Trans-Dimensional multimode surface wave inversion of DAS data at CaMI-FRS

Luping Qu, Jan Dettmer, Kristopher A. Innanen

Inversion of surface wave seismic data to aid in the characterization of the near-surface is a rich and well-explored field. However, several new areas of technology development, both algorithmic and acquisition-based, have the potential to lead to significant improvements in the accuracy and availability of near-surface models. To this end, in this study we apply a trans-dimensional surface wave dispersion inversion, which incorporates jointly using the multimodal phase velocity information of the Rayleigh wave, and we apply it to Distributed Acoustic Sensing (DAS) data acquired with a trenched fibreoptic cable. The joint use of multiple modes, combined in a stochastic sense, is explained in detail in this work. A thorough spectral analysis and error estimations on DAS data are required, and in processing the data we have found that a new mode separation method, called dispersion compensation, permitted clear picking of dispersion curves. Multimodal phase velocity dispersion curves are extracted from the densely sampled DAS data, and then used as input to a multimode phase velocity trans-dimensional inversion. We examine the subsurface phase velocity model recovery, and in particular show that better-resolved models result from the incorporation of the higher. Both synthetic and field testing are carried out, the latter involving DAS data acquired at the Containment and Monitoring Institute-Field Research Station as an offshoot of the CREWES 2018 mulit-offset multi-azimuth VSP experiment. Synthetic models appear to be consistent with our theoretical expectations, and results of real data furthermore appears to be in excellent agreement with known geology features. A better characterization of shallow area is revealed compared with other research results.