2-D velocity inversion/imaging of large offset seismic data via the tau‐p domain

Geophysics ◽  
1993 ◽  
Vol 58 (7) ◽  
pp. 1002-1016 ◽  
Author(s):  
Edmund C. Reiter ◽  
G. Michael Purdy ◽  
M. Nafi Toksöz
Keyword(s):  
Velocity Field ◽  
Three Dimensional ◽  
Synthetic Data ◽  
Velocity Model ◽  
Intermediate Step ◽  
Ocean Bottom ◽  
Velocity Inversion ◽  
Best Fitting ◽  
Ray Parameter ◽  
Refraction Data

We describe a method for determining a two‐dimensional (2-D) velocity field from refraction data that has been decomposed into some function of slowness. The most common decomposition, intercept time‐slowness or [Formula: see text], is used as an intermediate step in an iterative wave field continuation procedure previously applied to one‐dimensional (1-D) velocity inversions. We extend the 1-D approach to 2-D by performing the downward continuation along numerically computed raypaths. This allows a correction to be made for the change in ray parameter induced by 2-D velocity fields. A best fitting velocity model is chosen as a surface defined by critically reflected and refracted energy that has been downward continued into a three dimensional (3-D) space of velocity, offset, and depth. Synthetic data are used to demonstrate how this approach can compensate for the effects of known lateral inhomogeneities while determining an underlying 1-D velocity field. We also use synthetic data to show how multiple refraction lines may be used to determine a general 2-D velocity model. Large offset field data collected with an Ocean Bottom Hydrophone are used to illustrate this technique in an area of significant lateral heterogeneity caused by a sloping seafloor.

scholarly journals A reflection-based efficient wavefield inversion

Geophysics ◽  
2021 ◽  
pp. 1-53
Author(s):  
Chao Song ◽  
Tariq Alkhalifah
Keyword(s):  
High Resolution ◽  
Initial Velocity ◽  
Waveform Inversion ◽  
Synthetic Data ◽  
Velocity Model ◽  
Background Model ◽  
Ocean Bottom ◽  
Velocity Inversion ◽  
Velocity Models ◽  
Wavefield Inversion

Full-waveform inversion (FWI) is popularly used to obtain a high-resolution subsurface velocity model. However, it requires either a good initial velocity model or low-frequency data to mitigate the cycle-skipping issue. Reflection-waveform inversion (RWI) uses a migration/demigration process to retrieve a background model that can be used as a good initial velocity in FWI. The drawback of the conventional RWI is that it requires the use of a least-squares migration, which is often computationally expensive, and is still prone to cycle skipping at far offsets. To improve the computational efficiency and overcome the cycle skipping in the original RWI, we incorporate it into a recently introduced method called efficient wavefield inversion (EWI) by inverting for the Born scattered wavefield instead of the wavefield itself. In this case, we use perturbation-related secondary sources in the modified source function. Unlike conventional RWI, the perturbations are calculated naturally as part of the calculation of the scattered wavefield in an efficient way. As the sources in the reflection-based EWI (REWI) are located in the subsurface, we are able to update the background model along the reflection wave path. In the background velocity inversion, we calculate the background perturbation by a deconvolution process at each frequency. After obtaining the REWI inverted velocity model, a sequential FWI or EWI is needed to obtain a high-resolution model. We demonstrate the validity of the proposed approach using synthetic data generated from a section of the Sigsbee2A model. To further demonstrate the effectiveness of the proposed approach, we test it on an ocean bottom cable (OBC) dataset from the North Sea. We find that the proposed methodology leads to improved velocity models as evidenced by flatter angle gathers.

Imaging the Deep Galicia margin using three-dimensional full waveform inversion

2020 ◽  
Author(s):  
Bhargav Boddupalli ◽  
Tim Minshull ◽  
Joanna Morgan ◽  
Gaye Bayrakci
Keyword(s):  
High Resolution ◽  
Travel Time ◽  
Waveform Inversion ◽  
Three Dimensional ◽  
Velocity Model ◽  
Normal Faults ◽  
Full Waveform Inversion ◽  
Ocean Bottom ◽  
Time Model ◽  
Full Waveform

