Seismic Wavefield Calibration of the Korean Peninsula Topic 2 – Seismic Calibration and Ground Truth Collection

Seismic Wavefield Calibration of the Korean Peninsula

Topic 2 – Seismic Calibration and Ground Truth Collection
R. B. Herrmann

Department of Earth and Atmospheric Sciences

Saint Louis University

1. 
   Summary
   

This proposal addresses the calibration of seismic wave propagation in the Korean peninsula to improve confidence in locations, to determine source mechanisms of seismic events through waveform inversion, to describe the high frequency attenuation of regional phases and to provide a catalog of calibrated events for other studies. This effort is possible because of cooperation with Dr. Kiehwa Lee of Seoul National University and Dr. Duk Kee Lee of the Korean Meteorological Research Institute to address their research on seismic hazard. This cooperative effort provides access to KMA (Korea Meteorological Administration) and KIGAM (Korean Institute of Geology and Mining) digital data sets. The connection with Korea is furthered by the participation of Young-Soo Jeon as a post-doc for the duration of the effort and Hyun-jae Yoo as a visiting researcher for the first 6 months of the proposal.

The scientific problems to be addressed are the suitability of joint inversion of surface-wave dispersion and receiver functions for the determination of a crustal model adequate for waveform modeling, the effect of adding travel time constraints to that inversion, the fine tuning of the crustal model for source parameter determination, and, if possible, the collection of ground truth.

Seismic Wavefield of the Korean Peninsula

Topic 2 – Seismic Calibration and Ground Truth Collection
R. B. Herrmann

Department of Earth and Atmospheric Sciences

Saint Louis University

2. 
   Narrative
   

2.1 Introduction
The Korean peninsula occupies the southeastern part of the North China Block or Sino-Korean craton (Fitches et. al, 1991) in the Eurasian plate. It is an important tectonic link between eastern China and the Japanese Islands. The peninsula represents a denudation remnant of deformed basement rocks and sedimentary successions as well as granitic intrusions and volcanics, concealing a long history of basin formation and crustal deformation. The

peninsula has three major Precambrian massifs, viz., Nangrim, Kyonggi, and Yongnam massifs in the north, central and southern part of the peninsula. The massifs are associated with the higher elevations. In the southeast, the Cretaceous Kyongsang Basin has gently eastward-dipping successions of nonmarine sediments (Chough et al., 2000). Figure 1 presents a surface geology map of the peninsula. The Bouguer gravity map, Figure 2, has negative residuals that correlate with the massifs. Other than the southeast, the peninsula is characterized by old rocks.

Analysis of earthquake data to improve crustal structure models and to define earthquake source parameters has progressed slowly because of the low rate of seismic activity ( ~ 50 earthquakes located annually in the south) and the lack of quality data. The second issue was recently addressed by the installation of modern digital seismograph systems by KMA and KIGAM. Newly instrumented sites have a 3-component strong motion sensors and short period velocity sensors, or broadband sensors. The data sets on local earthquakes are slowly growing in size. Selected teleseisms are achived.
Moment tensor source inversion has been performed by Kim and Kraeva (1999) and Kim et al (2000). (I note that one of the two Korean events studied has a seismic moment 4 times too large because of the use of an incorrect gain for the INCH LH channels).



Figure 1. Simplified geology map of Korea

Using C. J. Ammon's codes, Kim and Lee (2001), Kim et al (1998) and Yoo (2001) used the teleseismic P-wave receiver function technique to estimate crustal structure variations within the peninsula. The Kim and Lee (2001) study is quite extensive but can be extended using additional waveform data, domain, rather than water level, deconvolution techniques and by the addition of other data, such as surface-wave dispersion or body-wave travel times.

Travel time studies have been performed using limited data sets. References to many of these models are found in Kim and Lee (2001). Song and Lee (2001) used the VELEST program to estimate structure from published KMA arrival times, but were hampered by a very small data set of 178 travel times from 29 earthquakes. A plot of first arrival times for an initial location based on the Kim and Kim (1983) velocity model, showed a simple linear trends corresponding to velocities of 6.3 and 8.0 km/sec from which an average crustal thickness of 35 km is inferred.

Figure 2 Bouguer gravity map of Korea and the neighboring region. Note the very negative anomalies in the northern part of the country.

