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Distributed acoustic sensing (DAS) is a relatively new technology forrecording stress wave propagation, with promising applications in bothengineering and geophysics. DAS's ability to simultaneously collect highspatial resolution data over long arrays suggests that it is especially wellsuited for near-surface imaging applications such as 2D MASW (multi-channelanalysis of surface waves). 2D MASW aims to produce a pseudo-2D cross-sectionof shear-wave velocity (Vs) for the purpose of identifying and characterizingsubsurface layering and anomalies. These cross-sections are produced byinterpolating numerous 1D Vs profiles extracted from overlapping sub-arraysalong the testing alignment. When using traditional seismic equipment, thesesub-arrays are typically collected in a roll-along configuration, where theequipment is moved along the alignment at some predetermined sub-arrayinterval. DAS does not have the same limitations, as data from all shotlocations are simultaneously recorded along the entire length of the DAS array.This alleviates the requirements to pre-determine sub-array length and intervalduring the acquisition stage and allows for multiple geometries to beinvestigated during the processing stage. The present study utilizes DAS datato evaluate the effects of sub-array length on 2D MASW results at awell-characterized field test site. We organize the DAS waveforms into multiplesets of overlapping MASW sub-arrays of differing lengths, allowing for directcomparison of the derived results at the same site. We show that the length ofthe individual MASW sub-arrays has a significant effect on the resolution ofthe resulting cross-sections as well as the resolved location of largeimpedance contrasts at our study site and evaluate those locations compared toinvasive testing.

DAS for 2D MASW Imaging: A Case Study on the Benefits of Flexible Sub-Array Processing