principles and applications of microearthquake networks

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224 9. Discussion denser station coverage for a portion of the network area at a time. This allows the permanent stations to monitor the general seismicity of the entire area, and the temporary stations to fill in the details. The average station spacing 5 in a microearthquake network is related to the network areaA and the number of stations N by 5 = (A/N)”‘. Since reducing ( by a factor of 2 requires increasingN by a factor of 4, it is not practical to have small station spacing over a large area. Let us consider the problem of monitoring an area of 100 km x 100 km with a network of 100 stations. If the stations are permanent and distributed evenly over the area, then the average station spacing is 10 km, which is not adequate for some detailed microearthquake studies. An alternative plan is to equip the network with 75 permanent stations and a mobile array of 25 temporary stations. The average spacing for the permanent stations is increased to 1 I .6 km, but the network location capability is not degraded significantly. If we use the mobile array to supplement the permanent stations and to occupy one-tenth of the network area at a time, we will achieve an effective station spacing of 5.6 km. Thus, we can carry out detailed microearthquake studies without increasing the total number of stations. In practice, such a combination of permanent and mobile stations has not yet been fully exploited. There are two major difficulties in operating a microearthquake network on a continuing basis: (1) obtaining adequate financial support and management year after year, and (2) maintaining high standards of quality in network operations, especially with respect to data processing and analysis. A microearthquake network can become unmanageable if the tasks to achieve the desired goals are not clearly defined and performed. For example, if the scientific goal is to map the geometry of active faults in a given area, then it is not necessary to operate the network continuously in time. Furthermore, because the fault geometry can be defined by welllocated earthquakes, it is not necessary to save all the waveform data. The main tasks then are to operate a microearthquake network that surrounds the target area, and to collect first P-arrival times and first P-motion data for precise earthquake locations and fault-plane solutions. It is not easy to strike the proper balance between the desire to collect, process, and analyze as much data as possible, and the ability to perform these tasks with high standards of quality. It is tempting to rely on partial or total automation in the routine operation of a microearthquake network in order to reduce the staff and the cost. However, development and implementation of automatic procedures requires substantial amounts of resources and some lead time. It is easy to overlook this fact and thereby end up with disappointing results.
Automation usually does not reduce costs, but often opens up new possibilities in data analysis. Finally, because a microearthquake network is a complex tool, it is not possible for one person to understand every facet of the network operations and its many practical applications. Successful operation of a microearthquake network requires (1) well-defined tasks to achieve the desired goals; (2) a team of scientists, engineers, and technicians; and (3) effective management and adequate financial support. To get the best results from microearthquake networks also requires sharing experience and collaborating in research on national and international levels.
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PRINCIPLES AND APPLICATIONS OF MICR
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Contents FOREWORD PREFACE vii ix 1.
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Foreword Earthquakes occur over a c
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X PI-
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2 1 . It1 trodir ctivn of the earth
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frequency of occurrence N by (I .2)
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6 1. Introduction the initial P-ons
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8 1. Ititrodiictioti that changes i
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10 1. Introduction Fig. la. Schemat
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12 Fig. b. Map showing seismographi
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14 1. Introduction indicated the la
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~ 16 2. Ins trumeri tic t ion Syste
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18 2. Itistrirmeritation Systems In
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20 2. Ins trumeti ta tim S ys tems
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22 2. Ins tru inen ta t ion Systems
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24 2. Iris trumentrt tion Systems F
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26 2. Itistrutnetztntioti System 5H
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28 2. Instrumentntior? Systems Fig.
