Accurate Back Azimuth Determination Using 6-DoF Measurements and Wavetype Fingerprinting

Recent advances in seismology underscore the potential of innovative instrumentation and data-driven methods to overcome long-standing challenges in source localization. Traditional techniques such as P-wave polarization or arrival time analysis often suffer from reduced precision in complex wavefields, where scattering and heterogeneities distort seismic signals. These limitations highlight the need for methods that leverage emerging technologies and provide robust uncertainty quantification.
In this study, we used a novel approach for determining the back azimuth of seismic sources using six degrees of freedom (6-DoF) ground motion measurements, enabling precise source localization from single-point data. We tested the method in a controlled experiment, tracking the migration of a vibroseis truck across 160 distinct locations. Each of the 480 recorded sweep signals, lasting 15 seconds and spanning a frequency range of 7–120 Hz, was analyzed to derive back azimuth values.
One key innovation in this approach is the use of a wavefield fingerprinting algorithm to isolate SV-type waves, significantly improving the precision of back azimuth estimates. This step addresses the inherent challenges posed by the sensitivity of rotational sensors primarily to S waves and the scattering effects that degrade localization accuracy as the source moves farther from the receiver. By isolating the SV wavefield, our method reduced deviations in back azimuth estimates to a maximum of 2.2 degrees, compared to deviations of up to 48.6 degrees when the entire wavefield was analyzed.
Our findings not only demonstrate the value of combining advanced monitoring instruments with wavefield-specific processing techniques but also highlight the importance of integrating uncertainty quantification into seismic analyses. This approach offers a pathway to more robust localization methods, especially for applications requiring high-resolution imaging or real-time seismic monitoring in complex tectonic environments.