Multi-modal surface wave tomography to obtain S- and P-wave velocities applied to the recordings of UAV deployed sensors.

Geophysics ◽  
2021 ◽  
pp. 1-56
Author(s):  
Farbod Khosro Anjom ◽  
Thomas Jules Browaeys ◽  
Laura Valentina Socco
Keyword(s):  
Surface Wave ◽  
Wave Velocity ◽  
Poisson’S Ratio ◽  
P Wave ◽  
Poisson's Ratio ◽  
Surface Wave Tomography ◽  
Higher Modes ◽  
Wave Tomography ◽  
Irregular Geometry ◽  
The Impact

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.

P- and S-wave velocity models of shallow dry sand formations from surface wave multimodal inversion

Geophysics ◽  
2016 ◽  
Vol 81 (4) ◽  
pp. R197-R209 ◽  
Author(s):  
Paolo Bergamo ◽  
Laura Valentina Socco
Keyword(s):  
Surface Wave ◽  
Wave Velocity ◽  
Power Law ◽  
Poisson’S Ratio ◽  
Real Data ◽  
P Wave ◽  
Poisson's Ratio ◽  
S Wave ◽  
Data Set ◽  
Seismic Characterization

Surficial formations composed of loose, dry granular materials constitute a challenging target for seismic characterization. They exhibit a peculiar seismic behavior, characterized by a nonlinear seismic velocity gradient with depth that follows a power-law relationship, which is a function of the effective stress. The P- and S-wave velocity profiles are then characterized by a power-law trend, and they can be defined by two power-law exponents [Formula: see text] and two power-law coefficients [Formula: see text]. In case of depth-independent Poisson’s ratio, the P-wave velocity profile can be defined using the [Formula: see text] power-law parameters and Poisson’s ratio. Because body wave investigation techniques (e.g., P-wave tomography) may perform ineffectively on such materials because of high attenuation, we addressed the potential of surface-wave method for a reliable seismic characterization of shallow formations of dry, uncompacted granular materials. We took into account the dependence of seismic wave velocity on effective pressure and performed a multimodal inversion of surface-wave data, which allowed the [Formula: see text] and [Formula: see text] profiles to be retrieved. The method requires the selection of multimodal dispersion curve points referring to surface-wave frequency components traveling within the granular media formation and their inversion for the S-wave power-law parameters and Poisson’s ratio. We have tested our method on a synthetic dispersion curve and applied it to a real data set. In both cases, the surficial layer was made of loose dry sand. The test on the synthetic data set confirmed the reliability of the proposed procedure because the thickness and the [Formula: see text], [Formula: see text] profiles of the sand layer were correctly estimated. For the real data, the outcomes were validated by other geophysical measurements conducted at the same site and they were in agreement with similar studies regarding loose sand formations.

Seismic wave velocity investigation at The Geysers‐Clear Lake geothermal field, California

Geophysics ◽  
1982 ◽  
Vol 47 (5) ◽  
pp. 819-824 ◽  
Author(s):  
Harsh K. Gupta ◽  
Ronald W. Ward ◽  
Tzeu‐Lie Lin
Keyword(s):  
Wave Velocity ◽  
Poisson’S Ratio ◽  
Poisson Ratio ◽  
Volcanic Field ◽  
P Wave ◽  
Poisson's Ratio ◽  
Clear Lake ◽  
Seismic Wave Velocity ◽  
S Waves ◽  
The Geysers

Analysis of P‐ and S‐waves from shallow microearthquakes in the vicinity of The Geysers geothermal area, California, recorded by a dense, telemetered seismic array operated by the U.S. Geological Survey (USGS) shows that these phases are easily recognized and traced on record sections to distances of 80 km. Regional average velocities for the upper crust are estimated to be [Formula: see text] and [Formula: see text] for P‐ and S‐waves, respectively. Poisson’s ratio is estimated at 23 locations using Wadati diagrams and is found to vary from 0.13 to 0.32. In general, the Poisson’s ratio is found to be lower at the locations close to the steam production zones at The Geysers and Clear Lake volcanic field to the northeast. The low Poisson ratio corresponds to a decrease in P‐wave velocity in areas of high heat flow. The decrease may be caused by fracturing of the rock and saturation with gas or steam.