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30 2. Instrumentation Systems The o
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32 2. Instrumentation Systems other
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34 2. Instrumentation Systems 1 0 7
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a,No ak) ak) ak) TABLE I Seismic Sy
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38 2. Znstrumentution Systems FREQU
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40 2. Instrumentatiori Systems mome
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42 2. Ins tru rneti totion Sys tenz
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44 2. Instrumentation Systems magne
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3. Data Processing Procedures Micro
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48 3. Datu Processirig Procedures c
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50 3. Data Processitig Procedures c
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52 3. Data Processirig Procedures s
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54 3. Ihta Processing Procedures Se
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56 3. htcr Processirig Procedures w
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58 3. Data Processitig PrmedureLs i
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60 3. Datu Processirig Procedures f
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62 3. Data Processing Procedures Th
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64 3. Dutct Processing Procedures m
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66 3. Data Processing Procedures ch
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68 3. Dutu Processing Procedures an
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70 3. Data Processirig Procedures i
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72 3. Dnta Processing Procedures co
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74 3. Data Processing Procedures se
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4. Seismic Ray Tracing for Minimum
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78 4. Seismic Ray Tracing for Minim
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80 4. Seismic Ruy Trucing for Minim
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(1 84 4. Seismic Ray Tracing for Mi
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88 4. Seismic Ray Tracirig for Mini
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90 4. Seismic Ray Trucing .for Mini
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92 4. Seismic Ruy Tracing for Minim
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% 4. Seismic Ray Tracing for Minimu
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100 4. Seismic Ray Tracing for Mini
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106 5. Inversion and Optimization u
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108 5. Inversion and Optimization G
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110 5. Inversion and Optimization t
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112 5. Inversion and Optimization n
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114 5. Inversion and Optimization n
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116 5. Inversion and Optimization B
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118 5. In versiori nnd Optimization
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120 5. Iwersioti arid Optirnizntior
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122 5. Inversion and Optimization m
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124 5. Inversion and Optimization i
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126 5. Inversion criid Optimization
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128 5. Inversiori niid Optimization
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130 6. Methods of Data Analysk 6.1.
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132 6. Methods of Data Analysis We
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134 6. Methods of Data Analysis x*
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136 6. Methods oj Data Analysis It
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138 6. Methotls of Data Analysis te
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140 6. Methods of Data Analysis pur
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142 6. Methods of Data Analysis (a)
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144 6. Methods qf Dcrtcr Analysis N
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146 6. Methods of Dutcr Analysk imp
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148 6. Methods of Data Analysis sho
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150 6. Methods of Data Aizalysis tr
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152 6. Methods of Data Analysis (6.
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154 6. Methods of Data Analysis qua
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156 6. Methods of Datu Analysls mag
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158 6. Methods of Data Analysis 6.5
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160 6. Methods of Data Analysis (6.
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162 6. Methods of Data Analysis fro
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7. General Applications Data from m
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166 7. General Applications in ampl
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168 7. General Applications Rangely
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170 7. General Applications The inv
Page 213 and 214: 8.1. Seistnicit~ Pritterns 199 made
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Page 217 and 218: 8.1. Seismicit! Plitterrzs 203 betw
Page 219 and 220: Keilis-Borok et al. (1980b) suggest
Page 221 and 222: 8.1. Srismic.itJ Ptrtterns 207 of t
Page 223: 8.2. Temporal V'iricrtions of Seism
Page 229 and 230: 8.3. Temporiil Vuriiitiotis qf Otli
Page 231 and 232: 8.3. TemporuI Variations of Other S
Page 233 and 234: 8.3. Temporal Vcrridoris of‘ Othe
Page 235 and 236: 8.3. Totnportrl Vtrritrtiotis of' O
Page 237: 9. Discussion Microearthquake studi
Page 241 and 242: Glossar? of' A bbreiqiations 227 da
Page 243 and 244: Glossary of AbbrciTintions 229 said
Page 245 and 246: References Acton, F. S. (1970). "Nu
Page 247 and 248: References 23 3 Asada, T. ( 1957).
Page 249 and 250: Rtjfcrcric-es 235 travel-time chang
Page 251 and 252: Refererices 237 Cleary, J. R., Wrig
Page 253 and 254: References Eaton, J. P. (1976). Tes
Page 255 and 256: References 24 1 Francis, T. J. G.,
Page 257 and 258: 243 Hagiwarii. T., and Iwata. T. (1
Page 259 and 260: R efereiices 245 Horner, R. B., Ste
Page 261 and 262: References 247 Kagan, Y. Y., and Kn
Page 263 and 264: Referetices 249 Kodama, K. P., and
Page 265 and 266: 25 1 Lin, M. T., Tsai, Y. B., and F
Page 267 and 268: References 253 Mikumo, T., Otsuka,
Page 269 and 270: R eferetices 255 Nordquist, J. M. (
Page 271 and 272: Re feret ices 257 F'rothero, W. A.
Page 273 and 274: 259 Sauber. J., and Talwani, P. (19
Page 275 and 276: References 26 1 Stephens, C. D., La
Page 277 and 278: Keferetices 263 Tsujiura, M. (1978)
Page 279 and 280: R ef ere1 ices croearthquake observ
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