Near Surface Data Constrained Velocity Model Tomographic Inversion Technique

2013 ◽  
Author(s):  
Diao Rui ◽  
Zhao Shengtian
Keyword(s):  
Velocity Model ◽  
Tomographic Inversion ◽  
Near Surface ◽  
Inversion Technique ◽  
Surface Data

Model–parameterization scaling for improving accuracy of seismic tomography in reconstructing near–surface velocity model

2020 ◽  
Author(s):  
Gleb S. Chernyshov ◽  
◽  
Anton A. Duchkov ◽  
Aleksander A. Nikitin ◽  
Ivan Yu. Kulakov ◽  
...  
Keyword(s):  
Model Building ◽  
Regularization Parameter ◽  
Velocity Model ◽  
Surface Velocity ◽  
Surface Model ◽  
Tomographic Inversion ◽  
Near Surface ◽  
Model Parameterization ◽  
Regularization Parameters ◽  
Improving Accuracy

The problem of tomographic inversion is non–unique and requires regularization to solve it in a stable manner. It is highly non–trivial to choose between various regularization approaches or tune the regularization parameters themselves. We study the influence of one particular regularization parameter on the resolution and accuracy the tomographic inversion for the near–surface model building. We propose another regularization parameter, which allows to increase the accuracy of model building.

Tomographic inversion technique based on near-surface investigation results

2016 ◽  
Author(s):  
Rui Diao ◽  
Guo-Chen Wu ◽  
Xin-Min Shang ◽  
Yong-Jun Rui ◽  
Qing-Hui Cui
Keyword(s):  
Surface Investigation ◽  
Tomographic Inversion ◽  
Near Surface ◽  
Inversion Technique

Imaging permafrost velocity structure using high resolution 3D seismic tomography

Geophysics ◽  
2011 ◽  
Vol 76 (5) ◽  
pp. B187-B198 ◽  
Author(s):  
Kumar Ramachandran ◽  
Gilles Bellefleur ◽  
Tom Brent ◽  
Michael Riedel ◽  
Scott Dallimore
Keyword(s):  
High Resolution ◽  
Velocity Structure ◽  
Velocity Model ◽  
Water Bodies ◽  
Unfrozen Water ◽  
3D Seismic ◽  
Tomographic Inversion ◽  
Near Surface ◽  
First Arrival ◽  
Velocity Variations

A 3D seismic survey (Mallik 3D), covering [Formula: see text] in the Mackenzie Delta area of Canada’s north, was conducted by industry in 2002. Numerous lakes and marine inundation create a complex near-surface structure in the permafrost terrain. Much of the near subsurface remains frozen but significant melt zones exist particularly from perennially unfrozen water bodies. This results in an irregular distribution of permafrost ice creating a complex pattern of low and high frequency near-surface velocity variations which induce significant traveltime distortions in surface seismic data. A high resolution 3D traveltime tomography study was employed to map the permafrost velocity structure utilizing first-arrival traveltimes picked from 3D seismic shot records. Approximately 900,000 traveltime picks from 3167 shots were used in the inversion. Tomographic inversion of the first-arrival traveltimes resulted in a smooth velocity model for the upper 200 m of the subsurface. Ray coverage in the model is excellent down to 200 m providing effective control for estimating velocities through tomographic inversion. Resolution tests conducted through horizontal and vertical checkerboard tests confirm the robustness of the velocity model in detailing small scale velocity variations. Well velocities were used to validate tomographic velocities. The tomographic velocities do not show systematic correlation with well velocities. The velocity model clearly images the permafrost velocity structure in lateral and vertical directions. It is inferred from the velocity model that the permafrost structure in the near subsurface is discontinuous. Extensions of surface water bodies in depth, characterized by low P-wave velocities, are well imaged by the velocity model. Deep lakes with unfrozen water, inferred from the tomographic velocity model, correlate with areas of strong amplitude blanking and frequency attenuation observed in processed reflection seismic stack sections.

scholarly journals First arrival Q tomography based on an adjoint-state method

2020 ◽  
Author(s):  
Xinwei Huang ◽  
Zhenbo Guo ◽  
Huawei Zhou ◽  
Yubo Yue
Keyword(s):  
Time Domain ◽  
Spectral Ratio ◽  
Velocity Model ◽  
Similarity Coefficients ◽  
Tomographic Inversion ◽  
Near Surface ◽  
Adjoint State ◽  
Q Tomography ◽  
First Arrival ◽  
The Time Domain

