Seismic Reflection Views of the 1994 Northridge Earthquake Hypocentral Region Using Aftershock Data and Imaging Techniques

SERGIO CHÁVEZ-PÉREZ and JOHN N. LOUIE
SEISMOLOGICAL LABORATORY/174, MACKAY SCHOOL OF MINES, UNIVERSITY OF NEVADA, RENO, NV 89557, USA.
INTERNET: sergio@seismo.unr.edu & louie@seismo.unr.edu
URL: http://www.seismo.unr.edu/htdocs/students/CHAVEZ/curee97/curee97.html
Presented at the Northridge Earthquake Research Conference, Aug 20-22, 1997, Los Angeles, California, USA.

SUMMARY


Earthquake hazard assessment in the San Fernando Valley, California, requires knowledge of the existence and geometry of blind thrust faults. We show that crustal-scale reflection imaging for this region is feasible using aftershock data from a regional network of short-period vertical seismometers. We image regional fault structures based on the reflectivity structure beneath the hypocentral region of the 1994 Northridge earthquake. Our work combines simple data editing and imaging techniques borrowed from exploration seismology. Our results show the potential of migrated depth sections in defining major reflectors and strongly suggest that the use of existing aftershock data offers a cost effective and straightforward alternative for an integration of seismic reflection data in this and similar areas.

INTRODUCTION


The broad destruction caused by the 17 January 1994 Northridge earthquake on a thrust fault buried in the heavily-urbanized San Fernando Valley, California, emphasizes the need for better understanding of the structure and potential hazard of blind thrust fault systems.

Acoustic imaging using exploration seismology tools and earthquake sources allows us to produce reflection views of the crust to depths where other data are commonly not available. For instance, Revenaugh (1995a, b) has recently proven that analyses of scattered waves using stacking and Kirchhoff migration are rather useful for the evaluation of generalized site effects and earthquake hazard.

The close spatial distribution of Northridge aftershocks illuminates structures not previously mapped at depth (Hauksson et al., 1995). In this case a reliable velocity structure over the three-dimensional (3-d) array of sources (aftershocks) and receivers (network stations) provides the information needed to locate crustal reflectors in cross sections or 3-d volumes.

The main purpose of this work is to image the structure beneath San Fernando Valley using Northridge aftershocks and a combination of simple data editing and imaging techniques commonly used for oil exploration.

DATA


Our data are short-period vertical component seismograms from the Southern California Seismic Network (SCSN) provided through the Southern California Earthquake Center Data Center. We use well-located, A-quality aftershocks (magnitude 3 and greater) lying within 3 km depth.

Fig. 1 provides an example of the short-period data we use for our imaging purposes. As in oil industry seismic-reflection surveying, imaging of structure through high-frequency reflectivity demands high-multiplicity data, or a large number of overlapping sources and receivers. Despite the intrinsic limitations of close source spacing (because of multiple events) and wide station spacing, our initial work (Chávez-Pérez and Louie, 1995) showed that a small cluster of tens of aftershocks has the spatial sampling needed to image crustal reflectors in this area.


FIGURE 1. EXAMPLE OF A RECORD SECTION. RAW DATA, REDUCED TIME.


To project a reflected wave in a seismogram to a reflector location one needs to know the time of the arrival, and be able to characterize it as having significant amplitude within the seismogram. Stacking and migration find events that have some coherency across a source-receiver array (of events in this case) and sum amplitudes to reject uncorrelated noise. We can thus obtain coherent reflections, for instance, by common midpoint stacking (Chávez-Pérez and Louie, 1995) to improve the signal-to-noise ratio or even by simple vertical stacking. In our case, for the sake of attaining coherent summations, we use data with high-quality impulsive P-wave picks to roughly correct for sign reversals due to varying focal mechanisms.

Clipped and saturated records are quite common in short-period data. We regard them as sign-bit recordings (O'Brien et al., 1982). Thus, with sufficient data redundancy, stacking and migration allow us to recover geometric information. Record sections include 200 km in epicentral distance and 30 s duration to include wide-angle reflections between first compressional, Pg, and first shear, Sg, arrivals. We mute outside the window between Pg and Sg traveltime branches to extract only compressional arrivals, mostly Pg, PmP and S-P converted energy. Preprocessing includes bandpass filtering and trace equalization for intersource amplitude balancing (i.e., the amplitudes are normalized so that the mean-squared amplitude over the whole trace is the same for all traces). This is roughly equivalent to energy normalization for varying magnitudes.

CRUSTAL REFLECTIVITY


Based on subsurface projection of surface geology and integration of deep oil-well data, Davis and Namson (1994) proposed a balanced cross-section of the 1994 Northridge earthquake. They interpreted the Santa Susana Mountains and Santa Monica mountains anticlinoria as crustal-scale fault-propagation folds above the Pico and Elysian Park thrusts, respectively. If this is the case, expected reflections would be coming from the main thrust faults and a mid-crustal detachment where the Elysian Park thrust supposedly roots at ~22 km depth (Davis and Namson, 1994). However, picking fault locations and interpreting the core of a fault-propagation fold are problematic because of large lateral velocity changes. Most of the reflected events should arise from the basal detachment and depth migration is required to obtain a reasonable image of the subsurface.

