Multimodal surface-wave tomography to obtain S- and P-wave velocities applied to the recordings of unmanned aerial vehicle deployed sensors

Abstract

Exploration seismic surveys in hard-to-access areas such as foothills and forests are extremely challenging. The Multiphysics Exploration Technologies Integrated System (METIS) research project was initiated to design an exploration system, facilitating the acquisition in these areas by delivering the receivers from the sky using unmanned aerial vehicles. Air dropping of the sensors in vegetated areas results in an irregular geometry for the acquisition. This irregularity can limit the application of conventional surface wave methods. We have developed a surface wave workflow for estimating the S-wave velocity ( VS) and P-wave velocity ( VP) models and that supports the irregular geometry of the deployed sources and receivers. The method consists of a multimodal surface wave tomography (SWT) technique to compute the VS model and a data transform method (the wavelength/depth [W/D] method) to determine the Poisson’s ratio and VP model. We applied the method to the METIS’s first pilot records, which were acquired in the forest of Papua New Guinea. Application of SWT to the data resulted in the first 90 m of the VS model. The W/D method provided the Poisson’s ratio averaged over the area and the VP model between 10 and 70 m from the surface. The impact of the acquisition scale and layout on the resolution of the estimated model and the advantages of including the higher modes of surface waves in the tomographic inversion are assessed in detail. The presence of shots from diverse site locations significantly improves the resolution of the obtained model. Including the higher modes enhances the data coverage and increases the investigation depth.

Comparison of straight-ray and curved-ray surface wave tomography approaches in near-surface studies

“…Few researchers have used SWT for near-surface characterisation assuming straight-ray propagation of surface waves. Kugler et al (2007) characterised shallow water marine sediments using Scholte waves dispersion data, Picozzi et al (2009) applied SWT on highfrequency seismic noise data to construct a VS model up to 25 m in depth, Rector et al (2015) employed SWT to obtain a VS model in a mining site, Ikeda and Tsuji (2020) successfully applied SWT in laterally heterogeneous media, Papadopoulou (2021) showed the applicability of SWT in nearsurface characterisation in a mining site consisting of hard rocks and Khosro Anjom (2021) constructed a 3D VS model applying SWT on a large 3D dataset acquired for testing purposes in a mining area.…”

S- and P-wave velocity model estimation from seismic surface-waves

“…In the context of earthquake seismology, SWT is a well-stablished method for VS reconstruction of the crust and upper mantel (Wespestad et al, 2019;Bao et al, 2015;Boiero, 2009;Yao et al, 2008;Shapiro et al, 2005). Recently, a few authors showed the application of SWT for the near-surface characterization, using active (Da Col et al, 2019;Socco et al, 2014;Khosro Anjom et al, 2021) and passive data (Badal et al, 2013;Picozzi et al, 2009;Colombero et al, 2022).…”