation of anadvanced local search evolutionary algorithmrdquo in Proceedingsof the 2005 IEEE Congress on Evolutionary Computation no2 pp 1777ndash17842 Edinburgh Scotland September 2005

[14] Y Sato and D Skoko ldquoOptimum distribution of seismicobservationpoints IIIrdquo Bulletin of the Earthquake ResearchInstitute University of Tokyo vol 43 no 1 pp 451ndash457 1965

[15] A T Ringler T Storm L S Gee C R Hutt and D WilsonldquoUncertainty estimates in broadband seismometer sensitiv-ities usingmicroseismicsrdquo Journal of Seismology vol 19 no 2pp 317ndash327 2014

[16] A T Ringler R Sleeman C R Hutt et al Seismometer Self-Noise and Measuring Methods Springer Berlin Heidelberg2015

[17] Z Zhao and R S Zeng ldquoA method for improving the de-termination of earthquake hypocentersrdquo Chinese Journal ofGeophysics vol 30 no 4 pp 379ndash388 1987

[18] J I Sabbione M D Sacchi and D R Velis ldquoRadontransform-based microseismic event detection and signal-to-noise ratio enhancementrdquo Journal of Applied Geophysicsvol 113 pp 51ndash63 2015

[19] L J Dong ldquoMathematical functions and parameters formicroseismic source location without pre-measuring speedrdquoChinese Journal of Rock Mechanics and Engineering vol 30no 10 pp 2057ndash2067 2011

[20] J Li Y T Gao Y L Xie et al ldquoImprovement of microseismiclocating based on simplex method without velocity measur-ingrdquo Chinese Journal of Rock Mechanics and Engineeringvol 33 no 7 pp 1336ndash1346 2014

[21] L J Dong X B Li J Ma et al ldquo-ree-dimensional analyticalcomprehensive solutions for acoustic emissionmicroseismicsources of unknown velocity systemrdquo Chinese Journal of RockMechanics and Engineering vol 36 no 1 pp 186ndash197 2017

[22] M B Zhou J X Wu and W Zhang ldquoMicroseismic sourcelocation method based on small area signal pickuprdquo Safetyand Environmental Engineering vol 22 no 5 pp 154ndash1572015 in Chinese

[23] S Y Gong L M Dou X P Ma et al ldquo-e method to identifythe optimal channel numbers for increasing the locationaccuracy of microseismic events in coal minerdquo Journal ofChina Coal Society vol 35 no 12 pp 2017ndash2021 2012

[24] S Y Gong L M Dou X P Ma et al ldquoStudy on the con-struction and solution technique of anisotropic velocity modelin the location of coal mine tremorrdquo Chinese Journal ofGeophysics-Chinese Edition vol 55 no 5 pp 1757ndash17632012

[25] A Lurka and P Swanson ldquoImprovements in seismic eventlocations in a deep western US coal mine using tomographicvelocity models and an evolutionary search algorithmrdquoMining Science and Technology (China) vol 19 no 5pp 599ndash603 2009

10 Advances in Civil Engineering

the known and unknown wave velocities which cannotreect the actual geologic wave velocity e inuences ofthe two location methods on the location error were notobvious when the wave velocity error was not consideredHowever the variation trend of the location error wasdierent

322 Inuences of the Wave Velocity Error on the Locatione P-wave velocity of the rock samples in the experimentalarea was rst required to be determined by an ultrasonicvelocity meter based on the known wave velocity model forthe location Dierences between the given wave velocity andthe actual wave velocity were observed erefore the errorsthat are plusmn2 plusmn5 plusmn10 and plusmn15 are applied to disturb the

original wave velocity V 5600ms and take it as the truevalue of wave velocity A disturbance error greater than 0implied that the actual wave velocity was less than V oth-erwise the actual wave velocity was greater thanVe arrivaltime was calculated and taken as the initial value of the lo-cation calculation together with V 5600ms to verify theinuences of the wave velocity error on the location Figure 9shows the location distance error of each articial seismicsource under dierent wave velocity error disturbances

Figure 9 also depicts that the wave velocity error has agreat inuence on the location performance when the knownwave velocity was used for the location e location error ofeach source point increased in line with the increase of thewave velocity error when the actual wave velocity was less thanthat used for the location Meanwhile the location error of

180107180108

Verticalsha 180106

180m plane

180105110103

Short inclinedsha

110102110101

140m plane

140202

140201140m plane

111304

111305

111306

100301100m plane

111303

111302

111301

180103

180104180m plane

Long inclinedsha

Figure 2 180m plane and inclined shaft sensor layout

140206 140205 140204 140209 140210 140211140212

140208

140207Short inclined shaft

110101

Long inclined shaft

111303111304

140201

140202

140203140m plane

Figure 3 140m plane sensor layout

Advances in Civil Engineering 5

each source point inside the area increased in line with theincrease of the wave velocity error when the actual wavevelocity was greater than that used for the location e lo-cation error of each source point outside the area was greaterthan that inside the area that approximately showed an ex-ponential increase with the increase of the wave velocity errore error brought by a lower location wave velocity wasgenerally larger with a greater inuence on the location

323 Inuences of the Source Position on the LocationFigure 10 clearly shows that the location error of each sourcepoint inside and outside the monitoring area was

signicantly dierent e location error increased in astraight line with the enlarged distance from the centralpoint inside the area when the actual wave velocity wasgreater than location wave velocity and the disturbed valuewas less than minus5 e change rate of the error suddenlybecame higher from source point 6 (ie the demarcationpoint between the inside and the outside) and then becamelower Its position of becoming smaller became farther andfarther away with the decrease of the disturbed value Inaddition the change rate of the error eventually tended to bestable e disturbed value was greater than 5 when theactual wave velocity was less than the location wave velocitye location error rst increased and then decreased withthe enlarged distance from the central point inside the areaand gradually increased again with a more enlarged distancefrom the demarcation point e location error was verysmall when the disturbed value was plusmn2 is error slowlyincreased in a straight line inside the area but remainedstable outside the area e inuences of the source positionon the location are suggested to be interfered by the wavevelocity error With the great error in the wave velocity thelocation error changes could be divided into the three fol-lowing areas from the central point of the area (Figure 10)near enlarged mutation and far enlarged areas e changetrend of the location error changed within themutation areaFurthermore the range and the changing characteristics ofthe mutation area depended on the wave velocity error

4 Analysis on the Influences of the Quantity ofStation Planes and Stations on theLocation Error

e particle swarm algorithm was applied to undertake thesource location to the microexplosion performed on the sitee location parameters are as follows location area co-ordinates X [8800 9000] Y [6100 6400] and Z [95185] e eective arrival time was adopted for the locatione ultrasonic testing indoor showed that the P-wave ve-locity of the rock samples of the experimental diggings was6357ms e unknown wave velocity was adopted for themicroexplosion source location to avoid the inuences of thewave velocity error on the location performance

41 Inuences of the Quantity of Station Planes on theLocation Dierent station sensors including 180m plane140m plane 100m plane inclined shaft (long and shortinclined shafts) and some plane sensors were successivelyapplied for the location to analyze the high-density array forthe location performance of microseismic monitoring eunknown wave velocity location was adopted for a betterlocation performance (Figure 11) When the single stationplane was used for the location the source location was moreaccurately realized only when the source was located on ornearby the monitoring plane e single location of themonitoring plane far away from the source would have anextremely great error especially the vertical location errorWhen the sensor of the 140m plane was adopted for thelocation of the 100m plane its vertical error unexpectedly

100305

100306

100304

100m plane

100302

100301111306

Long inclined shaft

100303

Watertank

Figure 4 100m plane sensor layout

190

180

170

160

150

140

130

120

110

1006400

6300 62006100 8950 8900 8850 8800

Artificial source180m planeShort inclined shaft

140m plane100m planeLong inclined shaft

Figure 5 Sensor and articial source space layout

6 Advances in Civil Engineering

reached 51m and the vertical distance between the two planeswas only 40m e location performance was obviouslygreater than that of the single plane when two monitoringplanes were applied for the location However this value wasstill less than that in the location with all the sensors usedisnding illustrates that the increase of the sensor ldquoarray planerdquocould largely reduce the location error with a positive andstimulating inuence on the microseismic location

42 Inuences of the Station Quantity on the LocationFour sensors were selected from all the sensors in the arrayto verify the impact of the monitoring array density on the

location performance and avoid locating in a single planee sensors at the other positions were successivelysuperimposed to select dierent sensor quantities andperform an unknown wave velocity location for themicroblasting on the 140m plane ree sets of data wereselected to take the mean value for the location Figure 12shows the resulting location errore left gure depicts thatthe sensor quantity plays a positive role in improving thelocation accuracy of the source e location errors becameincreasingly smaller as the sensor quantity increased ederivation was taken for the location error to obtain thevariation trend curve of the error As shown in the right sideof Figure 12 the location error decreased with the increase ofthe sensor quantity when the sensor quantity was between 4and 14 e value change of the derivative then became slowbut was still less than 0 thereby indicating that the increaseof the sensor quantity can improve the location perfor-mance which proves that the high-density array is benecialto control the microseismicmonitoring accuracye sourcelocation error of the whole array was approximately 26me mathematical relationship between the location errorΔL and the sensor quantity n was obtained as shown inequation (4) based on the tting of the location error data inthe guree correction determination coecient Adj R2 098972 which shows that the tting result is very close tothe real situation rough this equation an exponentialrelationship can be found between both

ΔL 251999 times eminus(n2343) + 3166 (4)

In the above calculation the P-wave velocities of the140m plane and the 100m plane obtained from the

Table 2 Microblasting source

Seismic source no Location Number Explosive amountCoordinates (m)

Example of the signal waveformX Y Z

1 180mplane 1 300 g 8882635 6127475 181028

2 140mplane 1 300 g 8917753 6171168 139620

3 100mplane 1 400 g 8870609 6316663 100096

2000 800060004000

3

1

ndash3

0

ndash1

t (ms)

v (m

ms

)

(a)

2000 800060004000

3

1

ndash3

0

ndash1

t (ms)

v (m

ms

)

(b)

Figure 6 Microblasting signal (a) No 2 seismic source signal at the 100m plane (b) No 3 seismic signal at the 140m plane

