Abstract

In the last two decades seismic interferometry has become an important technique in a seismologist’s toolbox. Of the various applications of seismic interferometry, ambient noise tomography is perhaps the best known. The main reason being that it uses the pervasive ambient seismic field generated by natural processes. On the other hand, the anthropogenic contribution to the ambient seismic field has received less attention, although examples that use noise from traffic, industrial sites and even buildings are present in the literature.

In this presentation, I’ll discuss results from unpublished traffic noise datasets and explore previously published datasets. The focus of our analyses is the extraction of body waves, and more specifically reflections generated by subsurface targets. These datasets include highway and train traffic noise recordings within different environments. Different approaches are tested, such as cross-coherence interferometry and compared with standard cross-correlation results to determine the best method for each dataset. In addition, different binning and stacking methods are tested to determine which produces the most coherent body wave retrievals.

The case studies included in the presentation are fairly varied, for example we will look at a fairly recent deployment in South Africa which recorded train traffic above a railroad tunnel, another example which focused solely in vehicle traffic in the Northeastern US, and a couple of examples focusing in train traffic in New Mexico.