Backazimuth Estimates Research Articles

Optimal backazimuth estimation for three-component recordings of regional seismic events

Augmenting travel-time data with backazimuth information can improve regional seismic event locations for which only a few recording stations are available. This study examines the achievable accuracy of backazimuths derived from 164 regional short-period P waves recorded at Regional Seismic Test Network (RSTN ) stations. The data represent 62 events with a good distribution of distance, azimuth, and signal-to-noise ratio (SNR) at each of four RSTN stations. Using Preliminary Determination of Epicenter locations to generate reference backazimuths, we examine the effects of computational method, signal window length, frequency content, and SNR on RSTN backazimuth estimates. The variety of geologic environments at the receivers also allows assessment of the effect of receiver structure on backazimuth estimation. Our results indicate that regional three-component recordings can produce useful backazimuths; more than 75 per cent of the records yield backazimuths within 20° of the correct value when reasonable parameters are used. The accuracy of the calculated backazimuths does vary with the receiver, however. RSTN stations in New York and Ontario, located in Precambrian terranes, produce very accurate backazimuths for SNRs greater than 5 dB. At the South Dakota and Tennessee stations, located in sedimentary rocks, complicated receiver structure is the controlling factor in backazimuth estimation. Propagational complexities at the South Dakota site preclude recovery of reasonable backazimuth values; poor statistics are obtained for all parameter combinations. At the Tennessee site, backazimuth accuracy depends strongly on the computational method used. In general, the choice of frequency band is important and varies by stations, while the length of the signal window is less critical. If the problematic South Dakota records are excluded, we achieve an rms backazimuth error of about 6° for recordings with SNR above 10 dB. While a single optimized choice of parameters produces good results for the 164-record data set, a further 5 to 10 per cent improvement can be achieved if the parameters are customized on a station-by-station basis.

Azimuth estimation capabilities of the NORESS regional seismic array

Abstract We have investigated the regional Pn backazimuth estimation capabilities of the NORESS seismic array as a function of element spacing, frequency band, and time window to determine which parameters are optimal for reducing azimuth errors. We used a broadband frequency-wavenumber estimator to calculate backazimuths from the Pn arrival for each of 274 regional events recorded at NORESS for 126 parameter combinations. The large data base provides a wide range of signal-to-noise ratio (SNR) (0 to 70 dB), distance (up to 10.5°), and azimuth characteristics, and includes identified earthquakes and explosions as well as “unknown” sources. Most of the errors in backazimuth are less than 20° when appropriate parameters are used, and mean backazimuth errors are close to zero. The best results are obtained using a 13-element array configuration that has a 1.4 km aperture and a maximum station spacing of about 600 m. With the 13-element configuration and the data filtered to include frequencies between 3 and 10 Hz, the mean errors for the 274 event data set are less than 1.4°, and standard deviations are as small as ± 11.1°. The entire array also produces good results for 3 to 10 Hz, and a 9-element configuration (two inner rings) performs well at high frequencies. The five-element B-ring (600 m aperture) appears to be important in obtaining good backazimuth estimates for regional Pn waves. Of the frequency bands considered in this study, the 3 to 6 Hz, 4 to 8 Hz, and 5 to 10 Hz bands yield the most reliable backazimuth estimates, even better than an “optimal” band that calculates the azimuth in the fixed frequency band that has the largest average SNR. The time-window length has little effect on the backazimuth estimates. Other factors investigated include SNR, source region, and phase type. We found that event backazimuth accuracy degrades if the SNR of a beamed Pn signal is less than 5 dB in the frequency band of interest. Conversely, the backazimuth estimation statistics improve if only events with 5 dB of SNR are included in the event set. These data sets yield near-zero mean errors and smaller standard deviations than the entire data set. For specific source regions, standard deviations are as low as 2° for some parameter combinations, but there can also be large biases in the backazimuth estimates. Events farther than 500 km from NORESS tend to have larger azimuth errors than the closer events, but combinations of small aperture configurations and middle (3 to 10 Hz) frequency bands work well for events over the entire distance range of 40 to 1200 km. The Pn arrival and RONAPP azimuths calculated from the Lg phase have similar accuracy statistics for a 220 event common data base, implying that the two phases work equally well for regional event backazimuth estimation. In fact, averaging of the Lg and Pn estimates provides the most accurate backazimuths relative to PDE reference information.

