A full-waveform inversion workflow for estimationing ambient seismic source distributions from Rayleigh-wave multicomponent crosscorrelations

2021 ◽  
Author(s):  
Zongbo Xu ◽  
T. Dylan Mikesell ◽  
Josefine Umlauft ◽  
Gabriel Gribler
Keyword(s):  
Rayleigh Wave ◽  
Waveform Inversion ◽  
Vertical Component ◽  
Seismic Source ◽  
Source Distribution ◽  
Full Waveform Inversion ◽  
Subsurface Structures ◽  
Full Waveform ◽  
Source Mechanisms ◽  
Co2 Degassing

<p>Estimation of ambient seismic source distributions (e.g. location and strength) is important for studies of seismic source mechanisms and subsurface structures. It is current state of the art to estimate the source distribution by applying full-waveform inversion (FWI) to seismic crosscorrelations. We previously theoretically demonstrated the advantage of Rayleigh-wave multicomponent crosscorrelations in the FWI estimation process. In this presentation, we utilize the crosscorrelations from real ambient seismic data acquired in Hartoušov, Czech Republic, where the seismic sources are CO2 degassing areas at Earth’s surface (i.e. fumaroles or mofettes).  We develop a complete workflow from the raw data to the FWI estimation. We demonstrate that the multicomponent crosscorrelations can better constrain the source distribution than vertical-component crosscorrelations in both elastic media and anelastic media, even when we use an elastic forward model in the inversion process. Our inversion results indicate a strong seismic source near strong CO2 gas flux areas.</p>

Full waveform inversion of marine reflection data in the plane‐wave domain

Geophysics ◽  
1997 ◽  
Vol 62 (2) ◽  
pp. 540-553 ◽  
Author(s):  
Susan E. Minkoff ◽  
William W. Symes
Keyword(s):  
Plane Wave ◽  
Least Squares ◽  
Waveform Inversion ◽  
Viscoelastic Model ◽  
Seismic Source ◽  
P Wave ◽  
Full Waveform Inversion ◽  
Data Set ◽  
Full Waveform ◽  
Output Least Squares

Full waveform inversion of a p‐τ marine data set from the Gulf of Mexico provides estimates of the long‐wavelength P‐wave background velocity, anisotropic seismic source, and three high‐frequency elastic parameter reflectivities that explain 70% of the total seismic data and 90% of the data in an interval around the gas sand target. The forward simulator is based on a plane‐wave viscoelastic model for P‐wave propagation and primary reflections in a layered earth. Differential semblance optimization, a variant of output least‐squares inversion, successfully estimates the nonlinear P‐wave background velocity and linear reflectivities. Once an accurate velocity is estimated, output least‐squares inversion reestimates the reflectivities and an anisotropic seismic source simultaneously. The viscoelastic model predicts the amplitude‐versus‐angle trend in the data more accurately than does an elastic model. Simultaneous inversion for reflectivities and source explains substantially more of the actual data than does inversion for reflectivities with fixed source from an air‐gun modeler. The best reflectivity estimates conform to widely accepted lithologic relationships and closely match the filtered well logs.

scholarly journals Elastic full-waveform inversion of vertical seismic profile data acquired with distributed acoustic sensors

Geophysics ◽  
2018 ◽  
Vol 83 (3) ◽  
pp. R273-R281 ◽  
Author(s):  
Anton Egorov ◽  
Julia Correa ◽  
Andrej Bóna ◽  
Roman Pevzner ◽  
Konstantin Tertyshnikov ◽  
...  
Keyword(s):  
Elastic Properties ◽  
Particle Velocity ◽  
Waveform Inversion ◽  
Vertical Component ◽  
Seismic Profile ◽  
Full Waveform Inversion ◽  
Vertical Seismic Profile ◽  
Data Set ◽  
Full Waveform ◽  
Vsp Data

Distributed acoustic sensing (DAS) is a rapidly developing technology particularly useful for the acquisition of vertical seismic profile (VSP) surveys. DAS data are increasingly used for seismic imaging, but not for estimating rock properties. We have developed a workflow for estimating elastic properties of the subsurface using full-waveform inversion (FWI) of DAS VSP data. Whereas conventional borehole geophones usually measure three components of particle velocity, DAS measures a single quantity, which is an approximation of the strain or strain rate along the fiber. Standard FWI algorithms are developed for particle velocity data, and hence their application to DAS data requires conversion of these data to particle velocity along the fiber. This conversion can be accomplished by a specially designed filter. Field measurements show that the conversion result is close to vertical particle velocity as measured by geophones. Elastic time-domain FWI of a synthetic multioffset VSP data set for a vertical well shows that the inversion of the vertical component alone is sufficient to recover elastic properties of the subsurface. Application of the proposed workflow to a multioffset DAS data set acquired at the CO2CRC Otway Project site in Victoria, Australia, reveals salient subhorizontal layering consistent with the known geology of the site. The inverted [Formula: see text] model at the well location matches the upscaled [Formula: see text] log with a correlation coefficient of 0.85.

Sign in / Sign up

Export Citation Format

Share Document