<p>Imaging of hyperextended zone and exhumed continental mantle rocks can improve our understanding of the tectonics of the final stages of rifting. In the Deep Galicia margin, the upper and lower crust are coupled allowing the normal faults to cut through the brittle crust and penetrate to the mantle leading to serpentinization of the mantle. Localized extensional forces caused extreme thinning and elongation of crystalline continental crust causing the continental blocks to slip over a lithospheric-scale detachment fault called the S-reflector.  </p><p>A high-resolution velocity model obtained using seismic full waveform inversion gives us deeper insights into the rifting process. In this study, we present results from three dimensional acoustic full waveform inversion performed using wide-angle seismic data acquired in the deep water environments of the Deep Galicia margin using ocean bottom seismometers. We performed full waveform inversion in the time domain, starting with a velocity model obtained using travel-time tomography, of dimensions 78.5 km x 22.1 km and depth 12 km. The high-resolution modelling shows short-wavelength variations in the velocity, adding details to the travel-time model. We superimposed our final model, converted to two-way time, on pre-stack time-migrated three-dimensional reflection data from the same survey. Compared to the starting model, our model shows improved alignment of the velocity variations along the steeply dipping normal faults and a sharp velocity contrast across the S-reflector. We validated our result using checkerboard tests, by tracking changes in phases of the first arrivals during the inversion and by comparing the observed and the synthetic waveforms. We observe a clear evidence for preferential serpentinization (45 %) of the mantle with lower velocities in the mantle correlating with the fault intersections with the S-reflector.</p>

Computational aspects of finite-frequency traveltime inversion kernels

Geophysics ◽  
2020 ◽  
pp. 1-135
Author(s):  
Houzhu (James) Zhang ◽  
Hong Liang ◽  
Hyoungsu Baek ◽  
Yang Zhao
Keyword(s):  
Model Building ◽  
Synthetic Data ◽  
Velocity Model ◽  
Ocean Bottom ◽  
Finite Frequency ◽  
Simple Formulation ◽  
Traveltime Inversion ◽  
Distribution Density Function ◽  
Isotropic Media ◽  
Fresnel Zones

Finite-frequency traveltime inversion offers higher accuracy for velocity model building than ray-based traveltime inversion. The adjoint force is the key to computation of inversion kernels. Starting at the definition of inversion kernels for the acoustic wave equation, we derive the explicit formula for the spectral distribution density function used in the adjoint force computation. Two formulations are provided for the computation of adjoint forces for receiver-side extrapolation, frequency-domain representation and time-domain representation. The accuracy of finite-frequency traveltime inversion kernels is benchmarked with the analytical solutions for homogeneous isotropic media. We use wavefront construction to compute the first Fresnel zones for kernel conditioning. Based on dynamic ray tracing, we design a processing procedure guided by synthetic data tests to extract the desired events for wavefield backward extrapolation from the data. Unlike ray-based velocity tomography, finite-frequency inversion can resolve the velocity structures comparable with the size of Fresnel zones as we demonstrate on a marine salt model using ocean bottom node acquisition geometry. Despite the fact that the inversion kernels are based on Born approximation, velocities with errors up to 20% can be well resolved. For practical purposes, a simple formulation is given for the determination of the shot spacing. The proposed workflow for finite-frequency inversion is efficient and converges only in very few iterations.

Three-dimensional seismic-while-drilling (SWD) migration in the angular frequency domain

Geophysics ◽  
2005 ◽  
Vol 70 (6) ◽  
pp. S111-S120
Author(s):  
Fabio Rocca ◽  
Massimiliano Vassallo ◽  
Giancarlo Bernasconi
Keyword(s):  
Frequency Domain ◽  
Three Dimensional ◽  
Synthetic Data ◽  
Vertical Axis ◽  
Velocity Model ◽  
Angular Frequency ◽  
Data Set ◽  
Surface Reflection ◽  
Reflection Data ◽  
Seismic Depth Migration

Seismic depth migration back-propagates seismic data in the correct depth position using information about the velocity of the medium. Usually, Kirchhoff summation is the preferred migration procedure for seismic-while-drilling (SWD) data because it can handle virtually any configuration of sources and receivers and one can compensate for irregular spatial sampling of the array elements (receivers and sources). Under the assumption of a depth-varying velocity model, with receivers arranged along a horizontal circumference and sources placed along the central vertical axis, we reformulate the Kirchhoff summation in the angular frequency domain. In this way, the migration procedure becomes very efficient because the migrated volume is obtained by an inverse Fourier transform of the weighted data. The algorithm is suitable for 3D SWD acquisitions when the aforementioned hypothesis holds. We show migration tests on SWD synthetic data, and we derive solutions to reduce the migration artifacts and to control aliasing. The procedure is also applied on a real 3D SWD data set. The result compares satisfactorily with the seismic stack section obtained from surface reflection data and with the results from traditional Kirchhoff migration.