C

YDA

B

X

GF

E H

Z

Figure 7 Model of the monitoring region

Advances in Civil Engineering 7

inversion of the whole array were 5898ms and 5903msrespectively which were rather dierent from the results ofthe indoor experiment In addition compared with themodel analysis results the location error of the actualmonitoring was larger and related to the complexity of ageological structure e location size and direction ofvarious discontinuity surfaces such as fractures joints andfaults in the rock mass all inuence the wave propagation inthe medium Inevitably errors were found in the arrival timerequired for the location because the time was acquired fromthe waveform recorded in the noise environment throughphase identication On the one hand the high-density arraymicroseismic monitoring can extend the quantity of thearrival time data to reduce the signicant impact of thearrival time error On the other hand the high-density

station especially when being three-dimensionally laiddecreases the travel time distance from the source to thevarious sensors and reduces the dierence between spaceand time and the theoretical calculation of the travel timedata caused by the inhomogeneity of the rock mass Insummary benetting from the two abovementioned pointsthe high-density station can eectively improve the locationperformance of the microseismic source of the mine

5 Conclusions

e following conclusions are obtained from this study

(1) eoretical modeling was used herein to analyze thetarget function with the wave velocity nonwavevelocity and source location performance Conse-quently the wave velocity error had a great inuence

100806040200

ndash02ndash04ndash06ndash08

Loca

tion

erro

r (m

)

0 2 4 6 8 10 12Source point

Error in z directionError in y direction

Error in x directionDistance error

(a)

Error in z directionError in y directionError in x direction

Velocity errorDistance error

1 2 3 4 5 6 7 8 9 10 11

0806040200

ndash02ndash04ndash06

1816141210

Loca

tion

erro

r (m

)

6040200ndash20ndash40ndash60ndash80ndash100ndash120

Vel

ocity

erro

r (m

s)

Source point

(b)

Figure 8 (a) Location error distribution under the known wave velocity (b) Location error distribution under the unknown wave velocity

900

800

700

600

500

400

300

200

100

ndash100

0

Loca

tion

erro

r (m

)

ndash15 ndash10 ndash5 0 5 10 15Wave velocity error ()

Seismic source 6

Seismic source 1Seismic source 2Seismic source 3Seismic source 4Seismic source 5

Seismic source 7Seismic source 8Seismic source 9Seismic source 10Seismic source 11

Figure 9 Location distance error distribution of dierent wavevelocity errors

1 2 3 4 5 6 7 8 9 10 11 12

Loca

tion

erro

r (m

)900850800750700650600550500450400350300250200150100

500

ndash50ndash100 Source point

ndash15ndash10ndash5

02

ndash2 51015

Figure 10 Location distance error distribution of dierentpositions

8 Advances in Civil Engineering

on the location result in the target function with thewave velocity and such inuence exponentially in-creased e positioning error was small when thesource point was at the envelope center of themonitoring array e error was larger when thesource point was outside the envelope

(2) e inuence of the station density on the locationerror was analyzed by a eld experiment e ex-perimental results indicated that the inuence of thestation density can be divided into two parts station

quantity and station plane quantity e locationaccuracy signicantly increased with the increase ofthe station quantity when the station plane quantitywas certain When station quantity was more than12 such an increase was no longer obvious Whenthe station quantity is certain the increase of thestation plane quantity can signicantly improve thelocation accuracy e accuracy of the multistationplane was higher than that of the single-station planee best station density was 00192

Loca

tion

erro

r (m

)160

140

120

100

80

60

40

20

0Wholestations

180mplane

140mplane

100mplane

180mplane

+ 140mplane

Shortinclined

sha

Longinclined

sha

(a)

0

5

Loca

tion

erro

r (m

)

35

30

25

20

15

10

Wholestations

180mplane

140mplane

100mplane

180mplane

+ 140mplane

Shortinclined

shaft

Longinclined

shaft

(b)

Figure 11 Relationship between the location error and the sensor position (a) 100m plane seismic source location error (b) 140m planeseismic source location error

2 4 6 8 10 12 14 16 18 20 22 24 26 28 30

50

40

30

20

10

0

Loca

tion

erro

r (m

)

Number of stations

Location errorFitted location errorWhole array location error

(a)

40

ndash2

ndash4

ndash6

ndash8

ndash10

ndash12

6 8 10 12 14 16 18 20 22 24 26 28 30

Derivative

(b)

Figure 12 Relationship between the location error and the number of stations

Advances in Civil Engineering 9

Data Availability

-e data used to support the findings of this study areavailable from the corresponding author upon request

Conflicts of Interest

-e authors declare that there are no conflicts of interestregarding the publication of this paper

Acknowledgments

-e authors would like to express their gratitude to all thosewho helped them during the writing of this thesis First of allthe author is grateful for the site and technical support of themanager and technical staff of the Fuxin Xinmin gold mineSecond the authors are thankful to the postgraduates ofLiaoning Technical University for their help in the experi-ments Lastly the authors would like to thank Editage(httpwwweditagecn) for the English language editing-is work was supported by the National Natural ScienceFoundation of China grant no 51774173 the NaturalScience Foundation of Liaoning Province China grant no201602351 and the Open Fund for the State Key Laboratoryof Seismological Dynamics grant no LED2015B01

References

[1] S J Gibowicz and A Kijko An Introduction to MiningSeismology Academic Press Inc New York NY USA 1994

[2] Y M Yin F X Jiang G X Xie et al ldquoRelation between coal-rock failure andmethane emission based onmicroseismic anddynamic stress monitoringrdquo Journal of Mining and SafetyEngineering vol 32 no 2 pp 325ndash330 2015

[3] A-y Cao L-m Dou G-x Chen S-y Gong Y-g Wang andZ-h Li ldquoFocal mechanism caused by fracture or burst of acoal pillarrdquo Journal of China University of Mining andTechnology vol 18 no 2 pp 153ndash158 2008

[4] Y S Pan Y F Zhao F H Guan et al ldquoStudy on rockburstmonitoring and orientation system and its applicationrdquoChinese Journal of Rock Mechanics and Engineering vol 26no 5 pp 1002ndash1011 2007

[5] L M Dou J He S Y Gong et al ldquoA case study of micro-seismic monitoring goaf water-inrush dynamic hazardsrdquoJournal of China University of Mining and Technology vol 41no 1 pp 20ndash25 2012

[6] X F Xu L M Dou A Y Cao et al ldquoEffect of overlying stratastructures on rock burst and micro-seismic monitoringanalysisrdquo Journal of Mining and Safety Engineering vol 28no 1 pp 11ndash15 2011

[7] S Y Gong L M Dou A Y Cao et al ldquoStudy on optimalconfiguration of seismological observation network for coalminerdquo Chinese Journal of Geophysics vol 53 no 2pp 457ndash465 2010

[8] L Fojtıkova V Vavrycuk A Cipciar and J Madaras ldquoFocalmechanisms of micro-earthquakes in the dobra voda seis-moactive area in the male karpaty mts (little carpathians)Slovakiardquo Tectonophysics vol 492 no 1ndash4 pp 213ndash229 2010

[9] J Rhie and D Dreger ldquoA simple method for simulatingmicroseismic HV spectral ratio in 3D structurerdquo GeosciencesJournal vol 13 no 4 pp 401ndash406 2010

[10] K B Danilov and B Konstantin ldquo-e structure of the onegadownthrown block and adjacent geological objects accordingto the microseismic sounding methodrdquo Pure and AppliedGeophysics vol 174 no 7 pp 2663ndash2676 2017

[11] A V Gorbatikov A V Kalinina V A Volkov J ArnosoR Vieira and E Velez ldquoResults of analysis of the data ofmicroseismic survey at lanzarote island canary Spainrdquo Pureand Applied Geophysics vol 161 no 7 pp 1561ndash1578 2004

[12] D V Popov K B Danilov R A Zhostkov Z I Dudarov andE V Ivanova ldquoProcessing the digital microseismic recordingsusing the data analysis kit (DAK) software packagerdquo SeismicInstruments vol 50 no 1 pp 75ndash83 2014

[13] A Auger and N Hansen ldquoPerformance evaluation of anadvanced local search evolutionary algorithmrdquo in Proceedingsof the 2005 IEEE Congress on Evolutionary Computation no2 pp 1777ndash17842 Edinburgh Scotland September 2005

[14] Y Sato and D Skoko ldquoOptimum distribution of seismicobservationpoints IIIrdquo Bulletin of the Earthquake ResearchInstitute University of Tokyo vol 43 no 1 pp 451ndash457 1965

[15] A T Ringler T Storm L S Gee C R Hutt and D WilsonldquoUncertainty estimates in broadband seismometer sensitiv-ities usingmicroseismicsrdquo Journal of Seismology vol 19 no 2pp 317ndash327 2014

[16] A T Ringler R Sleeman C R Hutt et al Seismometer Self-Noise and Measuring Methods Springer Berlin Heidelberg2015

[17] Z Zhao and R S Zeng ldquoA method for improving the de-termination of earthquake hypocentersrdquo Chinese Journal ofGeophysics vol 30 no 4 pp 379ndash388 1987

[18] J I Sabbione M D Sacchi and D R Velis ldquoRadontransform-based microseismic event detection and signal-to-noise ratio enhancementrdquo Journal of Applied Geophysicsvol 113 pp 51ndash63 2015

[19] L J Dong ldquoMathematical functions and parameters formicroseismic source location without pre-measuring speedrdquoChinese Journal of Rock Mechanics and Engineering vol 30no 10 pp 2057ndash2067 2011

[20] J Li Y T Gao Y L Xie et al ldquoImprovement of microseismiclocating based on simplex method without velocity measur-ingrdquo Chinese Journal of Rock Mechanics and Engineeringvol 33 no 7 pp 1336ndash1346 2014

[21] L J Dong X B Li J Ma et al ldquo-ree-dimensional analyticalcomprehensive solutions for acoustic emissionmicroseismicsources of unknown velocity systemrdquo Chinese Journal of RockMechanics and Engineering vol 36 no 1 pp 186ndash197 2017

[22] M B Zhou J X Wu and W Zhang ldquoMicroseismic sourcelocation method based on small area signal pickuprdquo Safetyand Environmental Engineering vol 22 no 5 pp 154ndash1572015 in Chinese