2.2 Source parameter determination

Dr. Duk Kee Lee of KMRI visited Saint Louis University at the end of November, 2002, and brought event recordings from 8 events made by the KMA network. These events had local magnitudes in the range of 3.4-4.1 and

were the larger events recorded over a two year period. The preliminary event locations of the data set were as follow:

Time	Lat	Lon	H	M
990602091223.3	35.89	129.31	10	3.4
000411194401.4	36.91	125.26	10	3.5
001209185100.0	36.48	129.98	10	3.7
010629022107.8	35.78	126.60	13	3.6
010723082914.2	35.44	128.60	12	3.5
011121014912.0	36.72	128.28	7	3.5
011124071031.6	36.74	129.87	10	4.1
020708190151.2	35.93	129.62	12	3.8

While the purpose of the data set was to investigate its usefulness for defining the attenuation of high frequency S-waves, initial review of the digital data showed that only two of the eight events had sufficient low frequency signals to permit application of a waveform modeling technique to obtain focal mechanisms. The limitation in using data from small events is the local microseism noise level which is depends upon the time of year. These two events both occurred in November, one on 21 NOV 2001 and the other on 24 Nov 2001 and were both well recorded by the combined KMA and KIGAM seismic networks. Figure3 shows the locations of the earthquake and the broadband stations that recorded the 21 NOV 2001 event. Data are also available from the accelerometers and short period sensors at these and other locations which are not discussed here. The broadband stations are at distances of 83 – 205 km from the event.

Figure 3. Location of broadband stations recording the 21 NOV 2001 earthquake (yellow star)

Waveform inversion was initially performed using only the traces at SEO, ULJ and TAG which had clean records. The CUS model was used because its Green's functions matched the P – Surface wave interval time better than the Song and Lee (2001) model. The program used was wvfgrd96 which is described in Computer Programs in Seismology 3.20 – Source Inversion (2002). Figure 4 compares the observed and predicted waveforms for this event for all the stations shown in Figure 3. The ground velocity traces are bandpass filtered in the 0.02 – 0.10 Hz band. The source depth used was 13 km, the Mw = 3.44 and the mechanism has a strike of 15, dip of 65 and a rake of 150 degrees. The fits are quite good but indicate a tendency for the synthetic surface-wave arrival to occur slightly later than the observed. Part of this is due to the discrete distances at which the Green's functions were computed. SNU and SEO are 143 and 148 km from the source, respectively, and the program used Green's functions at 145 and 150 km, respectively. This concern over time shifts is important if high frequencies are used in the inversion, which may be necessary for even smaller events.

Figure 5 compares the observed and predicted waveforms for the bandpass filter range of 0.02 – 1.0 Hz (SAC command bp c 0.02 1.0 np 2 ). The difference between the observed and predicted traces is less than a factor of 2 for some of the traces, which is surprising given the simplicity of the crustal model used for the Green's functions.

Figure 4. Comparison of observed (light gray) and predicted (dark) traces at each station. The trace pairs for a given component are plotted with the same scale and the peak amplitudes are indicated for each. Each trace is 80 sec long and starts at a time r/8.0 -5.0 sec after the origin.

Figure 5. Comparison of observed and predicted ground velocity traces at frequencies < 1.0 Hz.

A detailed discussion of this event and that of 24 NOV 2001 is given at

http://www.eas.slu.edu/People/RBHerrmann/KOREA.2003/

The interesting fact is that waveform inversion was successfully applied to 2 of the 43 earthquakes located during 2001. Having demonstrated the ability to obtain source parameters the challenge is to extend this to events which have lower signal-to-noise ratios because of smaller size or increased seasonal noise.

2.3 Structure Inversion
Julia et al (2000, 2003) implemented a joint inversion of surface-waves

and receiver functions for crustal structure beneath a station. The many broadband stations in the Republic of Korea operated by KMA and KIGAM permit such the application of such and inversion technique. Application of this technique requires quality receiver functions, good dispersion and a starting model that does not bias the results.

Mr. Hyun-Jae Yoo of Seoul National University collected teleseisms recorded at 25 locations which had KMA and KIGAM instruments. Most of the events were from Indonesia, with a few from India/Afghanistan and Alaska. All waveforms were examined for a P-wave arrival with good signal-to-noise and the better ones were processed using the time-domain deconvolution technique of Ligorria and Ammon (1999). The implementation saves a goodness of fit parameter in the SAC header of the receiver function which indicates the ability of the receiver function to predict the filtered radial component, with 100% being a perfect prediction. All receiver functions with at least an 80% goodness of fit were identified. Because of the small variation in ray parameter, a presumed simple structure beneath Korea and the lack of significant azimuthal coverage, the individual traces for Gaussian filter parameters ALPHA = 1.0 and 2.5 were stacked to create a data set two receiver functions for each station. Figures 6 and 7 show the station locations and the stacked receiver functions, respectively. Inversions with the stacked data were faster than with using the many individual traces, but the resulting model did nmot differ significantly.
Stations of the KMA network were initially deployed at local KMA offices in cities, which were noisy. In addition some of the KMA sites were near KIGAM stations. Subsequently KMA stations were redeployed to provide broader national coverage from quieter sites. Good coverage is possible because of data stream exchange between KMA and KIGAM.
The shaded area display of the receiver function stacks in Figure 7 was