Advances in surface-wave tomography for near-surface applications

2021 ◽  
Vol 40 (8) ◽  
pp. 567-575
Author(s):  
Myrto Papadopoulou ◽  
Farbod Khosro Anjom ◽  
Mohammad Karim Karimpour ◽  
Valentina Laura Socco
Keyword(s):  
Surface Wave ◽  
Wave Velocity ◽  
P Wave ◽  
Seismic Exploration ◽  
S Wave ◽  
Data Set ◽  
Near Surface ◽  
Processing Times ◽  
Spatial Coverage ◽  
Wave Tomography

Surface-wave (SW) tomography is a technique that has been widely used in the field of seismology. It can provide higher resolution relative to the classical multichannel SW processing and inversion schemes that are usually adopted for near-surface applications. Nevertheless, the method is rarely used in this context, mainly due to the long processing times needed to pick the dispersion curves as well as the inability of the two-station processing to discriminate between higher SW modes. To make it efficient and to retrieve pseudo-2D/3D S-wave velocity (VS) and P-wave velocity (VP) models in a fast and convenient way, we develop a fully data-driven two-station dispersion curve estimation, which achieves dense spatial coverage without the involvement of an operator. To handle higher SW modes, we apply a dedicated time-windowing algorithm to isolate and pick the different modes. A multimodal tomographic inversion is applied to estimate a VS model. The VS model is then converted to a VP model with the Poisson's ratio estimated through the wavelength-depth method. We apply the method to a 2D seismic exploration data set acquired at a mining site, where strong lateral heterogeneity is expected, and to a 3D pilot data set, recorded with state-of-the-art acquisition technology. We compare the results with the ones retrieved from classical multichannel analysis.

Seismic Surface Wave Tomography on dense 3D active data

2020 ◽  
Author(s):  
Ilaria Barone ◽  
Emanuel Kästle ◽  
Claudio Strobbia ◽  
Giorgio Cassiani
Keyword(s):  
Surface Wave ◽  
Phase Velocity ◽  
Shear Wave ◽  
Wave Velocity ◽  
Shear Wave Velocity ◽  
Seismic Exploration ◽  
Surface Wave Tomography ◽  
Travel Times ◽  
Velocity Models ◽  
Wave Tomography

<p>Surface Wave Tomography (SWT) is a well-established technique in global seismology: signals from strong earthquakes or seismic ambient noise are used to retrieve 3D shear-wave velocity models, both at regional and global scale. This study aims at applying the same methodology to controlled source data, with specific focus on 3D acquisition geometries for seismic exploration. For a specific frequency, travel times between all source-receiver couples are derived from phase differences. However, higher modes and heterogeneous spatial sampling make phase extraction challenging. The processing workflow includes different steps as (1) filtering in f-k domain to isolate the fundamental mode from higher order modes, (2) phase unwrapping in two spatial dimensions, (3) zero-offset phase estimation and (4) travel times computation. Surface wave tomography is then applied to retrieve a 2D phase velocity map. This procedure is repeated for different frequencies. Finally, individual dispersion curves obtained by the superposition of phase velocity maps at different frequencies are depth inverted to retrieve a 3D shear wave velocity model.</p>

scholarly journals A single Rayleigh mode may exist with multiple values of phase-velocity at one frequency

2020 ◽  
Vol 222 (1) ◽  
pp. 582-594
Author(s):  
Thomas Forbriger ◽  
Lingli Gao ◽  
Peter Malischewsky ◽  
Matthias Ohrnberger ◽  
Yudi Pan
Keyword(s):  
Phase Velocity ◽  
Rayleigh Wave ◽  
Half Space ◽  
Wave Velocity ◽  
Poisson’S Ratio ◽  
P Wave ◽  
Poisson's Ratio ◽  
Wave Number ◽  
Homogeneous Layer ◽  
Rayleigh Mode

SUMMARY Other than commonly assumed in seismology, the phase velocity of Rayleigh waves is not necessarily a single-valued function of frequency. In fact, a single Rayleigh mode can exist with three different values of phase velocity at one frequency. We demonstrate this for the first higher mode on a realistic shallow seismic structure of a homogeneous layer of unconsolidated sediments on top of a half-space of solid rock (LOH). In the case of LOH a significant contrast to the half-space is required to produce the phenomenon. In a simpler structure of a homogeneous layer with fixed (rigid) bottom (LFB) the phenomenon exists for values of Poisson’s ratio between 0.19 and 0.5 and is most pronounced for P-wave velocity being three times S-wave velocity (Poisson’s ratio of 0.4375). A pavement-like structure (PAV) of two layers on top of a half-space produces the multivaluedness for the fundamental mode. Programs for the computation of synthetic dispersion curves are prone to trouble in such cases. Many of them use mode-follower algorithms which loose track of the dispersion curve and miss the multivalued section. We show results for well established programs. Their inability to properly handle these cases might be one reason why the phenomenon of multivaluedness went unnoticed in seismological Rayleigh wave research for so long. For the very same reason methods of dispersion analysis must fail if they imply wave number kl(ω) for the lth Rayleigh mode to be a single-valued function of frequency ω. This applies in particular to deconvolution methods like phase-matched filters. We demonstrate that a slant-stack analysis fails in the multivalued section, while a Fourier–Bessel transformation captures the complete Rayleigh-wave signal. Waves of finite bandwidth in the multivalued section propagate with positive group-velocity and negative phase-velocity. Their eigenfunctions appear conventional and contain no conspicuous feature.

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