[23] S Y Gong L M Dou X P Ma et al ldquo-e method to identifythe optimal channel numbers for increasing the locationaccuracy of microseismic events in coal minerdquo Journal ofChina Coal Society vol 35 no 12 pp 2017ndash2021 2012

[24] S Y Gong L M Dou X P Ma et al ldquoStudy on the con-struction and solution technique of anisotropic velocity modelin the location of coal mine tremorrdquo Chinese Journal ofGeophysics-Chinese Edition vol 55 no 5 pp 1757ndash17632012

[25] A Lurka and P Swanson ldquoImprovements in seismic eventlocations in a deep western US coal mine using tomographicvelocity models and an evolutionary search algorithmrdquoMining Science and Technology (China) vol 19 no 5pp 599ndash603 2009

10 Advances in Civil Engineering

each source point inside the area increased in line with theincrease of the wave velocity error when the actual wavevelocity was greater than that used for the location e lo-cation error of each source point outside the area was greaterthan that inside the area that approximately showed an ex-ponential increase with the increase of the wave velocity errore error brought by a lower location wave velocity wasgenerally larger with a greater inuence on the location

323 Inuences of the Source Position on the LocationFigure 10 clearly shows that the location error of each sourcepoint inside and outside the monitoring area was

signicantly dierent e location error increased in astraight line with the enlarged distance from the centralpoint inside the area when the actual wave velocity wasgreater than location wave velocity and the disturbed valuewas less than minus5 e change rate of the error suddenlybecame higher from source point 6 (ie the demarcationpoint between the inside and the outside) and then becamelower Its position of becoming smaller became farther andfarther away with the decrease of the disturbed value Inaddition the change rate of the error eventually tended to bestable e disturbed value was greater than 5 when theactual wave velocity was less than the location wave velocitye location error rst increased and then decreased withthe enlarged distance from the central point inside the areaand gradually increased again with a more enlarged distancefrom the demarcation point e location error was verysmall when the disturbed value was plusmn2 is error slowlyincreased in a straight line inside the area but remainedstable outside the area e inuences of the source positionon the location are suggested to be interfered by the wavevelocity error With the great error in the wave velocity thelocation error changes could be divided into the three fol-lowing areas from the central point of the area (Figure 10)near enlarged mutation and far enlarged areas e changetrend of the location error changed within themutation areaFurthermore the range and the changing characteristics ofthe mutation area depended on the wave velocity error

4 Analysis on the Influences of the Quantity ofStation Planes and Stations on theLocation Error

e particle swarm algorithm was applied to undertake thesource location to the microexplosion performed on the sitee location parameters are as follows location area co-ordinates X [8800 9000] Y [6100 6400] and Z [95185] e eective arrival time was adopted for the locatione ultrasonic testing indoor showed that the P-wave ve-locity of the rock samples of the experimental diggings was6357ms e unknown wave velocity was adopted for themicroexplosion source location to avoid the inuences of thewave velocity error on the location performance

41 Inuences of the Quantity of Station Planes on theLocation Dierent station sensors including 180m plane140m plane 100m plane inclined shaft (long and shortinclined shafts) and some plane sensors were successivelyapplied for the location to analyze the high-density array forthe location performance of microseismic monitoring eunknown wave velocity location was adopted for a betterlocation performance (Figure 11) When the single stationplane was used for the location the source location was moreaccurately realized only when the source was located on ornearby the monitoring plane e single location of themonitoring plane far away from the source would have anextremely great error especially the vertical location errorWhen the sensor of the 140m plane was adopted for thelocation of the 100m plane its vertical error unexpectedly

100305

100306

100304

100m plane

100302

100301111306

Long inclined shaft

100303

Watertank

Figure 4 100m plane sensor layout

190

180

170

160

150

140

130

120

110

1006400

6300 62006100 8950 8900 8850 8800

Artificial source180m planeShort inclined shaft

140m plane100m planeLong inclined shaft

Figure 5 Sensor and articial source space layout

6 Advances in Civil Engineering

reached 51m and the vertical distance between the two planeswas only 40m e location performance was obviouslygreater than that of the single plane when two monitoringplanes were applied for the location However this value wasstill less than that in the location with all the sensors usedisnding illustrates that the increase of the sensor ldquoarray planerdquocould largely reduce the location error with a positive andstimulating inuence on the microseismic location

42 Inuences of the Station Quantity on the LocationFour sensors were selected from all the sensors in the arrayto verify the impact of the monitoring array density on the

location performance and avoid locating in a single planee sensors at the other positions were successivelysuperimposed to select dierent sensor quantities andperform an unknown wave velocity location for themicroblasting on the 140m plane ree sets of data wereselected to take the mean value for the location Figure 12shows the resulting location errore left gure depicts thatthe sensor quantity plays a positive role in improving thelocation accuracy of the source e location errors becameincreasingly smaller as the sensor quantity increased ederivation was taken for the location error to obtain thevariation trend curve of the error As shown in the right sideof Figure 12 the location error decreased with the increase ofthe sensor quantity when the sensor quantity was between 4and 14 e value change of the derivative then became slowbut was still less than 0 thereby indicating that the increaseof the sensor quantity can improve the location perfor-mance which proves that the high-density array is benecialto control the microseismicmonitoring accuracye sourcelocation error of the whole array was approximately 26me mathematical relationship between the location errorΔL and the sensor quantity n was obtained as shown inequation (4) based on the tting of the location error data inthe guree correction determination coecient Adj R2 098972 which shows that the tting result is very close tothe real situation rough this equation an exponentialrelationship can be found between both

ΔL 251999 times eminus(n2343) + 3166 (4)

In the above calculation the P-wave velocities of the140m plane and the 100m plane obtained from the

Table 2 Microblasting source

Seismic source no Location Number Explosive amountCoordinates (m)

Example of the signal waveformX Y Z

1 180mplane 1 300 g 8882635 6127475 181028

2 140mplane 1 300 g 8917753 6171168 139620

3 100mplane 1 400 g 8870609 6316663 100096

2000 800060004000

3

1

ndash3

0

ndash1

t (ms)

v (m

ms

)

(a)

2000 800060004000

3

1

ndash3

0

ndash1

t (ms)

v (m

ms

)

(b)

Figure 6 Microblasting signal (a) No 2 seismic source signal at the 100m plane (b) No 3 seismic signal at the 140m plane

C

YDA

B

X

GF

E H

Z

Figure 7 Model of the monitoring region

Advances in Civil Engineering 7

inversion of the whole array were 5898ms and 5903msrespectively which were rather dierent from the results ofthe indoor experiment In addition compared with themodel analysis results the location error of the actualmonitoring was larger and related to the complexity of ageological structure e location size and direction ofvarious discontinuity surfaces such as fractures joints andfaults in the rock mass all inuence the wave propagation inthe medium Inevitably errors were found in the arrival timerequired for the location because the time was acquired fromthe waveform recorded in the noise environment throughphase identication On the one hand the high-density arraymicroseismic monitoring can extend the quantity of thearrival time data to reduce the signicant impact of thearrival time error On the other hand the high-density

station especially when being three-dimensionally laiddecreases the travel time distance from the source to thevarious sensors and reduces the dierence between spaceand time and the theoretical calculation of the travel timedata caused by the inhomogeneity of the rock mass Insummary benetting from the two abovementioned pointsthe high-density station can eectively improve the locationperformance of the microseismic source of the mine

5 Conclusions

e following conclusions are obtained from this study

(1) eoretical modeling was used herein to analyze thetarget function with the wave velocity nonwavevelocity and source location performance Conse-quently the wave velocity error had a great inuence

100806040200

ndash02ndash04ndash06ndash08

Loca

tion

erro

r (m

)

0 2 4 6 8 10 12Source point

Error in z directionError in y direction

Error in x directionDistance error

(a)

Error in z directionError in y directionError in x direction

Velocity errorDistance error

1 2 3 4 5 6 7 8 9 10 11

0806040200

ndash02ndash04ndash06

1816141210

Loca

tion

erro

r (m

)

6040200ndash20ndash40ndash60ndash80ndash100ndash120

Vel

ocity

erro

r (m

s)

Source point

(b)

Figure 8 (a) Location error distribution under the known wave velocity (b) Location error distribution under the unknown wave velocity

900

800

700

600

500

400

300

200

100

ndash100

0

Loca

tion

erro

r (m

)

ndash15 ndash10 ndash5 0 5 10 15Wave velocity error ()

Seismic source 6

Seismic source 1Seismic source 2Seismic source 3Seismic source 4Seismic source 5

Seismic source 7Seismic source 8Seismic source 9Seismic source 10Seismic source 11

Figure 9 Location distance error distribution of dierent wavevelocity errors

1 2 3 4 5 6 7 8 9 10 11 12

Loca

tion

erro

r (m

)900850800750700650600550500450400350300250200150100

500

ndash50ndash100 Source point

ndash15ndash10ndash5

02

ndash2 51015

Figure 10 Location distance error distribution of dierentpositions

8 Advances in Civil Engineering

on the location result in the target function with thewave velocity and such inuence exponentially in-creased e positioning error was small when thesource point was at the envelope center of themonitoring array e error was larger when thesource point was outside the envelope

(2) e inuence of the station density on the locationerror was analyzed by a eld experiment e ex-perimental results indicated that the inuence of thestation density can be divided into two parts station

quantity and station plane quantity e locationaccuracy signicantly increased with the increase ofthe station quantity when the station plane quantitywas certain When station quantity was more than12 such an increase was no longer obvious Whenthe station quantity is certain the increase of thestation plane quantity can signicantly improve thelocation accuracy e accuracy of the multistationplane was higher than that of the single-station planee best station density was 00192

Loca

tion

erro

r (m

)160

140

120

100

80

60

40

20

0Wholestations

180mplane

140mplane

100mplane

180mplane

+ 140mplane

Shortinclined

sha

Longinclined

sha

(a)

0

5

Loca

tion

erro

r (m

)

35

30

25

20

15

10

Wholestations

180mplane

140mplane

100mplane

180mplane

+ 140mplane

Shortinclined

shaft

Longinclined

shaft

(b)

Figure 11 Relationship between the location error and the sensor position (a) 100m plane seismic source location error (b) 140m planeseismic source location error

2 4 6 8 10 12 14 16 18 20 22 24 26 28 30

50

40

30

20

10

0

Loca

tion

erro

r (m

)

Number of stations

Location errorFitted location errorWhole array location error

(a)