Abstract Under the assumption of invariant ray path in a weakly dissipative (high quality factor Q) subsurface medium, a tomographic inversion approach composed of two cascading applications of first arrival traveltime and Q tomography is proposed for compensating amplitude loss caused by near-surface anomalies, such as unconsolidated soils or the overburden gas cloud. To improve the computational efficiency, these two related tomography methods were adopted with an adjoint-state technique. First, arrival traveltime tomography will be performed to provide an inverted velocity model as one of the inputs for the following first arrival Q tomography. Then, the synthetic first break generated by the inverted velocity model will be used as a stable guidance of accessing the scopes of first arrival waveforms in the time domain where the potential attenuated time information is contained. The attenuated time will be estimated through a logarithmic spectral ratio linear regression corresponding to frequency-dependent propagation responses of different wave types. All these estimated attenuated times will be applied with reference signals to generate synthetic attenuated seismic data in the time domain, and their discrepancies with real data will be evaluated using similarity coefficients. The ones with larger values will be selected as optimal attenuated time inputs for the following Q tomographic inversion. Examples of both synthetic and field data reveal the feasibility and potential of this method.

Shear and compressive wave data acquisition using multicomponent vibrating source and landstreamer

2021 ◽  
Author(s):  
Andre Pugin ◽  
Barbara Dietiker ◽  
Kevin Brewer ◽  
Timothy Cartwright
Keyword(s):  
Leading Edge ◽  
Data Sets ◽  
Compressive Wave ◽  
Near Surface ◽  
Source Type ◽  
Receiver Array ◽  
Surface Data ◽  
Source Orientation ◽  
Refracted Waves ◽  
Wave Modes

<p>In the vicinity of Ottawa, Ontario, Canada, we have recorded many multicomponent seismic data sets using an in-house multicom­ponent vibrator source named Microvibe and a landstreamer receiver array with 48 3-C 28-Hz geophones at 0.75-m intervals. The receiver spread length was 35.25 m, and the near-offset was 1.50 m. We used one, two or three source and three receiver orientations — vertical (V), inline-horizontal (H1), and transverse-horizontal (H2). We identified several reflection wave modes in the field records — PP, PS, SP, and SS, in addition to refracted waves, and Rayleigh-mode and Love-mode surface waves. We computed the semblance spectra of the selected shot records and ascertained the wave modes based on the semblance peaks. We then performed CMP stacking of each of the 9-C data sets using the PP and SS stacking velocities to compute PP and SS reflection profiles.</p><p>Despite the fact that any source type can generate any combination of wave modes — PP, PS, SP, and SS, partitioning of the source energy depends on the source orientation and VP/VS ratio. Our examples demonstrate that the most prominent PP reflection energy is recorded by the VV source-receiver orientation, whereas the most prominent SS reflection energy is recorded by the H2H2 source-receiver orientation with possibility to obtain decent shear wave near surface data in all other vibrating and receiving directions.</p><p>Pugin, Andre and Yilmaz, Öz, 2019. Optimum source-receiver orientations to capture PP, PS, SP, and SS reflected wave modes. The Leading Edge, vol. 38/1, p. 45-52. https://doi.org/10.1190/tle38010045.1</p>

scholarly journals Seismic Risk Assessment of Chania, Greece, Using an Integrated Computational Approach

2021 ◽  
Vol 11 (23) ◽  
pp. 11249
Author(s):  
Ioannis Koutsoupakis ◽  
Yiannis Tsompanakis ◽  
Pantelis Soupios ◽  
Panagiotis Kirmizakis ◽  
SanLinn Kaka ◽  
...  
Keyword(s):  
Seismic Risk ◽  
Seismic Vulnerability ◽  
Risk Model ◽  
Soil Classification ◽  
Velocity Model ◽  
Surface Shear ◽  
Near Surface ◽  
Effective Decision Making ◽  
Ground Motion Scenarios ◽  
The City

This study develops a comprehensive seismic risk model for the city of Chania, in Greece, which is located ina highly seismic-prone region due to the occurrenceof moderate to large earthquakes because of the nearby major subduction zone between African and Eurasian tectonic plates. The main aim is to reduce the seismic risk for the study area by incorporating the spatial distribution of the near-surface shear wave velocity model and the soil classification, along with all possible seismic sources, taking into account historical events. The study incorporates and correlates various ground motion scenarios and geological fault zones as well as information on existing buildings to develop a seismic risk model using QuakeIST software, and then the seismic hazard and a realistic prediction of resulting future adverse effects are assessed. The developed model can assist the municipal authorities of Chania to be prepared for potential seismic events, as well as city planners and decisionmakers, who can use the model as an effective decision-making tool to identify the seismic vulnerability of the city buildings and infrastructure. Thus, this study enables the implementation of an appropriate and viable earthquake-related hazards strategy to mitigate damage and losses in future earthquakes.

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