scholarly journals Full Waveform Inversion for Seismic Velocity and Anelastic Losses in Heterogeneous Structures

2007 ◽  
Vol 97 (6) ◽  
pp. 1990-2008 ◽  
Author(s):  
A. Askan ◽  
V. Akcelik ◽  
J. Bielak ◽  
O. Ghattas
Keyword(s):  
Seismic Velocity ◽  
Waveform Inversion ◽  
Full Waveform Inversion ◽  
Full Waveform ◽  
Heterogeneous Structures

Direct updating of rock physics properties using elastic full-waveform inversion

Geophysics ◽  
2021 ◽  
pp. 1-64
Author(s):  
Qi Hu ◽  
Scott Keating ◽  
Kristopher A. Innanen ◽  
Huaizhen Chen
Keyword(s):  
Reservoir Characterization ◽  
Seismic Velocity ◽  
Water Saturation ◽  
Quantitative Estimation ◽  
Waveform Inversion ◽  
Rock Physics ◽  
Full Waveform Inversion ◽  
Full Waveform ◽  
Physics Model ◽  
Rock Physics Model

Quantitative estimation of rock physics properties is an important part of reservoir characterization. Most current seismic workflows in this field are based on amplitude variation with offset. Building on recent work on high resolution multi-parameter inversion for reservoir characterization, we construct a rock-physics parameterized elastic full-waveform inversion (EFWI) scheme. Within a suitably-formed multi-parameter EFWI, in this case a 2D frequency-domain isotropic-elastic FWI with a truncated Gauss-Newton optimization, any rock physics model with a well-defined mapping between its parameters and seismic velocity/density can be examined. We select a three-parameter porosity, clay content, and water saturation (PCS) parameterization, and link them to elastic properties using three representative rock physics models: the Han empirical model, the Voigt-Reuss-Hill boundary model, and the Kuster and Toksöz inclusion model. Numerical examples suggest that conditioning issues, which make a sequential inversion (in which velocities and density are first determined through EFWI, followed by PCS parameters) unstable, are avoided in this direct approach. Significant variability in inversion fidelity is visible from one rock physics model to another. However, the response of the inversion to the range of possible numerical optimization and frequency selections, as well as acquisition geometries, varies widely. Water saturation tends to be the most difficult property to recover in all situations examined. This can be explained with radiation pattern analysis, where very low relative scattering amplitudes from saturation perturbations are observed. An investigation performed with a Bayesian approach illustrates that the introduction of prior information may increase the inversion sensitivity to water saturation

Central-difference time-lapse 4D seismic full waveform inversion

Geophysics ◽  
2020 ◽  
pp. 1-42
Author(s):  
Wei Zhou ◽  
David Lumley
Keyword(s):  
High Resolution ◽  
Seismic Velocity ◽  
Waveform Inversion ◽  
Computational Cost ◽  
Time Lapse ◽  
Full Waveform Inversion ◽  
Central Difference ◽  
Data Set ◽  
Velocity Inversion ◽  
Full Waveform

Repeated seismic surveys contain valuable information regarding time-lapse (4D) changes in the subsurface. Full waveform inversion (FWI) of seismic data can provide high-resolution estimates of 4D change. We propose a new time-domain 2D acoustic time-lapse FWI method based on the central-difference scheme with higher-order mathematical accuracy and reasonable computational cost. The method is rigorously tested on the SEAM 4D time-lapse model and OBN data set. High-resolution 4D velocity estimates are obtained, which show strong ~25% velocity increases in a 75 m-thick gas layer, as well as weaker (5%) changes due to geomechanical effects, the latter of which are poorly recovered by the conventional parallel 4D FWI method. We also perform the bootstrap 4D FWI method and the result is contaminated by strong artifacts in the underburden, whereas the proposed central-difference method has fewer underburden artifacts allowing more reliable interpretations. In this realistic case study, acoustic FWI erroneously overfits the elastic scattered waves, and cannot fit the strong elastic 4D coda waves at all. The results show that the proposed central-difference 4D FWI method within the acoustic approximation may be a practical solution for time-lapse seismic velocity inversion.