40

ndash2

ndash4

ndash6

ndash8

ndash10

ndash12

6 8 10 12 14 16 18 20 22 24 26 28 30

Derivative

(b)

Figure 12 Relationship between the location error and the number of stations

Advances in Civil Engineering 9

Data Availability

-e data used to support the findings of this study areavailable from the corresponding author upon request

Conflicts of Interest

-e authors declare that there are no conflicts of interestregarding the publication of this paper

Acknowledgments

-e authors would like to express their gratitude to all thosewho helped them during the writing of this thesis First of allthe author is grateful for the site and technical support of themanager and technical staff of the Fuxin Xinmin gold mineSecond the authors are thankful to the postgraduates ofLiaoning Technical University for their help in the experi-ments Lastly the authors would like to thank Editage(httpwwweditagecn) for the English language editing-is work was supported by the National Natural ScienceFoundation of China grant no 51774173 the NaturalScience Foundation of Liaoning Province China grant no201602351 and the Open Fund for the State Key Laboratoryof Seismological Dynamics grant no LED2015B01

References

[1] S J Gibowicz and A Kijko An Introduction to MiningSeismology Academic Press Inc New York NY USA 1994

[2] Y M Yin F X Jiang G X Xie et al ldquoRelation between coal-rock failure andmethane emission based onmicroseismic anddynamic stress monitoringrdquo Journal of Mining and SafetyEngineering vol 32 no 2 pp 325ndash330 2015

[3] A-y Cao L-m Dou G-x Chen S-y Gong Y-g Wang andZ-h Li ldquoFocal mechanism caused by fracture or burst of acoal pillarrdquo Journal of China University of Mining andTechnology vol 18 no 2 pp 153ndash158 2008

[4] Y S Pan Y F Zhao F H Guan et al ldquoStudy on rockburstmonitoring and orientation system and its applicationrdquoChinese Journal of Rock Mechanics and Engineering vol 26no 5 pp 1002ndash1011 2007

[5] L M Dou J He S Y Gong et al ldquoA case study of micro-seismic monitoring goaf water-inrush dynamic hazardsrdquoJournal of China University of Mining and Technology vol 41no 1 pp 20ndash25 2012

[6] X F Xu L M Dou A Y Cao et al ldquoEffect of overlying stratastructures on rock burst and micro-seismic monitoringanalysisrdquo Journal of Mining and Safety Engineering vol 28no 1 pp 11ndash15 2011

[7] S Y Gong L M Dou A Y Cao et al ldquoStudy on optimalconfiguration of seismological observation network for coalminerdquo Chinese Journal of Geophysics vol 53 no 2pp 457ndash465 2010

[8] L Fojtıkova V Vavrycuk A Cipciar and J Madaras ldquoFocalmechanisms of micro-earthquakes in the dobra voda seis-moactive area in the male karpaty mts (little carpathians)Slovakiardquo Tectonophysics vol 492 no 1ndash4 pp 213ndash229 2010

[9] J Rhie and D Dreger ldquoA simple method for simulatingmicroseismic HV spectral ratio in 3D structurerdquo GeosciencesJournal vol 13 no 4 pp 401ndash406 2010

[10] K B Danilov and B Konstantin ldquo-e structure of the onegadownthrown block and adjacent geological objects accordingto the microseismic sounding methodrdquo Pure and AppliedGeophysics vol 174 no 7 pp 2663ndash2676 2017

[11] A V Gorbatikov A V Kalinina V A Volkov J ArnosoR Vieira and E Velez ldquoResults of analysis of the data ofmicroseismic survey at lanzarote island canary Spainrdquo Pureand Applied Geophysics vol 161 no 7 pp 1561ndash1578 2004

[12] D V Popov K B Danilov R A Zhostkov Z I Dudarov andE V Ivanova ldquoProcessing the digital microseismic recordingsusing the data analysis kit (DAK) software packagerdquo SeismicInstruments vol 50 no 1 pp 75ndash83 2014

[13] A Auger and N Hansen ldquoPerformance evaluation of anadvanced local search evolutionary algorithmrdquo in Proceedingsof the 2005 IEEE Congress on Evolutionary Computation no2 pp 1777ndash17842 Edinburgh Scotland September 2005

[14] Y Sato and D Skoko ldquoOptimum distribution of seismicobservationpoints IIIrdquo Bulletin of the Earthquake ResearchInstitute University of Tokyo vol 43 no 1 pp 451ndash457 1965

[15] A T Ringler T Storm L S Gee C R Hutt and D WilsonldquoUncertainty estimates in broadband seismometer sensitiv-ities usingmicroseismicsrdquo Journal of Seismology vol 19 no 2pp 317ndash327 2014

[16] A T Ringler R Sleeman C R Hutt et al Seismometer Self-Noise and Measuring Methods Springer Berlin Heidelberg2015

[17] Z Zhao and R S Zeng ldquoA method for improving the de-termination of earthquake hypocentersrdquo Chinese Journal ofGeophysics vol 30 no 4 pp 379ndash388 1987

[18] J I Sabbione M D Sacchi and D R Velis ldquoRadontransform-based microseismic event detection and signal-to-noise ratio enhancementrdquo Journal of Applied Geophysicsvol 113 pp 51ndash63 2015

[19] L J Dong ldquoMathematical functions and parameters formicroseismic source location without pre-measuring speedrdquoChinese Journal of Rock Mechanics and Engineering vol 30no 10 pp 2057ndash2067 2011

[20] J Li Y T Gao Y L Xie et al ldquoImprovement of microseismiclocating based on simplex method without velocity measur-ingrdquo Chinese Journal of Rock Mechanics and Engineeringvol 33 no 7 pp 1336ndash1346 2014

[21] L J Dong X B Li J Ma et al ldquo-ree-dimensional analyticalcomprehensive solutions for acoustic emissionmicroseismicsources of unknown velocity systemrdquo Chinese Journal of RockMechanics and Engineering vol 36 no 1 pp 186ndash197 2017

[22] M B Zhou J X Wu and W Zhang ldquoMicroseismic sourcelocation method based on small area signal pickuprdquo Safetyand Environmental Engineering vol 22 no 5 pp 154ndash1572015 in Chinese

[23] S Y Gong L M Dou X P Ma et al ldquo-e method to identifythe optimal channel numbers for increasing the locationaccuracy of microseismic events in coal minerdquo Journal ofChina Coal Society vol 35 no 12 pp 2017ndash2021 2012

[24] S Y Gong L M Dou X P Ma et al ldquoStudy on the con-struction and solution technique of anisotropic velocity modelin the location of coal mine tremorrdquo Chinese Journal ofGeophysics-Chinese Edition vol 55 no 5 pp 1757ndash17632012

[25] A Lurka and P Swanson ldquoImprovements in seismic eventlocations in a deep western US coal mine using tomographicvelocity models and an evolutionary search algorithmrdquoMining Science and Technology (China) vol 19 no 5pp 599ndash603 2009

10 Advances in Civil Engineering

reached 51m and the vertical distance between the two planeswas only 40m e location performance was obviouslygreater than that of the single plane when two monitoringplanes were applied for the location However this value wasstill less than that in the location with all the sensors usedisnding illustrates that the increase of the sensor ldquoarray planerdquocould largely reduce the location error with a positive andstimulating inuence on the microseismic location

42 Inuences of the Station Quantity on the LocationFour sensors were selected from all the sensors in the arrayto verify the impact of the monitoring array density on the

location performance and avoid locating in a single planee sensors at the other positions were successivelysuperimposed to select dierent sensor quantities andperform an unknown wave velocity location for themicroblasting on the 140m plane ree sets of data wereselected to take the mean value for the location Figure 12shows the resulting location errore left gure depicts thatthe sensor quantity plays a positive role in improving thelocation accuracy of the source e location errors becameincreasingly smaller as the sensor quantity increased ederivation was taken for the location error to obtain thevariation trend curve of the error As shown in the right sideof Figure 12 the location error decreased with the increase ofthe sensor quantity when the sensor quantity was between 4and 14 e value change of the derivative then became slowbut was still less than 0 thereby indicating that the increaseof the sensor quantity can improve the location perfor-mance which proves that the high-density array is benecialto control the microseismicmonitoring accuracye sourcelocation error of the whole array was approximately 26me mathematical relationship between the location errorΔL and the sensor quantity n was obtained as shown inequation (4) based on the tting of the location error data inthe guree correction determination coecient Adj R2 098972 which shows that the tting result is very close tothe real situation rough this equation an exponentialrelationship can be found between both

ΔL 251999 times eminus(n2343) + 3166 (4)

In the above calculation the P-wave velocities of the140m plane and the 100m plane obtained from the

Table 2 Microblasting source

Seismic source no Location Number Explosive amountCoordinates (m)

Example of the signal waveformX Y Z

1 180mplane 1 300 g 8882635 6127475 181028

2 140mplane 1 300 g 8917753 6171168 139620

3 100mplane 1 400 g 8870609 6316663 100096

2000 800060004000

3

1

ndash3

0

ndash1

t (ms)

v (m

ms

)

(a)

2000 800060004000

3

1

ndash3

0

ndash1

t (ms)

v (m

ms

)

(b)

Figure 6 Microblasting signal (a) No 2 seismic source signal at the 100m plane (b) No 3 seismic signal at the 140m plane

C

YDA

B

X

GF

E H

Z

Figure 7 Model of the monitoring region

Advances in Civil Engineering 7

inversion of the whole array were 5898ms and 5903msrespectively which were rather dierent from the results ofthe indoor experiment In addition compared with themodel analysis results the location error of the actualmonitoring was larger and related to the complexity of ageological structure e location size and direction ofvarious discontinuity surfaces such as fractures joints andfaults in the rock mass all inuence the wave propagation inthe medium Inevitably errors were found in the arrival timerequired for the location because the time was acquired fromthe waveform recorded in the noise environment throughphase identication On the one hand the high-density arraymicroseismic monitoring can extend the quantity of thearrival time data to reduce the signicant impact of thearrival time error On the other hand the high-density

station especially when being three-dimensionally laiddecreases the travel time distance from the source to thevarious sensors and reduces the dierence between spaceand time and the theoretical calculation of the travel timedata caused by the inhomogeneity of the rock mass Insummary benetting from the two abovementioned pointsthe high-density station can eectively improve the locationperformance of the microseismic source of the mine

