The DOE Model for Improving Seismic Event Locations Using Travel Time Corrections: Description and Demonstration
The U.S. National Laboratories, under the auspices of the Department of Energy, have been tasked with improv- ing the capability of the United States National Data Center (USNDC) to monitor compliance with the Comprehen- sive Test Ban Trea~ (CTBT). One of the most important services which the USNDC must provide is to locate suspicious events, preferably as accurately as possible to help identify their origin and to insure the success of on-site inspections if they are deemed necessary. The seismic location algorithm used by the USNDC has the capability to generate accurate locations by applying geographically dependent travel time corrections, but to date, none of the means, proposed for generating and representing these corrections has proven to be entirely satisfactory. In this presentation, we detail the complete DOE model for how regional calibration travel time information gathered by the National Labs will be used to improve event locations and provide more realistic location error esti- mates. We begin with residual data and error estimates from ground truth events. Our model consists of three parts: data processing, data storage, and data retrieval. The former two are effectively one-time processes, executed in advance before the system is made operational. The last step is required every time an accurate event location is needed. Data processing involves applying non-stationary Bayesian kriging to the residwd data to densifi them, and iterating to find the optimal tessellation representation for the fast interpolation in the data retrieval task. Both the kriging and the iterative re-tessellation are slow, computationally-expensive processes but this is acceptable because they are performed off-line, before any events are to be located. In the data storage task, the densified data set is stored in a database and spatially indexed. Spatial indexing improves the access efficiency of the geographically-ori- ented data requests associated with event location. Finally, in the Data Retrieval phase, when an accurate location is needed, the densified data is retrieved and a quick interpolation is performed using natural neighbor interpolation with a gradient slope modification to guarantee continuous derivatives. To test our model, we use the residuals from a large set of synthetic events (441) that were created to have travel times consistent with the IASP91 radial base model plus perturbations of up to 2 seconds taken from spherical har- monic surfaces with randomly generated coefficients. Relocating these events using 3 stations with poor azimuthal coverage and IASP91 travel times alone yields dislocations of up 278 km with a mean value of 58 km. Using our model to apply travel time corrections we reduce the hugest dislocation to 151 km and the mean value to 13 km. Fur- ther, the error ellipses generated now accurately reflect the uncertainly associated with the composite model (base model + corrections), and as a result are small for events occurring near ground truth event points and large for events occurring where no calibration data is available.
- Research Organization:
- Sandia National Laboratories (SNL), Albuquerque, NM, and Livermore, CA (United States)
- Sponsoring Organization:
- USDOE
- DOE Contract Number:
- AC04-94AL85000
- OSTI ID:
- 1055
- Report Number(s):
- SAND98-2347C; ON: DE00001055
- Resource Relation:
- Conference: 20th Annual Seismic Research Symposium for Monitoring A Comprehensive Test Ban Treaty; Santa Fe, NM; 09/21-23/1998
- Country of Publication:
- United States
- Language:
- English
Similar Records
LLNL's 3-D A Priori Model Constraints and Uncertainties for Improving Seismic Location
Integrating diverse calibration products to improve seismic location