organized by receiver function similarity using a cluster analysis. If the receiver functions are controlled by crustal structure, then geographically adjacent stations should have adjacent receiver functions.

The Rayleigh-wave dispersion data available were sparse. A single dispersion curve was used for all stations, even for the island stations of ULL, SOG and SGP. The group velocities were taken from Stevens and Adams (2000) by asking the program for the dispersion between two points 1 degree apart in latitude. In addition, a few phase velocity dispersion points were obtained from a p-omega stack of teleseisms propagating across the array of broadband stations.
Stable inversion requires constraints and a conscious decision to prevent persistence of initial model detail in the final inversion results. The same starting model and processing scripts were used for each of the 25 stations so that results could be compared. The starting model was based on AK135 (Kennett et al, 1995) with the upper 50 km having the velocities fixed at their 50 km values. In this case, the receiver function and dispersion data are required to define the crustal structure and the sharpness of the Moho. Layering consisted of twenty-five 2 km thick, followed by ten 5 km thick and finally ten 10 km thick layers to yield a 200 km thick model. The halfspace velocities were fixed, and the model was constrained to be very smooth beneath a 50 km depth.

 Figure 6. Location of broadband stations used for receiver function analysis

The fit to the receiver functions and surface wave dispersion was such that 96% of the signal power in the receiver functions and 99% if the signal power in the dispersion data were fit.

 Figure 7. Receiver function stacks for the two Gaussian filter parameters used. The number adjacent to each receiver function indicates the number of individual receiver function in the stack.

Figures 8 and 9 show the 25 models and also the model predicted P-wave first arrival times for a surface source depth. Most inversions share the same features, as expected from the similarity of all receiver functions other than for ULL, SOG and SGP. The first arrival time predictions for each model, including ULL, OSG and SGP, are similar and in qualitative agreement with the Song and Lee (2001) simplified crustal velocity structure.
As an independent test on the models, waveform integration synthetics were computed in an attempt to use a Korean velocity model for waveform inversion of the 21 NOV 2001 earthquake instead of the Central U. S. model (CUS). As will be seen below, this was not successful since these models predicted later surface-wave arrivals than observed. Since the inversion derived the P-wave arrival times from the shear-wave velocities based on the initial Vp/Vs ratios, inversions were rerun using different values of these ratios. This was not sufficient to improve the fit.

Figure Figure 8 Joint inversion model for each station. The solid black line is the mean model of all stations except for the stations on the two islands.

Figure 9. Predicted P-wave arrival travel times for each model

Figure Figure 10. Models arising from additional dispersion constraints.

To force a better fit to the surface-wave arrivals the original dispersion set was augmented by the theoretical Love- and Rayleigh-wave fundamental mode phase and group velocity dispersion between 4 and 30 seconds, the bandwidth of the surface-waves shown in Figures 4 and 5. Figures 10 and 11 compare the models and the predicted P-wave travel times.

Figure 11. Predicted P-wave travel times for inversion constrained with additional dispersion values.

The similarity of the predicted travel times is not surprising since the additional dispersion data provided strong constraints on the upper crustal velocities. The subtle variations in the models are sufficient to fit all receiver functions well, except for the island stations. Figure 12 compares the observed and predicted receiver stacked receiver functions using the model obtained for each station. The models capture most features in the receiver functions. Figure 13 illustrates the differences in the two inversion to highlight the consequence of adding additional dispersion data. The primary effect is to make the crust faster.

Figure 12. Figure 12. Comparison of observed (red) and predicted (blue) receiver functions for each of the stations. The integer indicates the number of traces used to form each stack.

Figure Figure 13. SNU models: Red - original inversion; Blue - inversion with CUS model dispersion constraints.

Synthetic were computed using the new SNU model and the new mean model of Figure 10 and provided better fit to the waveform data for the 21 NOV 2001 earthquake. This is not surprising since the CUS dispersion was used to constrain the model.