5 Conclusions

e following conclusions are obtained from this study

(1) eoretical modeling was used herein to analyze thetarget function with the wave velocity nonwavevelocity and source location performance Conse-quently the wave velocity error had a great inuence

100806040200

ndash02ndash04ndash06ndash08

Loca

tion

erro

r (m

)

0 2 4 6 8 10 12Source point

Error in z directionError in y direction

Error in x directionDistance error

(a)

Error in z directionError in y directionError in x direction

Velocity errorDistance error

1 2 3 4 5 6 7 8 9 10 11

0806040200

ndash02ndash04ndash06

1816141210

Loca

tion

erro

r (m

)

6040200ndash20ndash40ndash60ndash80ndash100ndash120

Vel

ocity

erro

r (m

s)

Source point

(b)

Figure 8 (a) Location error distribution under the known wave velocity (b) Location error distribution under the unknown wave velocity

900

800

700

600

500

400

300

200

100

ndash100

0

Loca

tion

erro

r (m

)

ndash15 ndash10 ndash5 0 5 10 15Wave velocity error ()

Seismic source 6

Seismic source 1Seismic source 2Seismic source 3Seismic source 4Seismic source 5

Seismic source 7Seismic source 8Seismic source 9Seismic source 10Seismic source 11

Figure 9 Location distance error distribution of dierent wavevelocity errors

1 2 3 4 5 6 7 8 9 10 11 12

Loca

tion

erro

r (m

)900850800750700650600550500450400350300250200150100

500

ndash50ndash100 Source point

ndash15ndash10ndash5

02

ndash2 51015

Figure 10 Location distance error distribution of dierentpositions

8 Advances in Civil Engineering

on the location result in the target function with thewave velocity and such inuence exponentially in-creased e positioning error was small when thesource point was at the envelope center of themonitoring array e error was larger when thesource point was outside the envelope

(2) e inuence of the station density on the locationerror was analyzed by a eld experiment e ex-perimental results indicated that the inuence of thestation density can be divided into two parts station

quantity and station plane quantity e locationaccuracy signicantly increased with the increase ofthe station quantity when the station plane quantitywas certain When station quantity was more than12 such an increase was no longer obvious Whenthe station quantity is certain the increase of thestation plane quantity can signicantly improve thelocation accuracy e accuracy of the multistationplane was higher than that of the single-station planee best station density was 00192

Loca

tion

erro

r (m

)160

140

120

100

80

60

40

20

0Wholestations

180mplane

140mplane

100mplane

180mplane

+ 140mplane

Shortinclined

sha

Longinclined

sha

(a)

0

5

Loca

tion

erro

r (m

)

35

30

25

20

15

10

Wholestations

180mplane

140mplane

100mplane

180mplane

+ 140mplane

Shortinclined

shaft

Longinclined

shaft

(b)

Figure 11 Relationship between the location error and the sensor position (a) 100m plane seismic source location error (b) 140m planeseismic source location error

2 4 6 8 10 12 14 16 18 20 22 24 26 28 30

50

40

30

20

10

0

Loca

tion

erro

r (m

)

Number of stations

Location errorFitted location errorWhole array location error

(a)

40

ndash2

ndash4

ndash6

ndash8

ndash10

ndash12

6 8 10 12 14 16 18 20 22 24 26 28 30

Derivative

(b)

Figure 12 Relationship between the location error and the number of stations

Advances in Civil Engineering 9

Data Availability

-e data used to support the findings of this study areavailable from the corresponding author upon request

Conflicts of Interest

-e authors declare that there are no conflicts of interestregarding the publication of this paper

Acknowledgments

-e authors would like to express their gratitude to all thosewho helped them during the writing of this thesis First of allthe author is grateful for the site and technical support of themanager and technical staff of the Fuxin Xinmin gold mineSecond the authors are thankful to the postgraduates ofLiaoning Technical University for their help in the experi-ments Lastly the authors would like to thank Editage(httpwwweditagecn) for the English language editing-is work was supported by the National Natural ScienceFoundation of China grant no 51774173 the NaturalScience Foundation of Liaoning Province China grant no201602351 and the Open Fund for the State Key Laboratoryof Seismological Dynamics grant no LED2015B01

References

[1] S J Gibowicz and A Kijko An Introduction to MiningSeismology Academic Press Inc New York NY USA 1994

[2] Y M Yin F X Jiang G X Xie et al ldquoRelation between coal-rock failure andmethane emission based onmicroseismic anddynamic stress monitoringrdquo Journal of Mining and SafetyEngineering vol 32 no 2 pp 325ndash330 2015

[3] A-y Cao L-m Dou G-x Chen S-y Gong Y-g Wang andZ-h Li ldquoFocal mechanism caused by fracture or burst of acoal pillarrdquo Journal of China University of Mining andTechnology vol 18 no 2 pp 153ndash158 2008

[4] Y S Pan Y F Zhao F H Guan et al ldquoStudy on rockburstmonitoring and orientation system and its applicationrdquoChinese Journal of Rock Mechanics and Engineering vol 26no 5 pp 1002ndash1011 2007

[5] L M Dou J He S Y Gong et al ldquoA case study of micro-seismic monitoring goaf water-inrush dynamic hazardsrdquoJournal of China University of Mining and Technology vol 41no 1 pp 20ndash25 2012

[6] X F Xu L M Dou A Y Cao et al ldquoEffect of overlying stratastructures on rock burst and micro-seismic monitoringanalysisrdquo Journal of Mining and Safety Engineering vol 28no 1 pp 11ndash15 2011

[7] S Y Gong L M Dou A Y Cao et al ldquoStudy on optimalconfiguration of seismological observation network for coalminerdquo Chinese Journal of Geophysics vol 53 no 2pp 457ndash465 2010

[8] L Fojtıkova V Vavrycuk A Cipciar and J Madaras ldquoFocalmechanisms of micro-earthquakes in the dobra voda seis-moactive area in the male karpaty mts (little carpathians)Slovakiardquo Tectonophysics vol 492 no 1ndash4 pp 213ndash229 2010

[9] J Rhie and D Dreger ldquoA simple method for simulatingmicroseismic HV spectral ratio in 3D structurerdquo GeosciencesJournal vol 13 no 4 pp 401ndash406 2010

[10] K B Danilov and B Konstantin ldquo-e structure of the onegadownthrown block and adjacent geological objects accordingto the microseismic sounding methodrdquo Pure and AppliedGeophysics vol 174 no 7 pp 2663ndash2676 2017

[11] A V Gorbatikov A V Kalinina V A Volkov J ArnosoR Vieira and E Velez ldquoResults of analysis of the data ofmicroseismic survey at lanzarote island canary Spainrdquo Pureand Applied Geophysics vol 161 no 7 pp 1561ndash1578 2004

[12] D V Popov K B Danilov R A Zhostkov Z I Dudarov andE V Ivanova ldquoProcessing the digital microseismic recordingsusing the data analysis kit (DAK) software packagerdquo SeismicInstruments vol 50 no 1 pp 75ndash83 2014

[13] A Auger and N Hansen ldquoPerformance evaluation of anadvanced local search evolutionary algorithmrdquo in Proceedingsof the 2005 IEEE Congress on Evolutionary Computation no2 pp 1777ndash17842 Edinburgh Scotland September 2005

[14] Y Sato and D Skoko ldquoOptimum distribution of seismicobservationpoints IIIrdquo Bulletin of the Earthquake ResearchInstitute University of Tokyo vol 43 no 1 pp 451ndash457 1965

[15] A T Ringler T Storm L S Gee C R Hutt and D WilsonldquoUncertainty estimates in broadband seismometer sensitiv-ities usingmicroseismicsrdquo Journal of Seismology vol 19 no 2pp 317ndash327 2014

[16] A T Ringler R Sleeman C R Hutt et al Seismometer Self-Noise and Measuring Methods Springer Berlin Heidelberg2015

[17] Z Zhao and R S Zeng ldquoA method for improving the de-termination of earthquake hypocentersrdquo Chinese Journal ofGeophysics vol 30 no 4 pp 379ndash388 1987

[18] J I Sabbione M D Sacchi and D R Velis ldquoRadontransform-based microseismic event detection and signal-to-noise ratio enhancementrdquo Journal of Applied Geophysicsvol 113 pp 51ndash63 2015

[19] L J Dong ldquoMathematical functions and parameters formicroseismic source location without pre-measuring speedrdquoChinese Journal of Rock Mechanics and Engineering vol 30no 10 pp 2057ndash2067 2011

[20] J Li Y T Gao Y L Xie et al ldquoImprovement of microseismiclocating based on simplex method without velocity measur-ingrdquo Chinese Journal of Rock Mechanics and Engineeringvol 33 no 7 pp 1336ndash1346 2014

[21] L J Dong X B Li J Ma et al ldquo-ree-dimensional analyticalcomprehensive solutions for acoustic emissionmicroseismicsources of unknown velocity systemrdquo Chinese Journal of RockMechanics and Engineering vol 36 no 1 pp 186ndash197 2017

[22] M B Zhou J X Wu and W Zhang ldquoMicroseismic sourcelocation method based on small area signal pickuprdquo Safetyand Environmental Engineering vol 22 no 5 pp 154ndash1572015 in Chinese

[23] S Y Gong L M Dou X P Ma et al ldquo-e method to identifythe optimal channel numbers for increasing the locationaccuracy of microseismic events in coal minerdquo Journal ofChina Coal Society vol 35 no 12 pp 2017ndash2021 2012

[24] S Y Gong L M Dou X P Ma et al ldquoStudy on the con-struction and solution technique of anisotropic velocity modelin the location of coal mine tremorrdquo Chinese Journal ofGeophysics-Chinese Edition vol 55 no 5 pp 1757ndash17632012

[25] A Lurka and P Swanson ldquoImprovements in seismic eventlocations in a deep western US coal mine using tomographicvelocity models and an evolutionary search algorithmrdquoMining Science and Technology (China) vol 19 no 5pp 599ndash603 2009