Correlation of waveforms from closely spaced regional events

Abstract We studied the similarity of waveforms recorded at the high frequency element of the NORESS array from 137 events (ML = 0.8 to 2.1) in or near the mining districts of Central Sweden. Waveform correlations based on the covariance matrices of three component recordings and on maximum amplitudes were calculated from traces filtered between 2.5 and 4.0 Hz, in which band the signal-to-noise ratio consistently peaked for the waveforms. A cutoff value for the correlations to separate waveforms with poor and good correlation values could be defined from the statistical uncertainty in back azimuth estimates of NORESS. More than 80 per cent of the events could be grouped with hierarchical clustering into one large group of 98 events and five smaller groups. The NORESS epicenters of the events in the large group were scattered over an area of 20 × 75 km. An exponential decay of the waveform correlation with event separation (d in km) could be fitted to the data of this group (exp(−d/8), taking NORESS epicenter uncertainties into account. A procedure for location of close events based on correlation values is defined. When applied to the large event group it limits the event epicenters to be within an area of about 4 km. For one small event group, high correlation values were obtained above 15 Hz. These frequencies are significantly higher than those reported in other studies, and the so called quarter wavelength argument constrains the event epicenters to within 0.1 km.

Location performance of a sparse regional network

A key element in successful seismic verification of a nuclear test ban treaty is the capability of a sparse network of seismic stations to accurately locate regional events. We have investigated the regional location accuracy of the Regional Seismic Test Network (RSTN), a five‐element, three‐component network in eastern North America, using 62 events varying in size from magnitude 3.0 to 5.1. Applying an algorithm which allows inclusion of back‐azimuth estimates as well as travel times, we determined a median location error of 23 km for the data set relative to the PDE locations. Considering the large station spacing (1500 km) and few data used in the locations (2 to 4 stations), the RSTN location accuracy is remarkably good; the results imply that a widely spaced network of single, three‐component stations could reliably locate regional seismic events.

Summary of corrections needed for accurate backazimuth estimation using Regional Seismic Test Network data

Brief Report| October 01, 1988 Summary of corrections needed for accurate backazimuth estimation using Regional Seismic Test Network data K. K. Nakanishi; K. K. Nakanishi Earth Sciences Department Lawrence Livermore National LaboratoryLivermore, California 94550 Search for other works by this author on: GSW Google Scholar S. P. Jarpe S. P. Jarpe Earth Sciences Department Lawrence Livermore National LaboratoryLivermore, California 94550 Search for other works by this author on: GSW Google Scholar Author and Article Information K. K. Nakanishi Earth Sciences Department Lawrence Livermore National LaboratoryLivermore, California 94550 S. P. Jarpe Earth Sciences Department Lawrence Livermore National LaboratoryLivermore, California 94550 Publisher: Seismological Society of America Received: 28 Apr 1988 First Online: 03 Mar 2017 Online Issn: 1943-3573 Print Issn: 0037-1106 Copyright © 1988, by the Seismological Society of America Bulletin of the Seismological Society of America (1988) 78 (5): 1830–1833. https://doi.org/10.1785/BSSA0780051830 Article history Received: 28 Apr 1988 First Online: 03 Mar 2017 Cite View This Citation Add to Citation Manager Share Icon Share Facebook Twitter LinkedIn MailTo Tools Icon Tools Get Permissions Search Site Citation K. K. Nakanishi, S. P. Jarpe; Summary of corrections needed for accurate backazimuth estimation using Regional Seismic Test Network data. Bulletin of the Seismological Society of America 1988;; 78 (5): 1830–1833. doi: https://doi.org/10.1785/BSSA0780051830 Download citation file: Ris (Zotero) Refmanager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentBy SocietyBulletin of the Seismological Society of America Search Advanced Search This content is PDF only. Please click on the PDF icon to access. First Page Preview Close Modal You do not have access to this content, please speak to your institutional administrator if you feel you should have access.

Locating events with a sparse network of regional arrays

Abstract An automated procedure for locating regional seismic events with a network including arrays and single element seismometers is described. The method incorporates backazimuth estimates, arrival-time data, and associated uncertainties into a least-squares-inverse location algorithm. The formulation is essentially that of Jordan and Sverdrup extended to incorporate azimuth data. This technique allows the use of both a priori and a posteriori information about data uncertainties to compute confidence ellipsoids for location estimates. This is important for obtaining realistic confidence ellipsoids for solutions based on few data. It also permits a refinement of the confidence ellipsoid calculations as experience accumulates for events in a particular area. Small arrays like NORESS in Norway provide accurate estimates for the backazimuth of regional phases. These azimuth data provide a strong constraint on the location of events detected by a small number of stations. The strength of the constraint depends on the geometry, and in some situations azimuth data are as important as arrival-time data. Synthetic examples illustrating this are given for a network including two arrays. Actual data from the NORESS array in southern Norway and the FINESA array near Helsinki, Finland, are presented to demonstrate the use of the location technique. Most of the events studied are mine blasts for which there are highly accurate, independent locations. Comparing one-array and two-array locations and their confidence ellipses with these independent locations provides a preliminary validation of our estimates of the (signal-dependent) a priori arrival-time and azimuth variances, and demonstrates the effectiveness of our location procedure for a sparse network of regional arrays.