2.4 Lessons learned
It is very easy to derive earth models that fit receiver functions and surface-wave dispersion. However, if the objective is to have an earth model for precise modeling of broadband digital seismic data from small events recorded at short distance, the models must be able to predict the surface wave signals in the 4 – 20 second period range to within a fraction of a period for a simple waveform inversion technique to succeed. A simple technique is defined as one whose Green's functions match the observed signal in terms of absolute trace time, perhaps from the P-wave through the surface-wave arrivals. The requirements are less severe for large events which have sufficient long-period signal whose propagation is less dependent upon detailed crustal structure.

5. 
   Research Objectives
   

The objective of this research is to provided improved seismic velocity models for the Korean peninsula that will improve location and source parameter information to include mechanism, seismic moment and depth. Because of the very low levels of natural and man-made seismicity all available data and tools will be used to accomplish this effort.

The following must be done:

• 
  Analyze local, regional and teleseismic surface-wave signals to improve the Love and Rayleigh-wave phase and group velocity dispersion model for the Korean peninsula. These results will be compared to global and broader regional models developed by other groups. In addition new techniques for processing by treading the broadband network as a very large aperture array.
  
• 
  Pick arrival times from all local event data and relocate the events using the seismic velocity models developed. Use the arrival time set to define the 3-D crustal structure.
  
• 
  Analyze teleseismic P-wave residuals to investigate their use as an added constraint on station specific models.
  
• 
  Use waveform inversion techniques to inverse local waveforms as a step in defining a 3-D crustal structure for the region.
  
• 
  Invert regional and local event broadband waveforms for source parameters.
  
• 
  Document data, data processing and derived models of structure of sources and structure for inclusion into the NNSA/LLNL data base.
  

2.6. References
Chough, S. K., S. T. Kwon, J. H. Ree, and D. K. Choi (2000). Tectonic and sedimentary evolution of the Korean peninsula: a review and new view, Earth-Science Reviews, 52, 175-235.
Fitches, W. R., C. J. N. Fletcher, and X. Jiawei (1991). Geotectonic relationships between cratonic blocks in E. China and Korea, J. Southeast Asian Earth Sci. 6, 185-199.
Herrmann, R. B., and C. J. Ammon (2002). Computer Programs in Seismology 3.20 – Source Inversion, Saint Louis University,

http://mnw.eas.slu.edu/People/RBHerrmann/ComputerPrograms.html
Kennett B.L.N., Engdahl E.R., Buland R. (1995). Constraints on seismic velocities in the earth from travel times Geophys. J. Int, 122, 108-124.
Kim, S. K. and S. G. Kim (1983). A study on the crustal structure of south Korea by using seismic waves J. Korean Institute of Mining Geology 16, 51-61 (in Korean).
Kim, S. G., and N. Kraeva (1999). Source parameter determination of local earthquake in Korea using moment tensor inversion of single station data, Bull. Seism. Soc. Am. 89, 1077-1083.
Kim, S. G., N. Kraeva, and Y.-T. Chen (2000). source parameter determination of regional earthquakes in the far East using moment tensor inversion of single-station data, Tectonophysics 317, 125-136.
Kim, S. G., and S. K. Lee (2001). Moho discontinuity studies beneath the broadband stations using receiver functions in South Korea, Korean Society of Hazard Mitigation 6, 139-155.
Kim, S. G., S. K. Lee, M. S. Jun and I. B. Kang (1998). Crustal structure of the Korean peninsula from broadband teleseismic records by using receiver function, J. Economic and Environmental Geology 31, 21-29.
Julia, J., C. J. Ammon, R. B. Herrmann and A. M. Correig (2000). Joint inversion of receiver function and surface-wave dispersion observations, Geophys. J. Int. 143, 99-112.
Julia, J. C. J. Ammon and R. B. Herrmann (2003). Lithospheric structure of the Arabian Shield from the joint inversion of receiver functions and surface-wave group velocities, Tectonophysics, (submitted).
Ligorria, J. and C. J. Ammon (1999). Iterative deconvolution of teleseismic seismograms and receiver function estimation, Bull. Seism. Soc. Am., 89, 1395-1400.
Song, S. and K. Lee (2001). Crustal structure of the Korean peninsula by travel time inversion of local earthquakes, J. Korean Geophysical Society 4, 21-33.
Stevens, J. L., and D.A. Adams (2000). Improved surface wave detection and measurement using phase-matched filtering and improved regionalized models, Proceedings of the 22 Annual DOD/DOE Seismic Research Symposium, 12-15 September 2000.
Yoo, H. J., and K. Lee (2001). Crustal structure under the Taejon (TJN) station by receiver function methods, J. Korean Geophysical Society 4, 35-46.