10 Advances in Civil Engineering

inversion of the whole array were 5898ms and 5903msrespectively which were rather dierent from the results ofthe indoor experiment In addition compared with themodel analysis results the location error of the actualmonitoring was larger and related to the complexity of ageological structure e location size and direction ofvarious discontinuity surfaces such as fractures joints andfaults in the rock mass all inuence the wave propagation inthe medium Inevitably errors were found in the arrival timerequired for the location because the time was acquired fromthe waveform recorded in the noise environment throughphase identication On the one hand the high-density arraymicroseismic monitoring can extend the quantity of thearrival time data to reduce the signicant impact of thearrival time error On the other hand the high-density

station especially when being three-dimensionally laiddecreases the travel time distance from the source to thevarious sensors and reduces the dierence between spaceand time and the theoretical calculation of the travel timedata caused by the inhomogeneity of the rock mass Insummary benetting from the two abovementioned pointsthe high-density station can eectively improve the locationperformance of the microseismic source of the mine

5 Conclusions

e following conclusions are obtained from this study

(1) eoretical modeling was used herein to analyze thetarget function with the wave velocity nonwavevelocity and source location performance Conse-quently the wave velocity error had a great inuence

100806040200

ndash02ndash04ndash06ndash08

Loca

tion

erro

r (m

)

0 2 4 6 8 10 12Source point

Error in z directionError in y direction

Error in x directionDistance error

(a)

Error in z directionError in y directionError in x direction

Velocity errorDistance error

1 2 3 4 5 6 7 8 9 10 11

0806040200

ndash02ndash04ndash06

1816141210

Loca

tion

erro

r (m

)

6040200ndash20ndash40ndash60ndash80ndash100ndash120

Vel

ocity

erro

r (m

s)

Source point

(b)

Figure 8 (a) Location error distribution under the known wave velocity (b) Location error distribution under the unknown wave velocity

900

800

700

600

500

400

300

200

100

ndash100

0

Loca

tion

erro

r (m

)

ndash15 ndash10 ndash5 0 5 10 15Wave velocity error ()

Seismic source 6

Seismic source 1Seismic source 2Seismic source 3Seismic source 4Seismic source 5

Seismic source 7Seismic source 8Seismic source 9Seismic source 10Seismic source 11

Figure 9 Location distance error distribution of dierent wavevelocity errors

1 2 3 4 5 6 7 8 9 10 11 12

Loca

tion

erro

r (m

)900850800750700650600550500450400350300250200150100

500

ndash50ndash100 Source point

ndash15ndash10ndash5

02

ndash2 51015

Figure 10 Location distance error distribution of dierentpositions

8 Advances in Civil Engineering

on the location result in the target function with thewave velocity and such inuence exponentially in-creased e positioning error was small when thesource point was at the envelope center of themonitoring array e error was larger when thesource point was outside the envelope

(2) e inuence of the station density on the locationerror was analyzed by a eld experiment e ex-perimental results indicated that the inuence of thestation density can be divided into two parts station

quantity and station plane quantity e locationaccuracy signicantly increased with the increase ofthe station quantity when the station plane quantitywas certain When station quantity was more than12 such an increase was no longer obvious Whenthe station quantity is certain the increase of thestation plane quantity can signicantly improve thelocation accuracy e accuracy of the multistationplane was higher than that of the single-station planee best station density was 00192

Loca

tion

erro

r (m

)160

140

120

100

80

60

40

20

0Wholestations

180mplane

140mplane

100mplane

180mplane

+ 140mplane

Shortinclined

sha

Longinclined

sha

(a)

0

5

Loca

tion

erro

r (m

)

35

30

25

20

15

10

Wholestations

180mplane

140mplane

100mplane

180mplane

+ 140mplane

Shortinclined

shaft

Longinclined

shaft

(b)

Figure 11 Relationship between the location error and the sensor position (a) 100m plane seismic source location error (b) 140m planeseismic source location error

2 4 6 8 10 12 14 16 18 20 22 24 26 28 30

50

40

30

20

10

0

Loca

tion

erro

r (m

)

Number of stations

Location errorFitted location errorWhole array location error

(a)

40

ndash2

ndash4

ndash6

ndash8

ndash10

ndash12

6 8 10 12 14 16 18 20 22 24 26 28 30

Derivative

(b)

Figure 12 Relationship between the location error and the number of stations

Advances in Civil Engineering 9

Data Availability

-e data used to support the findings of this study areavailable from the corresponding author upon request

Conflicts of Interest

-e authors declare that there are no conflicts of interestregarding the publication of this paper

Acknowledgments

-e authors would like to express their gratitude to all thosewho helped them during the writing of this thesis First of allthe author is grateful for the site and technical support of themanager and technical staff of the Fuxin Xinmin gold mineSecond the authors are thankful to the postgraduates ofLiaoning Technical University for their help in the experi-ments Lastly the authors would like to thank Editage(httpwwweditagecn) for the English language editing-is work was supported by the National Natural ScienceFoundation of China grant no 51774173 the NaturalScience Foundation of Liaoning Province China grant no201602351 and the Open Fund for the State Key Laboratoryof Seismological Dynamics grant no LED2015B01

References

[1] S J Gibowicz and A Kijko An Introduction to MiningSeismology Academic Press Inc New York NY USA 1994

[2] Y M Yin F X Jiang G X Xie et al ldquoRelation between coal-rock failure andmethane emission based onmicroseismic anddynamic stress monitoringrdquo Journal of Mining and SafetyEngineering vol 32 no 2 pp 325ndash330 2015

[3] A-y Cao L-m Dou G-x Chen S-y Gong Y-g Wang andZ-h Li ldquoFocal mechanism caused by fracture or burst of acoal pillarrdquo Journal of China University of Mining andTechnology vol 18 no 2 pp 153ndash158 2008

[4] Y S Pan Y F Zhao F H Guan et al ldquoStudy on rockburstmonitoring and orientation system and its applicationrdquoChinese Journal of Rock Mechanics and Engineering vol 26no 5 pp 1002ndash1011 2007

[5] L M Dou J He S Y Gong et al ldquoA case study of micro-seismic monitoring goaf water-inrush dynamic hazardsrdquoJournal of China University of Mining and Technology vol 41no 1 pp 20ndash25 2012

[6] X F Xu L M Dou A Y Cao et al ldquoEffect of overlying stratastructures on rock burst and micro-seismic monitoringanalysisrdquo Journal of Mining and Safety Engineering vol 28no 1 pp 11ndash15 2011

[7] S Y Gong L M Dou A Y Cao et al ldquoStudy on optimalconfiguration of seismological observation network for coalminerdquo Chinese Journal of Geophysics vol 53 no 2pp 457ndash465 2010

[8] L Fojtıkova V Vavrycuk A Cipciar and J Madaras ldquoFocalmechanisms of micro-earthquakes in the dobra voda seis-moactive area in the male karpaty mts (little carpathians)Slovakiardquo Tectonophysics vol 492 no 1ndash4 pp 213ndash229 2010

[9] J Rhie and D Dreger ldquoA simple method for simulatingmicroseismic HV spectral ratio in 3D structurerdquo GeosciencesJournal vol 13 no 4 pp 401ndash406 2010

[10] K B Danilov and B Konstantin ldquo-e structure of the onegadownthrown block and adjacent geological objects accordingto the microseismic sounding methodrdquo Pure and AppliedGeophysics vol 174 no 7 pp 2663ndash2676 2017

[11] A V Gorbatikov A V Kalinina V A Volkov J ArnosoR Vieira and E Velez ldquoResults of analysis of the data ofmicroseismic survey at lanzarote island canary Spainrdquo Pureand Applied Geophysics vol 161 no 7 pp 1561ndash1578 2004

[12] D V Popov K B Danilov R A Zhostkov Z I Dudarov andE V Ivanova ldquoProcessing the digital microseismic recordingsusing the data analysis kit (DAK) software packagerdquo SeismicInstruments vol 50 no 1 pp 75ndash83 2014

[13] A Auger and N Hansen ldquoPerformance evaluation of anadvanced local search evolutionary algorithmrdquo in Proceedingsof the 2005 IEEE Congress on Evolutionary Computation no2 pp 1777ndash17842 Edinburgh Scotland September 2005

[14] Y Sato and D Skoko ldquoOptimum distribution of seismicobservationpoints IIIrdquo Bulletin of the Earthquake ResearchInstitute University of Tokyo vol 43 no 1 pp 451ndash457 1965

[15] A T Ringler T Storm L S Gee C R Hutt and D WilsonldquoUncertainty estimates in broadband seismometer sensitiv-ities usingmicroseismicsrdquo Journal of Seismology vol 19 no 2pp 317ndash327 2014

[16] A T Ringler R Sleeman C R Hutt et al Seismometer Self-Noise and Measuring Methods Springer Berlin Heidelberg2015

[17] Z Zhao and R S Zeng ldquoA method for improving the de-termination of earthquake hypocentersrdquo Chinese Journal ofGeophysics vol 30 no 4 pp 379ndash388 1987

[18] J I Sabbione M D Sacchi and D R Velis ldquoRadontransform-based microseismic event detection and signal-to-noise ratio enhancementrdquo Journal of Applied Geophysicsvol 113 pp 51ndash63 2015

[19] L J Dong ldquoMathematical functions and parameters formicroseismic source location without pre-measuring speedrdquoChinese Journal of Rock Mechanics and Engineering vol 30no 10 pp 2057ndash2067 2011

[20] J Li Y T Gao Y L Xie et al ldquoImprovement of microseismiclocating based on simplex method without velocity measur-ingrdquo Chinese Journal of Rock Mechanics and Engineeringvol 33 no 7 pp 1336ndash1346 2014

[21] L J Dong X B Li J Ma et al ldquo-ree-dimensional analyticalcomprehensive solutions for acoustic emissionmicroseismicsources of unknown velocity systemrdquo Chinese Journal of RockMechanics and Engineering vol 36 no 1 pp 186ndash197 2017

[22] M B Zhou J X Wu and W Zhang ldquoMicroseismic sourcelocation method based on small area signal pickuprdquo Safetyand Environmental Engineering vol 22 no 5 pp 154ndash1572015 in Chinese

[23] S Y Gong L M Dou X P Ma et al ldquo-e method to identifythe optimal channel numbers for increasing the locationaccuracy of microseismic events in coal minerdquo Journal ofChina Coal Society vol 35 no 12 pp 2017ndash2021 2012

[24] S Y Gong L M Dou X P Ma et al ldquoStudy on the con-struction and solution technique of anisotropic velocity modelin the location of coal mine tremorrdquo Chinese Journal ofGeophysics-Chinese Edition vol 55 no 5 pp 1757ndash17632012