Near-surface characterization using traveltime and full-waveform inversion with vertical and horizontal component seismic data

2019 ◽  
Vol 7 (1) ◽  
pp. T141-T154 ◽  
Author(s):  
Md. Iftekhar Alam
Keyword(s):  
Surface Characterization ◽  
Seismic Waves ◽  
Seismic Velocity ◽  
Waveform Inversion ◽  
Horizontal Component ◽  
Full Waveform Inversion ◽  
Near Surface ◽  
Velocity Modeling ◽  
Full Waveform ◽  
Attenuation Models

Seismic imaging of the shallow subsurface (approximately 5 m) can be very challenging when reflections are absent and the data are dominated by ground roll. I analyzed the transmission coda to produce fine-scale, interpretable vertical and horizontal component seismic velocity ([Formula: see text] and [Formula: see text]) models using full-waveform inversion (FWI). Application of FWI is tested through imaging two buried targets. The first target is a pair of well-documented utility pipes with known diameters (0.8 m) and burial depths (approximately 1.5 m). The second target is a poorly documented former location of the pipe(s), which is now a backfilled void. Data are acquired along a 23 m 2D profile using a static array with single-component vertical and horizontal geophones. Our results indicate considerable velocity updates in the [Formula: see text] and [Formula: see text] models across the pipes and backfill. The pipes appear as negative velocity updates in the final inverted [Formula: see text] and [Formula: see text] models, whereas the backfilled area represents negative and positive velocity updates in the [Formula: see text] and [Formula: see text] models, respectively. Variations of the polarities in the inverted models ([Formula: see text] and [Formula: see text]) across the backfill can be indicative of the medium, which respond differently to the vertical and horizontal component seismic waves. The attenuation models show a general decreasing trend with increasing depth. Therefore, simultaneous applications of vertical ([Formula: see text]) and horizontal ([Formula: see text]) component seismic velocity modeling can be an effective tool to understand the subsurface medium in near-surface characterization.

SeisAndes: A High Resolution Crust and Upper Mantle Seismic Velocity Model beneath the Central Andes from 16° S to 30° S from Full Waveform Inversion

2020 ◽  
Author(s):  
Yajian Gao ◽  
Frederik Tilmann ◽  
Dirk-Philip van Herwaarden ◽  
Sölvi Thrastarson ◽  
Andreas Fichtner ◽  
...  
Keyword(s):  
Upper Mantle ◽  
Seismic Velocity ◽  
Waveform Inversion ◽  
Velocity Model ◽  
Central Andes ◽  
Full Waveform Inversion ◽  
Low Velocity ◽  
Nazca Plate ◽  
Middle Crust ◽  
Full Waveform

<div> <div> <div> <p>We present a new seismic tomography model from multi-scale full seismic waveform Inversion for the crustal and upper-mantle structure beneath the Central Andes (16°-30° S), where the oceanic Nazca plate is subducting beneath the South American continent. The Central Andes is characterized by significant along-strike changes in crustal shortening and thickening, arc migration, subduction erosion and catastrophic earthquakes (e.g. the 2014 Iquique M8.1 earthquake). A high resolution seismic velocity model would bring new insights into the geodynamics of this region, especially for the effects on the seismicity and volcanic arc from the serpentinization in the mantle wedge and dehydration effects from the subducting oceanic crust. </p> <p>Our model is derived from multi-scale full waveform inversion, including multiple time period stages (40-80 s, 30-80 s, 20-80 s, 15-80 s and 12-60 s). In order to avoid the risk of falling into the local minima of optimization, we started our inversion from the lowest frequency signals costing lower computational resources. Specifically, the forward and adjoint simulation based on a 3D model are accomplished with Salvus (Afanasiev et al., 2018), which is a suite of spectral-element method solver of the seismic wave equation. We invert waveforms from 117 events, which are carefully selected for good data coverage of the study region and depth range. We take advantage of the adjoint methodology coupled with conjugate gradients and L-BFGS optimization scheme to update the velocity model. We adopt a time-frequency phase shift as misfit functional with adjoint sources in the first four period-stages, and cross-correlation coefficient in the final stage after most of the phase shifts has been eliminated. The cross-correlation coefficient can capture distorted body wave seismograms, not only the phase shift. We also provide a resolution analysis through the computation of the point-spreading functions and validation dataset with a misfits evolution chart, demonstrating the robustness of our final model.</p> <p>Through full-waveform inversion, we provide a new higher resolution P and S wave velocity model from the middle crust to the upper mantle around 300 km depth. The subducted Nazca slab in the upper mantle beneath the Central Andes is fully imaged, with dip angle variations from the north to the south. We could also observe a strong low velocity band in the middle crust and uppermost mantle from 80 to 100 km beneath the volcanic arc, correlating with the volcano distributions and recent intermediate depth seismicity relocation results. An offset of this low velocity band between 20°-21°S is conspicuous, both in the middle crust and uppermost mantle, indicating a weak extent of the dehydration from 20°-21°S, resulting in the weak intermediate depth seismicity and absent volcanic activity in the same latitude range. We also imaged strong low velocity anomalies in the middle crust beneath the Altiplano-Puna Volcanic Complex and South Puna, giving strong evidence supporting the magmatic underpinnings and reservoirs. Meanwhile, low velocity beneath Puna tectonic units down to 100 km may represent the lithospheric detachment, resulting in the melting and upwelling fluids from the Nazca plate.</p> </div> </div> </div>

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