3. 
   Technical Approach
   

Phase I.

Task I. Data acquisition and QC
This task focuses on augmenting the current preliminary data base by acquiring more data from KMA and KIGAM, with their cooperation. This is possible only because of the cooperation on other projects with Drs. Kiehwa Lee and Duk Kee Lee. The mechanism for data delivery to LLNL has been implemented.

Milestone: Collect data

Deliverable: Digital data, arrival times and locations to LLNL
Task II. Surface-wave analysis
This task focuses on improving phase and group velocity dispersion for the peninsula. Dispersion in the 0.5 – 2.0 Hz frequency band from small explosions in the region will be examined to provide necessary constraints on shallow structure. Access to some of the proprietary data can only be made internally by NNSA laboratories.

Milestone: Improved dispersion curves

Deliverable: Raw dispersion data and final values
Phase II.
Task I. Data acquisition and QC
Because of the low level of seismic activity, additional data must be accessed as events occur.
Task III. Model crustal structure
Determine crustal structure models that are consistent with all data – teleseismic, regional and local.

Milestone: Tested crustal model(s)

Deliverable: Model parameterization and documentation

3. 
   Proposed Schedule
   

Task I: Months 1 – 24

Task II: Months 1 – 12

Task III: Months 13 – 24

Deliverables will be made commensurate with the semi-annual reviews.

3. 
   Key Personnel
   

R. B. Herrmann is the PI of this proposal. He has over 30 years experience with the nuclear monitoring program. A shorted vita follows:

Robert B. Herrmann, Ph.D. (1974) in Geophysics, Saint Louis University

Professor of Geophysics (1983) Saint Louis University

Associate Professor of Geophysics (1978-1983) Saint Louis University;

Assistant Professor of Geophysics (1975-1978) Saint Louis University;

Post-doctoral Research Associate (1974-1975) Cooperative Institute

for Research in the Environmental Sciences/University of Colorado/

NOAA;

Research Assistant (1972-1974) Saint Louis University;

NSF Graduate Fellow (1967-1969,1971-1972);
Member AFTAC Seismic Review Panel (1988- )

Military Service: Lt. Col., USAR-EN (Ret)

Recent publications:

• 
  Mokhtar, T.A., Ammon, C.J., Herrmann, R.B., and Ghalib, H.A.A. (2001). Surface wave velocities across Arabia. PAGEOPH 158, No. 8, pp. 1425-1444.
  
• 
  Missouri Seismic Safety Commission, December, 1999. Earthquakes and Missouri: 1999 Report to the Governor, (editor).
  
• 
  Missouri Seismic Safety Commission, May, 1998. Earthquakes and Missouri: 1998 Report to the Governor, (editor).
  
• 
  Maceira, M., C. J. Ammon and R. B. Herrmann (2000). Faulting parameters of the September 25, 1998 Pymatuning, Pennsylvania earthquake, Seism. Res. Letters 71, No. 6, pp 742-752.
  
• 
  Akinci, A., L. Malagnini, R. B. Herrmann, N. A. Pino, L. Scognamiglio, and H. Eyidogan (2001). High-frequency ground motion in the Erzincan Region, Turkey: Inferences from small earthquakes, Bull. Seism. Soc. Am. 91, 1446-1455.
  
• 
  Herrmann, R. B. (2002). Comment on "Attenuative Dispersion of P waves in and near the New Madrid Seismic Zone" by L. Cong, J. Mejia, and B. J. Mitchell, Bull. Seism. Soc. Am. 92, 2049-2053.
  
• 
  Ortega, R., R. B. Herrmann and L. Quintinar (2002).High frequency earthquake ground motion scaling in central Mexico, (draft).
  
• 
  Malagnini, L., A. Akinci, R. B. Herrmann, N. A. Pino and L. Scognamiglio (2002). Characteristics of the ground motion in northeastern Italy, Bull. Seism. Soc. Am. 92, 2186-2204.
  
• 
  Mancilla, F., C. J. Ammon, R. B. Herrmann and J. Morales (2003). Faulting parameters of the 1999 Mula earthquake, southeastern Spain, Tectonophysics (in press).
  
• 
  Julia, J. C. J. Ammon and R. B. Herrmann (2003). Lithospheric structure of the Arabian Shield from the joint inversion of receiver functions and surface-wave group velocities, Tectonophysics, (submitted).
  

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