[25] A Lurka and P Swanson ldquoImprovements in seismic eventlocations in a deep western US coal mine using tomographicvelocity models and an evolutionary search algorithmrdquoMining Science and Technology (China) vol 19 no 5pp 599ndash603 2009

10 Advances in Civil Engineering

on the location result in the target function with thewave velocity and such inuence exponentially in-creased e positioning error was small when thesource point was at the envelope center of themonitoring array e error was larger when thesource point was outside the envelope

(2) e inuence of the station density on the locationerror was analyzed by a eld experiment e ex-perimental results indicated that the inuence of thestation density can be divided into two parts station

quantity and station plane quantity e locationaccuracy signicantly increased with the increase ofthe station quantity when the station plane quantitywas certain When station quantity was more than12 such an increase was no longer obvious Whenthe station quantity is certain the increase of thestation plane quantity can signicantly improve thelocation accuracy e accuracy of the multistationplane was higher than that of the single-station planee best station density was 00192

Loca

tion

erro

r (m

)160

140

120

100

80

60

40

20

0Wholestations

180mplane

140mplane

100mplane

180mplane

+ 140mplane

Shortinclined

sha

Longinclined

sha

(a)

0

5

Loca

tion

erro

r (m

)

35

30

25

20

15

10

Wholestations

180mplane

140mplane

100mplane

180mplane

+ 140mplane

Shortinclined

shaft

Longinclined

shaft

(b)

Figure 11 Relationship between the location error and the sensor position (a) 100m plane seismic source location error (b) 140m planeseismic source location error

2 4 6 8 10 12 14 16 18 20 22 24 26 28 30

50

40

30

20

10

0

Loca

tion

erro

r (m

)

Number of stations

Location errorFitted location errorWhole array location error

(a)

40

ndash2

ndash4

ndash6

ndash8

ndash10

ndash12

6 8 10 12 14 16 18 20 22 24 26 28 30

Derivative

(b)

Figure 12 Relationship between the location error and the number of stations

Advances in Civil Engineering 9

Data Availability

-e data used to support the findings of this study areavailable from the corresponding author upon request

Conflicts of Interest

-e authors declare that there are no conflicts of interestregarding the publication of this paper

Acknowledgments

-e authors would like to express their gratitude to all thosewho helped them during the writing of this thesis First of allthe author is grateful for the site and technical support of themanager and technical staff of the Fuxin Xinmin gold mineSecond the authors are thankful to the postgraduates ofLiaoning Technical University for their help in the experi-ments Lastly the authors would like to thank Editage(httpwwweditagecn) for the English language editing-is work was supported by the National Natural ScienceFoundation of China grant no 51774173 the NaturalScience Foundation of Liaoning Province China grant no201602351 and the Open Fund for the State Key Laboratoryof Seismological Dynamics grant no LED2015B01

References

[1] S J Gibowicz and A Kijko An Introduction to MiningSeismology Academic Press Inc New York NY USA 1994

[2] Y M Yin F X Jiang G X Xie et al ldquoRelation between coal-rock failure andmethane emission based onmicroseismic anddynamic stress monitoringrdquo Journal of Mining and SafetyEngineering vol 32 no 2 pp 325ndash330 2015

[3] A-y Cao L-m Dou G-x Chen S-y Gong Y-g Wang andZ-h Li ldquoFocal mechanism caused by fracture or burst of acoal pillarrdquo Journal of China University of Mining andTechnology vol 18 no 2 pp 153ndash158 2008

[4] Y S Pan Y F Zhao F H Guan et al ldquoStudy on rockburstmonitoring and orientation system and its applicationrdquoChinese Journal of Rock Mechanics and Engineering vol 26no 5 pp 1002ndash1011 2007

[5] L M Dou J He S Y Gong et al ldquoA case study of micro-seismic monitoring goaf water-inrush dynamic hazardsrdquoJournal of China University of Mining and Technology vol 41no 1 pp 20ndash25 2012

[6] X F Xu L M Dou A Y Cao et al ldquoEffect of overlying stratastructures on rock burst and micro-seismic monitoringanalysisrdquo Journal of Mining and Safety Engineering vol 28no 1 pp 11ndash15 2011

[7] S Y Gong L M Dou A Y Cao et al ldquoStudy on optimalconfiguration of seismological observation network for coalminerdquo Chinese Journal of Geophysics vol 53 no 2pp 457ndash465 2010

[8] L Fojtıkova V Vavrycuk A Cipciar and J Madaras ldquoFocalmechanisms of micro-earthquakes in the dobra voda seis-moactive area in the male karpaty mts (little carpathians)Slovakiardquo Tectonophysics vol 492 no 1ndash4 pp 213ndash229 2010

[9] J Rhie and D Dreger ldquoA simple method for simulatingmicroseismic HV spectral ratio in 3D structurerdquo GeosciencesJournal vol 13 no 4 pp 401ndash406 2010

[10] K B Danilov and B Konstantin ldquo-e structure of the onegadownthrown block and adjacent geological objects accordingto the microseismic sounding methodrdquo Pure and AppliedGeophysics vol 174 no 7 pp 2663ndash2676 2017

[11] A V Gorbatikov A V Kalinina V A Volkov J ArnosoR Vieira and E Velez ldquoResults of analysis of the data ofmicroseismic survey at lanzarote island canary Spainrdquo Pureand Applied Geophysics vol 161 no 7 pp 1561ndash1578 2004

[12] D V Popov K B Danilov R A Zhostkov Z I Dudarov andE V Ivanova ldquoProcessing the digital microseismic recordingsusing the data analysis kit (DAK) software packagerdquo SeismicInstruments vol 50 no 1 pp 75ndash83 2014

[13] A Auger and N Hansen ldquoPerformance evaluation of anadvanced local search evolutionary algorithmrdquo in Proceedingsof the 2005 IEEE Congress on Evolutionary Computation no2 pp 1777ndash17842 Edinburgh Scotland September 2005

[14] Y Sato and D Skoko ldquoOptimum distribution of seismicobservationpoints IIIrdquo Bulletin of the Earthquake ResearchInstitute University of Tokyo vol 43 no 1 pp 451ndash457 1965

[15] A T Ringler T Storm L S Gee C R Hutt and D WilsonldquoUncertainty estimates in broadband seismometer sensitiv-ities usingmicroseismicsrdquo Journal of Seismology vol 19 no 2pp 317ndash327 2014

[16] A T Ringler R Sleeman C R Hutt et al Seismometer Self-Noise and Measuring Methods Springer Berlin Heidelberg2015

[17] Z Zhao and R S Zeng ldquoA method for improving the de-termination of earthquake hypocentersrdquo Chinese Journal ofGeophysics vol 30 no 4 pp 379ndash388 1987

[18] J I Sabbione M D Sacchi and D R Velis ldquoRadontransform-based microseismic event detection and signal-to-noise ratio enhancementrdquo Journal of Applied Geophysicsvol 113 pp 51ndash63 2015

[19] L J Dong ldquoMathematical functions and parameters formicroseismic source location without pre-measuring speedrdquoChinese Journal of Rock Mechanics and Engineering vol 30no 10 pp 2057ndash2067 2011

[20] J Li Y T Gao Y L Xie et al ldquoImprovement of microseismiclocating based on simplex method without velocity measur-ingrdquo Chinese Journal of Rock Mechanics and Engineeringvol 33 no 7 pp 1336ndash1346 2014

[21] L J Dong X B Li J Ma et al ldquo-ree-dimensional analyticalcomprehensive solutions for acoustic emissionmicroseismicsources of unknown velocity systemrdquo Chinese Journal of RockMechanics and Engineering vol 36 no 1 pp 186ndash197 2017

[22] M B Zhou J X Wu and W Zhang ldquoMicroseismic sourcelocation method based on small area signal pickuprdquo Safetyand Environmental Engineering vol 22 no 5 pp 154ndash1572015 in Chinese

[23] S Y Gong L M Dou X P Ma et al ldquo-e method to identifythe optimal channel numbers for increasing the locationaccuracy of microseismic events in coal minerdquo Journal ofChina Coal Society vol 35 no 12 pp 2017ndash2021 2012

[24] S Y Gong L M Dou X P Ma et al ldquoStudy on the con-struction and solution technique of anisotropic velocity modelin the location of coal mine tremorrdquo Chinese Journal ofGeophysics-Chinese Edition vol 55 no 5 pp 1757ndash17632012

[25] A Lurka and P Swanson ldquoImprovements in seismic eventlocations in a deep western US coal mine using tomographicvelocity models and an evolutionary search algorithmrdquoMining Science and Technology (China) vol 19 no 5pp 599ndash603 2009

10 Advances in Civil Engineering

Data Availability

-e data used to support the findings of this study areavailable from the corresponding author upon request

Conflicts of Interest

-e authors declare that there are no conflicts of interestregarding the publication of this paper

Acknowledgments

-e authors would like to express their gratitude to all thosewho helped them during the writing of this thesis First of allthe author is grateful for the site and technical support of themanager and technical staff of the Fuxin Xinmin gold mineSecond the authors are thankful to the postgraduates ofLiaoning Technical University for their help in the experi-ments Lastly the authors would like to thank Editage(httpwwweditagecn) for the English language editing-is work was supported by the National Natural ScienceFoundation of China grant no 51774173 the NaturalScience Foundation of Liaoning Province China grant no201602351 and the Open Fund for the State Key Laboratoryof Seismological Dynamics grant no LED2015B01

References

[1] S J Gibowicz and A Kijko An Introduction to MiningSeismology Academic Press Inc New York NY USA 1994

[2] Y M Yin F X Jiang G X Xie et al ldquoRelation between coal-rock failure andmethane emission based onmicroseismic anddynamic stress monitoringrdquo Journal of Mining and SafetyEngineering vol 32 no 2 pp 325ndash330 2015

[3] A-y Cao L-m Dou G-x Chen S-y Gong Y-g Wang andZ-h Li ldquoFocal mechanism caused by fracture or burst of acoal pillarrdquo Journal of China University of Mining andTechnology vol 18 no 2 pp 153ndash158 2008