Kirchhoff depth migration is an imaging technique that produces an estimate of subsurface reflectors. One fundamental assumption used in this process is that the primary reflected energy, when treated as a P-P scattering problem, is isotropic (Wu and Aki, 1985). Thus, we obtain images by summing the data at traveltimes computed through a background velocity model.

The Kirchhoff depth migration process we use is similar to that utilized by Louie et al. (1988). The depth migration is a mapping or back projection of assumed primary reflection amplitudes into a depth section. It has been identified by Le Bras and Clayton (1988) as the tomographic inverse of the acoustic wave equation under the Born approximation in the far field, utilizing WKBJ rays for downward continuation and two-way reflection travel time for the imaging condition. We compute traveltimes with Vidale's (1988) finite-difference solution to the eikonal equation.

Depth sections depict reflectivity along a 50 km south-north migration profile (Fig. 2) by using 3-d Kirchhoff depth migration with Hadley and Kanamori's (1977) one-dimensional (1-d) P wave velocity model shown in Table 1.



FIGURE 2. MAP LOCATING THE 1994 NORTHRIDGE, CALIFORNIA, MAIN SHOCK (M6.7), AFTERSHOCKS (M3 AND GREATER, CLOSED DIAMONDS), THE MIGRATION PROFILE (SOUTH-NORTH LINE) AND SOME NETWORK STATIONS (CLOSED SQUARES).


Velocity, km/sDepth, km
5.5 0.0-5.5
6.3 5.5-16.0
6.7 16.0-32.0
7.8 32.0- ...

TABLE 1. HADLEY AND KANAMORI'S (1977) FLAT-LAYER VELOCITY MODEL FOR SOUTHERN CALIFORNIA.


Figure 3 shows that the final depth imaging result is obtained by stacking the migrated partial images for each event. Note here that data in each record section is defined only by a window of compressional arrivals (depicted by the gray fans).

DISCUSSION AND SYNOPSIS


One of the major problems with depth migration is image resolution. When we apply the method to data with limited observation geometry, artifacts or false images appear and make the results difficult to interpret. In this case sparse receiver coverage causes artifacts along elliptical trajectories in the migrated depth section, and unfocusing of P-S and S-P converted energy also contributes to image degradation.

Figure 4a shows a crustal reflectivity depth section of data from 27 A-quality aftershocks (823 seismograms) lying within 3 km depth. Datum is at sea level. Black depicts positive reflectivity, white depicts negative reflectivity and gray depicts no reflectivity.


FIGURE 3. MIGRATION OF RECORD SECTIONS. EACH RECORD IS MIGRATED INDIVIDUALLY ALONG THE MIGRATION PROFILE SHOWN IN FIG. 1. RESULTS ARE SUMMED TO ESTIMATE CRUSTAL REFLECTIVITY.


Artifacts due to poor reflection coverage show kinks in the nearly vertical trajectories they define. These are due to propagation through the 1-d velocity model and we can see them at the deepest interface, the Moho, at about 32 km depth. Strong dipping reflectors appear that do not follow the trajectories defined by the artifacts. They seem to correlate closely with the position of the Pico and Elysian Park thrusts, but extend below the projected depth of the proposed mid-crustal detachment. Note that there is a dipping reflector almost parallel to the Elysian Park thrust. We can also distinguish some nearly horizontal reflectors at depths between 20-30 km.

Figure 4b shows the depth section of Fig. 4a with Northridge main shock, A-quality aftershocks (magnitude 3 and greater) at all depths, and the thrust faults and mid-crustal detachment, proposed by Davis and Namson (1994), superimposed. Note how the Pico and Elysian Park thrusts correlate with some of the main dipping reflectors. This is how we can devise tests for current geological models of the area.

Existing aftershock data for the Northridge hypocentral area offers a cost effective alternative for an integration of seismic reflection data in this and similar areas. Our ongoing work focuses on improving structural definition and detail.


FIGURE 4. a) CRUSTAL REFLECTIVITY ALONG THE MIGRATION PROFILE (FIG. 1). ELLIPSES DEPICT COHERENT REFLECTIONS. b) SAME IMAGE AS IN (a) WITH NORTHRIDGE MAIN SHOCK, AFTERSHOCKS AND THE PROPOSED INTERPRETATION OF DAVIS AND NAMSON (1994) SUPERIMPOSED.


ACKNOWLEDGMENTS


This work was funded by a US National Science Foundation grant (EAR-9416224). The first author acknowledges financial support by CONACYT, Mexico's National Council for Science and Technology. Aftershock data were recorded by the Southern California Seismic Network (SCSN) which is operated jointly by the Seismological Laboratory at Caltech and the US Geological Survey, Pasadena, CA. We thank K. Hafner for giving us access to the SCSN data center. Steven Jaumé obtained the data set we used.

REFERENCES


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