Dirty salt velocity inversion: The road to a clearer subsalt image

Geophysics ◽  
2011 ◽  
Vol 76 (5) ◽  
pp. WB169-WB174 ◽  
Author(s):  
Shuo Ji ◽  
Tony Huang ◽  
Kang Fu ◽  
Zhengxue Li
Keyword(s):  
Model Building ◽  
Synthetic Data ◽  
Velocity Model ◽  
Reverse Time ◽  
Reverse Time Migration ◽  
Data Set ◽  
Velocity Inversion ◽  
Time Migration ◽  
And Migration ◽  
Subsalt Imaging

For deep-water Gulf of Mexico, accurate salt geometry is critical to subsalt imaging. This requires the definition of both external and internal salt geometries. In recent years, external salt geometry (i.e., boundaries between allochthonous salt and background sediment) has improved a great deal due to advances in acquisition, velocity model building, and migration algorithms. But when it comes to defining internal salt geometry (i.e., intrasalt inclusions or dirty salt), no efficient method has yet been developed. In common industry practices, intrasalt inclusions (and thus their velocity anomalies) are generally ignored during the model building stages. However, as external salt geometries reach higher levels of accuracy, it becomes more important to consider the once-ignored effects of dirty salt. We have developed a reflectivity-based approach for dirty salt velocity inversion. This method takes true-amplitude reverse time migration stack volumes as input, then estimates the dirty salt velocity based on reflectivity under a 1D assumption. Results from a 2D synthetic data set and a real 3D Wide Azimuth data set demonstrated that the reflectivity inversion scheme significantly improves the subsalt image for certain areas. In general, we believe that this method produces a better salt model than the traditional clean salt velocity approach.

scholarly journals A flexible framework for sequential estimation of model parameters in computational hemodynamics

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Christopher J. Arthurs ◽  
Nan Xiao ◽  
Philippe Moireau ◽  
Tobias Schaeffter ◽  
C. Alberto Figueroa
Keyword(s):  
Unscented Kalman Filter ◽  
Three Dimensional ◽  
Synthetic Data ◽  
Sequential Estimation ◽  
Wall Material ◽  
Patient Specific ◽  
Model Parameters ◽  
Computational Framework ◽  
Lumped Parameter ◽  
Estimation Of Model Parameters

AbstractA major challenge in constructing three dimensional patient specific hemodynamic models is the calibration of model parameters to match patient data on flow, pressure, wall motion, etc. acquired in the clinic. Current workflows are manual and time-consuming. This work presents a flexible computational framework for model parameter estimation in cardiovascular flows that relies on the following fundamental contributions. (i) A Reduced-Order Unscented Kalman Filter (ROUKF) model for data assimilation for wall material and simple lumped parameter network (LPN) boundary condition model parameters. (ii) A constrained least squares augmentation (ROUKF-CLS) for more complex LPNs. (iii) A “Netlist” implementation, supporting easy filtering of parameters in such complex LPNs. The ROUKF algorithm is demonstrated using non-invasive patient-specific data on anatomy, flow and pressure from a healthy volunteer. The ROUKF-CLS algorithm is demonstrated using synthetic data on a coronary LPN. The methods described in this paper have been implemented as part of the CRIMSON hemodynamics software package.

scholarly journals Structure-controlled asperities of the 1920 Haiyuan M8.5 and 1927 Gulang M8 earthquakes, NE Tibet, China, revealed by high-resolution seismic tomography

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Quan Sun ◽  
Shunping Pei ◽  
Zhongxiong Cui ◽  
Yongshun John Chen ◽  
Yanbing Liu ◽  
...  
Keyword(s):  
High Resolution ◽  
Seismic Tomography ◽  
High Velocity ◽  
Three Dimensional ◽  
Large Earthquake ◽  
Velocity Model ◽  
Tectonic Stress ◽  
Double Difference ◽  
Source Regions ◽  
Large Earthquakes