[4] Y S Pan Y F Zhao F H Guan et al ldquoStudy on rockburstmonitoring and orientation system and its applicationrdquoChinese Journal of Rock Mechanics and Engineering vol 26no 5 pp 1002ndash1011 2007

[5] L M Dou J He S Y Gong et al ldquoA case study of micro-seismic monitoring goaf water-inrush dynamic hazardsrdquoJournal of China University of Mining and Technology vol 41no 1 pp 20ndash25 2012

[6] X F Xu L M Dou A Y Cao et al ldquoEffect of overlying stratastructures on rock burst and micro-seismic monitoringanalysisrdquo Journal of Mining and Safety Engineering vol 28no 1 pp 11ndash15 2011

[7] S Y Gong L M Dou A Y Cao et al ldquoStudy on optimalconfiguration of seismological observation network for coalminerdquo Chinese Journal of Geophysics vol 53 no 2pp 457ndash465 2010

[8] L Fojtıkova V Vavrycuk A Cipciar and J Madaras ldquoFocalmechanisms of micro-earthquakes in the dobra voda seis-moactive area in the male karpaty mts (little carpathians)Slovakiardquo Tectonophysics vol 492 no 1ndash4 pp 213ndash229 2010

[9] J Rhie and D Dreger ldquoA simple method for simulatingmicroseismic HV spectral ratio in 3D structurerdquo GeosciencesJournal vol 13 no 4 pp 401ndash406 2010

[10] K B Danilov and B Konstantin ldquo-e structure of the onegadownthrown block and adjacent geological objects accordingto the microseismic sounding methodrdquo Pure and AppliedGeophysics vol 174 no 7 pp 2663ndash2676 2017

[11] A V Gorbatikov A V Kalinina V A Volkov J ArnosoR Vieira and E Velez ldquoResults of analysis of the data ofmicroseismic survey at lanzarote island canary Spainrdquo Pureand Applied Geophysics vol 161 no 7 pp 1561ndash1578 2004

[12] D V Popov K B Danilov R A Zhostkov Z I Dudarov andE V Ivanova ldquoProcessing the digital microseismic recordingsusing the data analysis kit (DAK) software packagerdquo SeismicInstruments vol 50 no 1 pp 75ndash83 2014

[13] A Auger and N Hansen ldquoPerformance evaluation of anadvanced local search evolutionary algorithmrdquo in Proceedingsof the 2005 IEEE Congress on Evolutionary Computation no2 pp 1777ndash17842 Edinburgh Scotland September 2005

[14] Y Sato and D Skoko ldquoOptimum distribution of seismicobservationpoints IIIrdquo Bulletin of the Earthquake ResearchInstitute University of Tokyo vol 43 no 1 pp 451ndash457 1965

[15] A T Ringler T Storm L S Gee C R Hutt and D WilsonldquoUncertainty estimates in broadband seismometer sensitiv-ities usingmicroseismicsrdquo Journal of Seismology vol 19 no 2pp 317ndash327 2014

[16] A T Ringler R Sleeman C R Hutt et al Seismometer Self-Noise and Measuring Methods Springer Berlin Heidelberg2015

[17] Z Zhao and R S Zeng ldquoA method for improving the de-termination of earthquake hypocentersrdquo Chinese Journal ofGeophysics vol 30 no 4 pp 379ndash388 1987

[18] J I Sabbione M D Sacchi and D R Velis ldquoRadontransform-based microseismic event detection and signal-to-noise ratio enhancementrdquo Journal of Applied Geophysicsvol 113 pp 51ndash63 2015

[19] L J Dong ldquoMathematical functions and parameters formicroseismic source location without pre-measuring speedrdquoChinese Journal of Rock Mechanics and Engineering vol 30no 10 pp 2057ndash2067 2011

[20] J Li Y T Gao Y L Xie et al ldquoImprovement of microseismiclocating based on simplex method without velocity measur-ingrdquo Chinese Journal of Rock Mechanics and Engineeringvol 33 no 7 pp 1336ndash1346 2014

[21] L J Dong X B Li J Ma et al ldquo-ree-dimensional analyticalcomprehensive solutions for acoustic emissionmicroseismicsources of unknown velocity systemrdquo Chinese Journal of RockMechanics and Engineering vol 36 no 1 pp 186ndash197 2017

[22] M B Zhou J X Wu and W Zhang ldquoMicroseismic sourcelocation method based on small area signal pickuprdquo Safetyand Environmental Engineering vol 22 no 5 pp 154ndash1572015 in Chinese

[23] S Y Gong L M Dou X P Ma et al ldquo-e method to identifythe optimal channel numbers for increasing the locationaccuracy of microseismic events in coal minerdquo Journal ofChina Coal Society vol 35 no 12 pp 2017ndash2021 2012

[24] S Y Gong L M Dou X P Ma et al ldquoStudy on the con-struction and solution technique of anisotropic velocity modelin the location of coal mine tremorrdquo Chinese Journal ofGeophysics-Chinese Edition vol 55 no 5 pp 1757ndash17632012

[25] A Lurka and P Swanson ldquoImprovements in seismic eventlocations in a deep western US coal mine using tomographicvelocity models and an evolutionary search algorithmrdquoMining Science and Technology (China) vol 19 no 5pp 599ndash603 2009

10 Advances in Civil Engineering

[26] Y Kovaleva M Ostadhassan N Tamimi and A Kovalev ldquoApreliminary optimization of borehole microseismic arraydesign with a multiple criteria decision analysisrdquo Journal ofApplied Geophysics vol 157 pp 87ndash95 2018

[27] F B Chen ldquoInfluence of distribution of mine microseismiclocating subnet on positioning accuracyrdquo Coal MiningTechnology vol 21 no 4 pp 107ndash114 2016 in Chinese

[28] M H Feng and H Lan ldquoOptimal channel combination fixedpoint test research for improving micro-seismic positioningaccuracy of coal minerdquo China Coal vol 10 pp 38ndash41 2016 inChinese

[29] B X Jia and G Z Li ldquo-e research and application for spatialdistribution of mines seismic monitoring stationsrdquo Journal ofChina Coal Society vol 35 no 12 pp 2045ndash2048 2010

[30] E Ruigrok D Draganov M Gomez et al ldquoMalargue seismicarray design and deployment of the temporary arrayrdquo Eu-ropean Physical Journal Plus vol 127 no 10 p 126 2012

[31] I A Sanina S G Volosov O A Chernykh V E AsmingA M Soldatenkov and O Y Riznichenko ldquo-e design andexperimental use of the Mikhnevo 2D small aperture seismicarrayrdquo Seismic Instruments vol 44 no 1 pp 1ndash11 2008

[32] J Y Hu and S L Li ldquoOptimization of picking mine mi-croseismic P-wave arrival time and its application in reducingerror of source locatingrdquo Machine Building and Automationvol 36 no 10 pp 1940ndash1946 2014

[33] F B Chen J L Liu and Y J Wang ldquoLocation error esti-mation of mine micro-seismic epicenter based on sequencingof P-wave arrival timerdquo Mining Safety and EnvironmentalProtection vol 43 no 6 pp 58ndash62 2016

Advances in Civil Engineering 11

International Journal of

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RoboticsJournal of

Hindawiwwwhindawicom Volume 2018

Hindawiwwwhindawicom Volume 2018

Active and Passive Electronic Components

VLSI Design

Hindawiwwwhindawicom Volume 2018

Hindawiwwwhindawicom Volume 2018

Shock and Vibration

Hindawiwwwhindawicom Volume 2018

Civil EngineeringAdvances in

Acoustics and VibrationAdvances in

Hindawiwwwhindawicom Volume 2018

Hindawiwwwhindawicom Volume 2018

Electrical and Computer Engineering

Journal of

Advances inOptoElectronics

Hindawiwwwhindawicom

Volume 2018

Hindawi Publishing Corporation httpwwwhindawicom Volume 2013Hindawiwwwhindawicom

The Scientific World Journal

Volume 2018

Control Scienceand Engineering

Journal of

Hindawiwwwhindawicom Volume 2018

Hindawiwwwhindawicom

Journal ofEngineeringVolume 2018

SensorsJournal of

Hindawiwwwhindawicom Volume 2018

International Journal of

RotatingMachinery

Hindawiwwwhindawicom Volume 2018

Modelling ampSimulationin EngineeringHindawiwwwhindawicom Volume 2018

Hindawiwwwhindawicom Volume 2018

Chemical EngineeringInternational Journal of Antennas and

Propagation

International Journal of

Hindawiwwwhindawicom Volume 2018

Hindawiwwwhindawicom Volume 2018

Navigation and Observation

International Journal of

Hindawi

wwwhindawicom Volume 2018

Advances in

Multimedia

Submit your manuscripts atwwwhindawicom

International Journal of

AerospaceEngineeringHindawiwwwhindawicom Volume 2018

RoboticsJournal of

Hindawiwwwhindawicom Volume 2018

Hindawiwwwhindawicom Volume 2018

Active and Passive Electronic Components

VLSI Design

Hindawiwwwhindawicom Volume 2018

Hindawiwwwhindawicom Volume 2018

Shock and Vibration

Hindawiwwwhindawicom Volume 2018

Civil EngineeringAdvances in

Acoustics and VibrationAdvances in

Hindawiwwwhindawicom Volume 2018

Hindawiwwwhindawicom Volume 2018

Electrical and Computer Engineering

Journal of

Advances inOptoElectronics

Hindawiwwwhindawicom

Volume 2018

Hindawi Publishing Corporation httpwwwhindawicom Volume 2013Hindawiwwwhindawicom

The Scientific World Journal

Volume 2018

Control Scienceand Engineering

Journal of

Hindawiwwwhindawicom Volume 2018

Hindawiwwwhindawicom

Journal ofEngineeringVolume 2018

SensorsJournal of

Hindawiwwwhindawicom Volume 2018

International Journal of

RotatingMachinery

Hindawiwwwhindawicom Volume 2018

Modelling ampSimulationin EngineeringHindawiwwwhindawicom Volume 2018

Hindawiwwwhindawicom Volume 2018

Chemical EngineeringInternational Journal of Antennas and

Propagation

International Journal of

Hindawiwwwhindawicom Volume 2018

Hindawiwwwhindawicom Volume 2018

Navigation and Observation

International Journal of

Hindawi

wwwhindawicom Volume 2018

Advances in

Multimedia

Submit your manuscripts atwwwhindawicom