principles and applications of microearthquake networks

204 8. Applications fm Earthquake Prediction
diagnostic features in the seismicity of an area that will be reliable predictors
of future earthquakes, either in time or in space. Computer algorithms
are formally defined and used to make an objective search of the
data set for the occurrence of specific patterns. When pattern recognition
techniques were first adapted to the seismicity problem in the 1960s and
early 1970s, the only catalog data available were those for the larger,
regional earthquake networks. This restricted the studies to events of
magnitude 4 and greater. More recently, catalogs from microearthquake
networks have become available, and pattern recognition techniques have
been applied to these data as well. Pattern recognition techniques can be
divided into two classes, and are summarized briefly.
In the first technique, temporal variations of seismicity over a region are
characterized by a few, simple time-series functions. Precursory features
of these functions are identified, and then the functions are tested on other
data sets. The definition and development of such functions is discussed,
for example, by Keilis-Borok and Malinovskaya ( 1964) and Keilis-Borok
et al. (1980a). Three time-series functions have been formally defined and
studied. Briefly, these are referred to as pattern B (bursts of aftershocks),
pattern S (swarms of activity), and pattern 2 (cumulative energy).
Pattern B is said to occur when an earthquake has an abnormally large
number of aftershocks concentrated at the beginning of its aftershock
sequence. The occurrence of pattern B was found to precede strong earthquakes
in southern California, New Zealand, and Italy (Keilis-Borok ef
al., 1980a).
Pattern S is said to occur when a group of earthquakes, concentrated in
space and time, happens at a time when the seismicity of the region is
above normal. This pattern may be considered as a variation of pattern B,
although it is computed over a much longer time window. Keilis-Borok et
ul. (1980a) reported that in southern California all earthquakes predicted
by pattern B were also predicted by pattern S: there were seven successful
predictions, one failure to predict, and one false prediction.
Pattern c is said to occur when the sum of the earthquake energies,
raised to a power less than 1 and computed using a sliding time window,
exceeds a threshold value for that region. The summation is carried out
for earthquakes with magnitude less than the magnitude of the earthquake
to be predicted. The success of pattern c as a predictor depends critically
on the choice of the threshold level and on the consistency with which
earthquake magnitudes are calculated. Pattern 2 has had some success as
a predictor in California, New Zealand, and the region of Tibet and
the Himalayas (Keilis-Borok et al., 1980a,b).
These patterns (B, S, and x) are computed from seismicity over a broad
region and are not capable of defining the focal region of a predicted event.