principles and applications of microearthquake networks

74 3. Data Processing Procedures
semiautomated method, and is ideally suited for a microearthquake network
of about 70 stations, which are recorded on four rolls of microfilms.
3.5.3. Automated Method
In the automated method, digitized seismic data are first set up in a
computer, the first P-arrival times and other phase data are determined by
some algorithm, and the hypocenter parameters are then calculated by the
computer. The complete processing procedure is performed automatically
without the analyst’s intervention. At present, several automated data
processing systems for microearthquake networks have been reported
(e.g., Crampin and Fyfe, 1974; Watanabe and Kuroiso, 1977; Stewart,
1977).
In theory, the automated method looks very attractive because it frees
the analyst from doing tedious work. In practice, however, the automated
method is limited by two factors: (1) the complexity of incoming signals
generated by a microearthquake network; and (2) the difficulty in designing
a computer system that can handle this complexity. The most serious
problem is distinguishing between seismic onsets and nonseismic transients.
An analyst can rely on past experience, whereas it would be difficult
to program a computer to handle every conceivable case.
Some simple schemes have been devised to minimize or eliminate the
effect of erroneous arrival times on the computed hypocenter parameters.
For example, the signal-to-noise ratio at a station generally decreases with
increasing distance from the earthquake hypocenter. Therefore, the
P-arrival times from stations at greater distances should be given less
weight. This weighting can be applied either according to the chronological
order of first P-arrival times (Crampin and Fyfe, 1974) or according to
epicentral distances to stations (Stewart, 1977). Large arrival time residuals
calculated in a hypocenter location program are often caused by a large
error in one or more first P-arrival times. Therefore, arrival times with
large residuals should be given less weight or discarded. For instance,
Stewart (1977) was able to improve the quality of the hypocenter solution
by discarding the arrival time with the largest residual and relocating the
event.
Several studies have been reported that compare the performance of
automated data processing techniques with that of an analyst. For example,
Stewart (1977) compared the results from his real-time processing
system with those obtained by a routine manual processing method. His
system monitored 91 stations of the USGS Central California Microearthquake
Network. For the period of October 1975 the routine processing
method located 260 earthquakes using data from 150 stations. Stewart’s