Detection of Systematic Errors in Travel-Time Data Using a Minimum 1D Model: Application to Costa Rica Seismic Tomography

Abstract

Many seismological studies depend on the accuracy of timing of seismological data. In seismic tomography, travel-time residuals defined as differences between the observed and calculated arrival times of seismic phases are minimized to constrain 3D velocity structure. Inconsistencies and large errors in data sets that result from incorrect station coordinates, errors in the timing acquisition system, errors in the merging procedure, inconsistency in the picking and phase misidentification can also generate travel-time residuals, and because of their systematic nature, these errors cannot be treated as random noise even by exploiting a large number of travel times. While the inverse problem is perfectly set up to deal with random noise, systematic errors lead to significant artifacts in the solution, but may not be detected by a posterior error assessment. For this reason, detecting and removing systematic travel-time errors from data sets before inversion is crucial for seismic tomography studies.We present a methodology based on the use of a minimum 1D model to detect and remove systematic errors in travel-time data by detailed analysis of station delays and observation residuals and apply it to a local earthquake data set from Costa Rica. The determination of the exact nature of detected inconsistencies needs further investigations in each individual case. If the cause of detected systematic errors cannot be determined beyond any doubt and the afflicted data may not be corrected, they must be deleted from the data set. To assess the extent of influence of systematic errors on hypocenter locations and their uncertainties, we present two examples showing the effects of station mislocation.

Local and regional minimum 1D models for earthquake location and data quality assessment in complex tectonic regions: application to Switzerland

“…The term minimum denotes the fact that a minimum 1D model leads to a minimum average RMS travel time residual for all earthquakes in the inversion. This makes the minimum 1D model a very suitable model to detect systematic errors in arrival data caused by phase misidentifications or by wrong station coordinates (Maurer et al 2010). Since all earthquakes are located with a similar accuracy a minimum 1D model presents also an ideal model for routine earthquake locations, where each earthquake should be located with a similar accuracy.…”

“…For these cases, the computation of a 1D velocity model is the only way to consistently obtain reliable hypocenter locations. Finally, 1D velocity models are the only choice for data quality assessment prior to a 3D tomography study (Husen et al 2003) and to detect systematic errors in arrival time data (Maurer et al 2010). Hence, there is still a need for reliable 1D velocity models in seismology, despite the fact that 3D velocity models are becoming increasingly popular.…”

“…The computation of a minimum 1D model explicitly solves the coupled hypocenter-velocity problem, and thus it also provides suitable velocity models for routine earthquake location, where a similar accuracy in earthquake location is required for each single earthquake (Kissling 1988). Moreover, a minimum 1D model can be used for data quality assessment prior to local earthquake tomography (Husen et al 2003) and to detect systematic errors in arrival time data (Maurer et al 2010). The latter is due to the fact that a minimum 1D model yields an average minimum data fit and that a 1D model, as opposed to a 3D model, may not absorb systematic errors in arrival time data as it is highly overdetermined.…”

1D Velocity Structure and Characteristics of Contemporary Local Seismicity around the Tehri Region, Garhwal Himalaya

“…1D velocity models have been traditionally adopted to compute hypocenter parameters at local, regional, and global scales because ray tracing is computationally easier and more efficient for 1D velocity models compared to 3D models. 1D velocity models also allow for assessing the data quality prior to a 3D tomography study (e.g., Husen et al, 2003) and detection of systematic errors in arrival-time data (Maurer et al, 2010). In view of these considerations, estimation of a reliable 1D velocity model of a region is a necessity, despite the fact that 3D velocity models are becoming increasingly popular.…”

A Review of Tomography System

“…Seismological tomography deals with the problem related to travel time residuals defined as differences between the observed and calculated arrivals time. [31] The huge data captured by seismic tomography contributes inconsistencies and errors in data results from incorrect coordinates, errors in timing acquisitions, and error in merging procedure. [31] The evolution in seismic tomography area has solved many problems that occurred based on this old method of tomography.…”