AbstractDetailed crustal structure of large earthquake source regions is of great significance for understanding the earthquake generation mechanism. Numerous large earthquakes have occurred in the NE Tibetan Plateau, including the 1920 Haiyuan M8.5 and 1927 Gulang M8 earthquakes. In this paper, we obtained a high-resolution three-dimensional crustal velocity model around the source regions of these two large earthquakes using an improved double-difference seismic tomography method. High-velocity anomalies encompassing the seismogenic faults are observed to extend to depths of 15 km, suggesting the asperity (high-velocity area) plays an important role in the preparation process of large earthquakes. Asperities are strong in mechanical strength and could accumulate tectonic stress more easily in long frictional locking periods, large earthquakes are therefore prone to generate in these areas. If the close relationship between the aperity and high-velocity bodies is valid for most of the large earthquakes, it can be used to predict potential large earthquakes and estimate the seismogenic capability of faults in light of structure studies.

Comparison of the S/N ratios of low-frequency hydrophones and geophones as a function of ocean depth

1981 ◽  
Vol 71 (5) ◽  
pp. 1649-1659
Author(s):  
Thomas M. Brocher ◽  
Brian T. Iwatake ◽  
Joseph F. Gettrust ◽  
George H. Sutton ◽  
L. Neil Frazer
Keyword(s):  
Nova Scotia ◽  
Continental Margin ◽  
Low Frequency ◽  
Weather Conditions ◽  
Ocean Bottom ◽  
Ocean Bottom Seismometer ◽  
Scotian Shelf ◽  
Ocean Bottom Seismometers ◽  
Particle Velocities ◽  
Refraction Data

abstract The pressures and particle velocities of sediment-borne signals were recorded over a 9-day period by an array of telemetered ocean-bottom seismometers positioned on the continental margin off Nova Scotia. The telemetered ocean-bottom seismometer packages, which appear to have been very well coupled to the sediments, contained three orthogonal geophones and a hydrophone. The bandwidth of all sensors was 1 to 30 Hz. Analysis of the refraction data shows that the vertical geophones have the best S/N ratio for the sediment-borne signals at all recording depths (67, 140, and 1301 m) and nearly all ranges. The S/N ratio increases with increasing sensor depth for equivalent weather conditions. Stoneley and Love waves detected on the Scotian shelf (67-m depth) are efficient modes for the propagation of noise.

Velocity inversion by global optimization using finite-offset common-reflection-surface stacking applied to synthetic and Tacutu Basin seismic data

Geophysics ◽  
2019 ◽  
Vol 84 (2) ◽  
pp. R165-R174 ◽  
Author(s):  
Marcelo Jorge Luz Mesquita ◽  
João Carlos Ribeiro Cruz ◽  
German Garabito Callapino
Keyword(s):  
Objective Function ◽  
Real Data ◽  
Velocity Model ◽  
Data Sets ◽  
Layer By Layer ◽  
Velocity Inversion ◽  
Very Fast Simulated Annealing ◽  
Target Layer ◽  
Common Reflection Surface ◽  
The Mean

Estimation of an accurate velocity macromodel is an important step in seismic imaging. We have developed an approach based on coherence measurements and finite-offset (FO) beam stacking. The algorithm is an FO common-reflection-surface tomography, which aims to determine the best layered depth-velocity model by finding the model that maximizes a semblance objective function calculated from the amplitudes in common-midpoint (CMP) gathers stacked over a predetermined aperture. We develop the subsurface velocity model with a stack of layers separated by smooth interfaces. The algorithm is applied layer by layer from the top downward in four steps per layer. First, by automatic or manual picking, we estimate the reflection times of events that describe the interfaces in a time-migrated section. Second, we convert these times to depth using the velocity model via application of Dix’s formula and the image rays to the events. Third, by using ray tracing, we calculate kinematic parameters along the central ray and build a paraxial FO traveltime approximation for the FO common-reflection-surface method. Finally, starting from CMP gathers, we calculate the semblance of the selected events using this paraxial traveltime approximation. After repeating this algorithm for all selected CMP gathers, we use the mean semblance values as an objective function for the target layer. When this coherence measure is maximized, the model is accepted and the process is completed. Otherwise, the process restarts from step two with the updated velocity model. Because the inverse problem we are solving is nonlinear, we use very fast simulated annealing to search the velocity parameters in the target layers. We test the method on synthetic and real data sets to study its use and advantages.

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